The Centre for Internet and Society
http://editors.cis-india.org
These are the search results for the query, showing results 11 to 19.
Call for Proposal: Big Data for Development – Initial Field Studies
http://editors.cis-india.org/jobs/call-for-proposal-big-data-for-development-field-studies
<b>The Centre for Internet and Society, as part of a project with the University of Manchester and University of Sheffield, is inviting calls from researchers to undertake a brief initial study of a specific instance of use of big data for development in India. This is an exercise to build preliminary understanding of the landscape of big data for development in India, identify key research questions and priorities, and start developing connections with researchers interested in the field. The studies will be 6 weeks long - running from May to June 2016 - and the researchers are expected to produce a 3,000 words long report. We will support three field studies.</b>
<p> </p>
<h3>Study Process and Deliverable</h3>
<p>The researcher is expected to propose and undertake a 6 weeks long study – starting from <strong>May 09</strong> and ending on <strong>June 17</strong> – of an instance of big data is being used to inform, target, operationalise, monitor, or support developmental and/or humanitarian activity in India.</p>
<p>During this period, the researcher is expected to interview <strong>4-5</strong> persons directly involved in the big data for development project concerned, and <strong>2-3</strong> other persons to get a wider sense of the context of the project.</p>
<p>By the end of the 6 weeks period, the researcher is expected to submit a <strong>3,000 words</strong> long report. The report will be commented upon by Prof. Richard Heeks (University of Manchester), Dr. Christopher Foster (University of Sheffield), and Sumandro Chattapadhyay (CIS), and revised accordingly during the last weeks of June.</p>
<p>The individual reports will be published independently and as part of the larger project report, under Creative Commons <a href="https://creativecommons.org/licenses/by/4.0/">Attribution 4.0 International</a> license. The authors will be attributed appropriately.</p>
<p>All researchers will take part in a work-in-progress meeting (held over internet) during last week of May or first week of June.</p>
<h3>Research Questions</h3>
<p>The interviews will focus on the following topics:</p>
<ul><li><strong>Innovation:</strong> What is the nature of the innovation being done by the use of big data? What technical systems and/or applications are being deployed and replaced/superceded? Who are key actors in this innovation process?</li>
<li><strong>Implementation:</strong> What is the grounded experience of implementing the big data technology? What are the key enablers and constraints being faced, both in the data collection stage, and the analysis and decision making stage?</li>
<li><strong>Value:</strong> What is the value being created, and how is it understood? Is it organisational value, or socio-economic value? Who is gaining this value?</li>
<li><strong>Ethics:</strong> What ethical concerns are emerging? Do they involve concerns about data quality, representation, privacy, or security? Is there concerns about a data divide being created among people who are represented in data and who are not, or among people who can gain value from the data and who cannot?</li></ul>
<h3>Application, Eligibility, and Remuneration</h3>
<p>Please submit the following documents to apply:</p>
<ul><li><strong>Proposal:</strong> A one page note on the big data for development project that you would like to study. Please share a brief description of the project and how you will study it, including the name/designation of key people you will speak to.</li>
<li><strong>Writing Sample:</strong> An article or a collection of articles, of not more than 8,000 words length in total.</li>
<li><strong>CV:</strong> A short CV, two pages or less.</li></ul>
<p>Please e-mail the documents to <strong>raw[at]cis-india[dot]org</strong> by <strong>Wednesday, May 04</strong>, 2016.</p>
<p>There is <strong>no eligibility criteria</strong> for submitting proposals. However, we will prioritise researchers living and studying big data for development projects in <strong>non <a href="https://en.wikipedia.org/wiki/Classification_of_Indian_cities">X-class</a> cities</strong>, that is in cities other than Ahmedabad, Bangalore, Chennai, Delhi, Hyderabad, Kolkata, Mumbai, and Pune.</p>
<p>We will select <strong>three</strong> researchers, and will offer <strong>Rs. 35,000</strong> to each of them for this study. The amount will be paid in a <strong>single</strong> installment, <strong>after</strong> the draft field study report is submitted for comments.</p>
<p> </p>
<p>
For more details visit <a href='http://editors.cis-india.org/jobs/call-for-proposal-big-data-for-development-field-studies'>http://editors.cis-india.org/jobs/call-for-proposal-big-data-for-development-field-studies</a>
</p>
No publishersumandroBig DataData SystemsBig Data for DevelopmentResearchResearchers at Work2016-04-28T07:28:23ZBlog EntryBrindaalakshmi.K - Gendering of Development Data in India: Beyond the Binary
http://editors.cis-india.org/raw/brindaalakshmi-k-gendering-development-data-india
<b>This report by Brindaalakshmi.K seeks to understand the gendering of development data in India: collection of data and issuance of government (foundational and functional) identity documents to persons identifying outside the cis/binary genders of female and male, and the data misrepresentations, barriers to accessing public and private services, and
informational exclusions that still remain. Sumandro Chattapadhyay edited the report and Puthiya Purayil Sneha offered additional editorial support. This work was undertaken as part of the Big Data for Development network supported by International Development Research Centre (IDRC), Canada.</b>
<p> </p>
<h4>Part 1 - Introduction, Research Method, and Summary of Findings: <a href="https://cis-india.org/raw/files/brindaalakshmi-k-gendering-of-development-data-in-india-beyond-the-binary-1" target="_blank">Download</a> (PDF)</h4>
<h4>Part 2 - Legal Rights and Enumeration Process: <a href="https://cis-india.org/raw/files/brindaalakshmi-k-gendering-of-development-data-in-india-beyond-the-binary-2" target="_blank">Download</a> (PDF)</h4>
<h4>Part 3 - Identity Documents and Access to Welfare: <a href="https://cis-india.org/raw/files/brindaalakshmi-k-gendering-of-development-data-in-india-beyond-the-binary-3" target="_blank">Download</a> (PDF)</h4>
<h4>Part 4 - Digital Services and Data Challenges: <a href="https://cis-india.org/raw/files/brindaalakshmi-k-gendering-of-development-data-in-india-beyond-the-binary-4" target="_blank">Download</a> (PDF)</h4>
<hr />
<p>India has been under a national lockdown due to the global outbreak of the COVID-19 pandemic since late March 2020. Although transgender persons or individuals who do not identify with the gender of their assigned sex at birth, fall into the eligibility category for the relief measures announced by the State, the implementation of the relief measures has seen to be inefficient in different states [1] of the country [2]. Many transgender persons still do not have proper identification documents in their preferred name and gender that can help them with claiming any welfare that is available [3].</p>
<p>Historically, the situation of transgender persons in India has been so, even prior to the present pandemic. A qualitative research study titled <em>Gendering of Development Data in India: Beyond the Binary</em> was undertaken during October 2018 - December 2019, to understand the gendering of development data in India, collection of data and issuance of government (foundational and functional) identity documents to persons identifying outside the cis/binary genders of female and male, and the data misrepresentations, barriers to accessing public and private services, and informational exclusions that still remain.</p>
<p>The interviews for this study were conducted in late 2018 and this report was completed in the beginning of 2020, after India went through an extended national debate on and finally enactment of the Transgender Persons (Protection of Rights) Act during 2019. Three key observations from this study are presented in this blog post. Although these observations were made prior to the release of the draft rules of the new law, it is important to note that the law along with the draft rules in its present version will likely aggrevate the data and social exclusions faced by the transgender community in India.</p>
<h4>Observation 1: The need for data has sidestepped the state’s responsibility to address the human rights of its people</h4>
<p>The present global development agenda is to <em>leave no one behind</em> [4]. The effort to leave no one behind has shifted the focus of the state towards collecting data on different population groups. The design of and access to welfare programmes relies heavily on the availability of data. The impact of these programmes are again measured and understood as reflected by data. This shift in focus to data has led to further exclusion of already disenfranchised groups including the transgender community [5]. The problem with this lies in the framing of the development discourse as one that demands data as the prerequisite to access welfare benefits.</p>
<p>However, there are significant issues with the data on transgender persons that has been fed into different national and state-level databases, beginning with the census of 2011. For the first time, census of 2011 attempted to enumerate transgender persons. However, the enumeration of transgender persons for the census of 2011 has been severely criticised by the transgender community due to lack of</p>
<ul>
<li>Clear distinction between sex and gender in the census data collection process,</li>
<li>Community consultation in designing the enumeration process, and</li>
<li>Inclusion of all transgender identities, among others.</li></ul>
<p>However, this flawed data set is being used as the primary data for fund allocation across different states for transgender people’s inclusion, note respondents. Further, any person identifying outside the gender of their assigned sex at birth faces the additional burden of proving their gender identity to access any welfare benefit. However, cisgendered men or women are never asked to prove their gender identity. The need for data from a marginalised population group without addressing the structural problems has only led to further exclusion of this already invisible group of individuals, note respondents. Further, the Transgender Persons (Protection of Rights) Act, 2019 was passed despite the severe criticisms from the transgender community, human rights activist groups [6] and even opposition political parties [7] in India for several reasons [8].</p>
<h4>Observation 2: Replication of existing offline challenges by digital systems in multiple data sources, continues to keep transgender persons excluded</h4>
<p>Digitisation was supposed to remove existing offline challenges and enable more people centric systems [9]. However, digital systems seem to have replicated the existing offline challenges. In several cases, digitisation has added to the complexities involved.</p>
<p>The replication of challenges begins with the assumption that digital processes are the best way to collect data on transgender persons. Both level of literacy and digital literacy are low among transgender persons in India. According to a report by the National Human Rights Commission [10], nearly 50% of transgender persons have studied less than Class X. This has a significant effect on their access to different rights.</p>
<p>Access to mobile phones is assumed to bridge this access gap to online systems and services. However, observations from different respondents suggest otherwise. Additionally, due to their gender identity, transgender individuals face different set of challenges in procuring valid identification documents required to enter data systems, note respondents. This includes but not limited to:</p>
<ul>
<li>Lack of standardised online or offline processes to aid in changing their documents and vary within each state in different documents.</li>
<li>Procuring any identification document in preferred name and gender requires existing identification documents in given name and assigned gender, in both online and offline processes. However, due to the stigma with their gender identity, transgender persons often run away from home with no identification document in their assigned name and gender.</li>
<li>With or without an existing ID document, individuals have to go through a tedious offline legal process to change their name and gender on different documents.</li>
<li>Information on such processes, digital or otherwise are usually available only to individuals who are educated or associated with a non-profit organisation working with the community. The challenges are higher for individuals with neither.</li></ul>
<h4>Observation 3: Private big data is not good enough as an alternative source of evidence for designing welfare services for transgender persons</h4>
<p>Globally, public private partnerships for big data are being pushed through different initiatives like Data Collaboratives [11] and UN Global Pulse [12], among others. These private partnerships are being seen as key to using big data for official statistics, which can then aid in making welfare decisions [13]. However, the respondents note that the different private big data sources are not good enough to make welfare decisions for various reasons including but not limited to:</p>
<ul>
<li><strong>Dependency on government documents:</strong> Access to any private service system like banking, healthcare, housing or education by any individual requires verification using some proof of identity. The discrimination and challenges in procuring government issued identification documents impacts the ability of transgender persons to enter private data systems. This in turn impacts their access to services.</li>
<li><strong>Misrepresentation in data:</strong> The dependency of private services on government issued documents / government recorded data, and hierarchy among such documents/data and the continued misrepresentation of transgender people, impacts the big data generated by private service providers. Due to the stigma faced, many transgender persons avoid using public healthcare systems for other medical conditions. The heavy dependency on private health care and lower usage of public health systems, results in insufficient big data on transgender persons, created by both public and private medical care and hence cannot be used to design health related welfare services.
</li><li><strong>Social media data issues:</strong> Different websites and apps also use social media login as the ID verification mechanism. Since not all transgender persons are out to their family and friends about their gender identity, they often tend to have multiple social media accounts with different names and gender to protect their identity. When open about their gender identity, harassment and bullying of transgender persons with violent threats or sexually lucid remarks are quite common on social media platforms. Online privacy therefore continues to be a serious concern for them. Disclosing their transgender status also enables the system to predict user patterns of a vulnerable group with potential for abuse, note respondents.</li></ul>
<p>In conclusion, the present global pandemic has further amplified the inherent flaws in the present data-driven welfare system in the country and its impacts on a marginalised population group like transgender persons in the country. Globally, gender in development data is seen in binary genders of male and female, leaving behind transgender individuals or those who do not identify with the gender of their assigned sex at birth. So the dominant binary gender data conversation is in fact leaving people behind. With the regressive Transgender Persons (Protection of Rights) Act of 2019 and its rules, this inadequacy in the global development agenda related to gender equality is felt at an amplified scale.</p>
<p>Building on the work of Dr. Usha Ramanathan, a renowned human rights activist, I say that data collection and monitoring systems that tag, track, and profile transgender persons placing them under surveillance, have consequences beyond the denial of services, and enter into the arena of criminalising for being beyond the binary [14]. The vulnerabilities of their gender identity exacerbates the threat to freedom. With their freedom threatened, expecting people to be forthcoming about self-identifying themselves in their preferred name and gender, so as to ensure that they are counted in data-driven development interventions and can thus access their constitutionally guaranteed rights, goes against the very idea of sustainable development and human rights.</p>
<p> </p>
<h4>References</h4>
<p>[1] Kumar. V (2020, May 13). In Jharkhand, a Mockery of 'Right to Food' as Lockdown Relief Measures Fail to Deliver. The Wire. Retrieved from: <a href="https://thewire.in/food/lockdown-jharkhand-hunger-deaths-corruption-food" target="_blank">https://thewire.in/food/lockdown-jharkhand-hunger-deaths-corruption-food</a></p>
<p>[2] Manoj. C.K. (2020, April 24). COVID-19: Thousands pushed to starvation due to faulty biometric system in Bihar. DownToEarth. Retrieved from: <a href="https://www.downtoearth.org.in/news/food/covid-19-thousands-pushed-to-starvation-due-to-faulty-biometric-system-in-bihar-70681" target="_blank">https://www.downtoearth.org.in/news/food/covid-19-thousands-pushed-to-starvation-due-to-faulty-biometric-system-in-bihar-70681</a></p>
<p>[3] G. Ram Mohan. (2020, May 01). Eviction Fear Heightens as Lockdown Signals Loss of Livelihood for Transgender People. The Wire. Retrieved from: <a href="https://thewire.in/rights/transgender-people-lockdown-coronavirus" target="_blank">https://thewire.in/rights/transgender-people-lockdown-coronavirus </a></p>
<p>[4] UN Statistics (2016). The Sustainable Development Goals Report 2016. United Nations Statistics. Retrieved from: <a href="https://unstats.un.org/sdgs/report/2016/leaving-no-one-behind" target="_blank">https://unstats.un.org/sdgs/report/2016/leaving-no-one-behind</a></p>
<p>[5] Chakrabarti. A (2020, April 25). Visibly Invisible: The Plight Of Transgender Community Due To India's COVID-19 Lockdown. Outlook. Retrieved from: <a href="https://www.outlookindia.com/website/story/opinion-visibly-invisible-the-plight-of-transgender-community-due-to-indias-covid-19-lockdown/351468" target="_blank">https://www.outlookindia.com/website/story/opinion-visibly-invisible-the-plight-of-transgender-community-due-to-indias-covid-19-lockdown/351468</a></p>
<p>[6] Knight Kyle. (2019, December 05). India’s Transgender Rights Law Isn’t Worth Celebrating. Human Rights Watch. Retrieved from: <a href="https://www.hrw.org/news/2019/12/06/indias-transgender-rights-law-isnt-worth-celebrating" target="_blank">https://www.hrw.org/news/2019/12/06/indias-transgender-rights-law-isnt-worth-celebrating</a></p>
<p>[7] Dharmadhikari Sanyukta. (2019). Trans Bill 2019 passed in Lok Sabha: Why the trans community in India is rejecting it. The News Minute. August 05. Retrieved from: <a href="https://www.thenewsminute.com/article/trans-bill-2019-passed-lok-sabha-why-trans-community-india-rejecting-it-106695" target="_blank">https://www.thenewsminute.com/article/trans-bill-2019-passed-lok-sabha-why-trans-community-india-rejecting-it-106695</a></p>
<p>[8] Editorial. (2018, December 20). Rights, revised: on the Transgender Persons Bill, 2018. The Hindu. Retrieved from: <a href="https://www.thehindu.com/opinion/editorial/rights-revised/article25783926.ece" target="_blank">https://www.thehindu.com/opinion/editorial/rights-revised/article25783926.ece</a></p>
<p>[9] Ministry of Electronics and Information Technology, Government of India. (2018). National e-Governance Plan. Retrieved from: <a href="https://meity.gov.in/divisions/national-e-governance-plan" target="_blank">https://meity.gov.in/divisions/national-e-governance-plan</a></p>
<p>[10] Kerala Development Society. (2017, February). <em>Study on Human Rights of Transgender as a Third Gender</em>. Retrieved from: <a href="https://nhrc.nic.in/sites/default/files/Study_HR_transgender_03082018.pdf" target="_blank">https://nhrc.nic.in/sites/default/files/Study_HR_transgender_03082018.pdf</a></p>
<p>[11] Verhulst, S. G., Young, A., Winowatan, M., & Zahuranec, A. J. (2019, October). <em>Leveraging Private Data for Public Good: A Descriptive Analysis and Typology of Existing Practices</em>. GovLab, Tandon School of Engineering, New York University. Retrieved from: <a href="https://datacollaboratives.org/static/files/existing-practices-report.pdf" target="_blank">https://datacollaboratives.org/static/files/existing-practices-report.pdf</a></p>
<p>[12] Kirkpatrick, R., & Vacarelu, F. (2018, December). A Decade of Leveraging Big Data for Sustainable Development. UN Chronicle, Vol. LV, Nos. 3 & 4. Retrieved from: <a href="https://unchronicle.un.org/article/decade-leveraging-big-data-sustainable-development" target="_blank">https://unchronicle.un.org/article/decade-leveraging-big-data-sustainable-development</a></p>
<p>[13] See [11].</p>
<p>[14] Ramanathan. U. (2014, May 02). Biometrics Use for Social Protection Programmes in India Risk Violating Human Rights of the Poor. UNRISD. Retrieved from: <a href="http://www.unrisd.org/sp-hr-ramanathan" target="_blank">http://www.unrisd.org/sp-hr-ramanathan</a></p>
<p> </p>
<p>
For more details visit <a href='http://editors.cis-india.org/raw/brindaalakshmi-k-gendering-development-data-india'>http://editors.cis-india.org/raw/brindaalakshmi-k-gendering-development-data-india</a>
</p>
No publisherBrindaalakshmi.KWelfare GovernanceData SystemsBig Data for DevelopmentResearchGender, Welfare, and PrivacyTransgenderResearchers at Work2020-06-30T10:26:40ZBlog EntryTo be Counted When They Count You: Words of Caution for the Gender Data Revolution
http://editors.cis-india.org/raw/to-be-counted-when-they-count-you-words-of-caution-for-the-gender-data-revolution
<b>In 2015, after the announcement of the SDGs or Sustainable Development Goals, a new global developmental framework through the year 2030, the United Nations described data as the “lifeblood of decision-making and the raw material for accountability” for the purpose of realizing these developmental goals. This curious yet key link between these new developmental goals and the use of quantitative data for agenda setting invited a flurry of big data-led initiatives such as but not limited to Data2X, that sought to further strengthen and solidify the relationship between ‘Big Development’ and ‘Big Data.’</b>
<p style="text-align: justify; ">One of those SDG goals (Goal 5) prioritizes gender equality and empowerment of women and girls not only as a standalone goal but also as a crucial factor to realizing the other goals. In response, several academic and non-profit initiatives have begun to interpret and conduct data-led gendered development or the “gender data revolution”. As with other data discourses, the gender-data discourse is also one of ‘speed’, charging ahead using a variety of quantitative and visualization approaches to reveal and eventually solve gendered problems of development.</p>
<p style="text-align: justify; ">These interventions also invite some classical critical questions: who is setting the agenda for the gender data revolution and who are its imagined subjects? How are questions of participation and asymmetries of power in developmental research being addressed? How does the gender data revolution address the situatedness as well as incompleteness of data records in the Global South (where most sites of intervention are)? Speaking specifically to the theme of this special issue (‘cross-cultural feminist technologies’), this paper demonstrates how the welfarist discourse of data-led gender development is, in fact, assembled through the overwhelming enumeration of female-identifying bodies in the Global South.</p>
<p style="text-align: justify; ">The paper offers critical historical insights from the fields of international development, anthropology, and postcolonial history to caution against both, the possible harms of gender disaggregated datafication as well as the consequences of non-participatory datafication of women, the subjects of the gender data revolution.</p>
<p style="text-align: justify; ">Read the full paper <strong><a href="http://editors.cis-india.org/raw/to-be-counted-when-they-count-you.pdf" class="internal-link">here</a></strong>.</p>
<p style="text-align: justify; ">This study was undertaken as part of the Big Data for Development network supported by the International Development Research Centre, Canada, and is shared under Creative Commons Attribution 4.0 International license.</p>
<hr />
<p style="text-align: justify; "><span class="discreet">The views and opinions expressed on this page are those of their individual authors. Unless the opposite is explicitly stated, or unless the opposite may be reasonably inferred, CIS does not subscribe to these views and opinions which belong to their individual authors. CIS does not accept any responsibility, legal or otherwise, for the views and opinions of these individual authors. For an official statement from CIS on a particular issue, please contact us directly.</span></p>
<p>
For more details visit <a href='http://editors.cis-india.org/raw/to-be-counted-when-they-count-you-words-of-caution-for-the-gender-data-revolution'>http://editors.cis-india.org/raw/to-be-counted-when-they-count-you-words-of-caution-for-the-gender-data-revolution</a>
</p>
No publishernoopurRAW PublicationsBig DataResearchers at WorkBD4DRAW ResearchBig Data for Development2022-02-01T01:06:08ZBlog EntryIs India's Digital Health System Foolproof?
http://editors.cis-india.org/raw/is-indias-digital-health-system-foolproof
<b>This contribution by Aayush Rathi builds on "Data Infrastructures and Inequities: Why Does Reproductive Health Surveillance in India Need Our Urgent Attention?" (by Aayush Rathi and Ambika Tandon, EPW Engage, Vol. 54, Issue No. 6, 09 Feb, 2019) and seeks to understand the role that state-run reproductive health portals such as the Mother and Child Tracking System (MCTS) and the Reproductive and Child Health will play going forward. The article critically outlines the overall digitised health information ecosystem being envisioned by the Indian state.</b>
<p> </p>
<h4>This article was first published in <a href="https://www.epw.in/engage/article/indias-digital-health-paradigm-foolproof" target="_blank">EPW Engage, Vol. 54, Issue No. 47</a>, on November 30, 2019</h4>
<hr />
<p>Introduced in 2013 and subsequently updated in 2016, the Ministry of Health and Family Welfare (MHFW) published a document laying out the standards for electronic health records (EHRs). While there exist varying interpretations of what constitutes as EHRs, some of its characteristics include electronic medical records (EMRs) of individual patients, arrangement of these records in a time series, and inter-operable linkages of the EMRs across various healthcare settings (Häyrinen et al 2008; OECD 2013).</p>
<p>To work effectively, EHRs are required to be highly interoperable so that they can facilitate exchange among health information systems (HIS) across participating hospitals. For this, the Integrated Health Information Platform (IHIP) is being developed so as to assimilate data from various registries across India and provide real-time information on health surveillance (Krishnamurthy 2018).</p>
<h3><strong>EHR Implementation: Unpacking the (Dis)incentive Structure</strong></h3>
<p>As the implementation of EHR standards is voluntary, anecdotal evidence indicates that their uptake in the Indian healthcare sector has been very slow. Here, the opposition of the Indian Medical Association to the Clinical Establishments (Registration and Regulation) Act, 2010, resulting in nationwide protests and subsequent legal challenges to the act, is instructive. To start with, the act prescribes the minimum standards that have to be maintained by clinical establishments which are registered or seeking registration (itself mandatory to run a clinic under the act) <strong>[1]</strong>. Further, Rule 9(ii) of the Clinical Establishments (Registration and Regulation) Rules, 2012, drafted under the act, requires clinical establishments to maintain EMRs or EHRs for every patient. However, with health being a state subject in India, the act has only been enforced in 11 states and all union territories except the National Capital Territory of Delhi (Jyoti 2018). The resistance to the act is largely due to protests by stakeholders from within the medical fraternity regarding its adverse impact on small- and medium-sized hospitals (Jyoti 2018).</p>
<h3><strong>Contextualising Clinicians' Inertia</strong></h3>
<p>Another major impediment to the adoption of EHRs by health service providers is reluctance on the part of individual physicians to transition to an EHR system. This is because compliance with EHR standards requires physicians to input clinical notes themselves.</p>
<p>Comparing the greater patient load faced by doctors in India vis-à-vis the United States (US), the chief medical officer of an EHR vendor in India estimates that the average Indian doctor sees about 40–60 patients a day, whereas in the US it may be around 18–20 patients (Kandhari 2017). This is suggestive of the wide disparity in the number of physicians per 1,000 citizens in both countries (World Bank nd). Given this, doctors in India tend to be more problem-oriented, time-strapped, and pay less attention to clinical notes (Kandhari 2017). Thus, clinicians will consider a system to be efficient only if the system reduces their documentation time, even if the time savings do not translate into better patient care (Allan and Englebright 2000). The inability of EHRs to help reduce documentation time deters clinicians from supporting their implementation (Poon et al 2004). Additionally, research done in the United States indicates that there is no evidence to suggest that an information system helps save time expended by clinicians on documentation (Daly et al 2002). Moreover, the use of an information system is stated to have had no impact on patient care, but doctors have acknowledged its use for research purposes (Holzemer and Henry 1992).</p>
<h3><strong>Prohibitive Costs of Implementation</strong></h3>
<p>While national-level EHRs have been adopted globally, their distribution across countries is telling. In a survey published in 2016 by the World Health Organization, wealthier countries were over-represented, with two-thirds from the upper-middle-income group and roughly half from the high-income countries having introduced EHR systems. On the other hand, only a third of lower-middle-income countries and 15% of low-income countries reported having implemented EHRs (World Health Organization 2016). A major reason for the slow uptake of EHRs in poorer countries is likely to be funding as EHR implementation requires considerable investment, with most projects averaging several million dollars (US) (Kuperman and Gibson 2003). Although various funding models for EHR implementation are being utilised globally, it is unclear what model will be adopted in India to bring in private healthcare service providers within its ambit (Healthcare Information and Management Systems Society 2007). This absence of funding direction for private actors poses to be a significant impediment in the integration of private databases with other public ones.</p>
<p>In general, poorer countries are also more likely to have less developed infrastructure and health Information and Communication Technology (ICT) to support EHR systems. Besides this, they not only lack the capacity and human resources required to develop and maintain such complex systems (Tierney et al 2010; McGinn et al 2011), but training periods have also been found to be long and more costly than expected (Kovener et al 1997).</p>
<h3><strong>Socio-economic Exclusions and Cross-cultural Barriers</strong></h3>
<p>There exists scant research investigating the existing use of EHRs in India, though preliminary work is being undertaken to assess EHR implementation in other developing countries (Tierney et al 2010; Fraser et al 2005). Even in the context of developed countries, where widespread adoption of EHRs has been gaining traction for some time now, very little data exists around implementation and efficacy in underserved regions and communities. This is further problematised as clinical information systems and user populations also vary in their characteristics and, for this reason, individual studies are unable to identify common trends that would predict EHR implementation success.</p>
<p>Underserved settings may lack the infrastructure needed to support EHRs. The risk of exclusion already exists in parts such as difficulties inherent in delivering care to remote locations, barriers related to cross-cultural communication, and the pervasive problem of providing care in the setting of severe resource constraints. Equally important is the fact that health workers who already report significant existing impediments in their delivery of routine care in these settings do not necessarily see EHRs as being useful in catering to the specific needs of their patient population (Bach et al 2004). Moreover, experience with EHRs also reveals that there are cultural barriers to capturing accurate data (Miklin et al 2019). What this could mean is that stigma associated with the diagnosis of conditions such as HIV/AIDS or induced abortions will result in their under-reporting even within EHR systems.</p>
<h3><strong>Stick or Twist?</strong></h3>
<p>Other modalities have been devised to nudge healthcare providers into adopting EHR standards voluntarily. The National Accreditation Board for Hospitals and Healthcare Providers (NABH), India, a constituent board of the Quality Council of India (a public–private initiative), has been reported to have incorporated the EHR standards within its accreditation matrix. NABH accreditation, considered an indicator of high quality patient care, is highly sought–after by hospitals in India in order to attract medical tourists as well as insurance companies: two prominent sources of income for hospitals (Kandhari 2017). Additionally, NABH accreditation is valid for a term of three years, thus requiring hospitals seeking to renew their accreditation to adopt EHR standards as well.</p>
<p>Another commercial use of EHR has been in health insurance. The Federation of Indian Chambers of Commerce and Industry (FICCI) and the Insurance Regulatory and Development Authority (IRDAI) have both voiced their support for expediting the implementation of the EHR standards (EMR Standards Committee 2013). Both, the FICCI and IRDAI have placed emphasis on adopting EHRs, seeing it as a necessary move for formalising the health insurance industry (FICCI 2015). They have also had representation on the committee that sent recommendations to the MHFW on the first version of the EHR standards in 2013 (FICCI 2015). FICCI had additionally played a coordination role in having the recommendations framed for the 2013 EHR standards.</p>
<h3><strong>Fluid Data Objectives</strong></h3>
<p>The push for EHR implementation is emblematic of a larger shift in the healthcare approach of the Indian state, that of an indirect targeting of demand-side financing by plugging data inefficiencies in health insurance.</p>
<p>The draft National Health Policy (NHP), published in 2015, reflected the mandate of the Ministry of Health and Family Welfare to strengthen the public health system by creating a right to healthcare legislation and reaching a public spend of 2.5% of the gross domestic product by 2018. The final version of the NHP, published in 2017, however, codified a shift in healthcare policy by focusing on strategic purchasing of secondary and tertiary care services from the private sector and a publicly funded health insurance model.</p>
<p>In line with the vision of the NHP 2017, in February 2018, the Union Minister for Finance and Corporate Affairs, Arun Jaitley, announced two major initiatives as a part of the government’s Ayushman Bharat programme (Ministry of Finance 2018). Administered under the aegis of the Ministry of Health and Family Welfare, these initiatives are intended to improve access to primary healthcare through the creation of 150,000 health and wellness centres as envisioned under the NHP 2017, and improve access to secondary and tertiary healthcare for over 100 million vulnerable families by providing insurance cover of up to ₹ 500,000 per family per year under the Pradhan Mantri–Rashtriya Swasthya Suraksha Mission/National Health Protection Scheme (PM–RSSM/NHPS) (Ministry of Health and Family Welfare 2018). The NHPS, modelled along the lines of the Affordable Care Act in the US, was later rebranded as the Pradhan Mantri–Jan Arogya Yojana (PM-JAY) at the time of its launch in September 2018. It is claimed to be the world’s largest government-funded healthcare programme and is intentioned to provide health insurance coverage for vulnerable sections in lieu of the Sustainable Development Goal-3 (National Health Authority nd).</p>
<p>To enable the implementation of the Ayushman Bharat programme, the NITI Aayog then proposed the creation of a supply-side digital infrastructure called National Health Stack (NHS) (NITI Aayog 2018). As outlined in the consultation and strategy paper, the NHS is “built for NHPS, but beyond NHPS.” The NHS seeks to leverage the digitisation push through IndiaStack, which seeks to digitalise “any large-scale health insurance program, in particular, any government-funded health care programs.” The synergy is clear, with the NHPS scheme also aiming to be “cashless and paperless at public hospitals and empanelled private hospitals" (National Health Authority nd) <strong>[2]</strong>.</p>
<p>The NHS is also closely aligned with the NHP 2017, which draws attention to leveraging technologies such as big data analytics on data stored in universal registries. The Vision document for the NHS emphasises the fragmented nature of health data as an impediment to reducing inequities in healthcare provision. The NHS, then, also seeks to be the master repository of health data akin to the IHIP. By creating a base layer of registries containing information about various actors involved in the healthcare supply chain (providers such as hospitals, beneficiaries, doctors, insurers and Accredited Social Health Activists), it potentially allows for recording of data from both public and private sector entities, plugging a significant gap in the coverage of the HIS currently implemented in India. With the provision of open, pullable APIs, the NHS also shares the motivations of the IndiaStack to monetise health data.</p>
<p>A key component of the proposed NHS is the Coverage and Claims platform, which the vision document describes as “provid[ing] the building blocks required to implement any large-scale health insurance program, in particular, any government-funded healthcare programs. This platform has the transformative vision of enabling both public and private actors to implement insurance schemes in an automated, data-driven manner through open APIs " (NITI Aayog2018). A post on the iSPIRT website further explains the centrality of this Coverage and Claims platform in enabling a highly personalised medical insurance market in India: “This component will not only bring down the cost of processing a claim but ... increased access to information about an individual’s health and claims history ... will also enable the creation of personalised, sachet-sized insurance policies." These data-driven customised insurance policies are expected to generate “care policies that are not only personalized in nature but that also incentivize good healthcare practices amongst consumers and providers … [and] use of techniques from microeconomics to manage incentives for care providers, and those from behavioural economics to incentivise consumers" (Productnation Network 2019). The Coverage and Claims platform, and especially the Policy (generation) Engine that it will contain, is aimed at intensive financialisation of personal healthcare expenses, and extensive experiments with designing personalised nudges to shape the demand behaviour of consumers.</p>
<p>The imagination of healthcare the NHS demonstrates is one where broadening health insurance coverage is equated to providing equitable healthcare and as a panacea for the public healthcare sector. The first phase of this push towards better healthcare provision is to focus on contextualising the historical socio-economic divide. The next phase is characterised by digitalisation: the introduction of ICT to bridge the socio-economic divide in healthcare provision. In this process, the resulting data divide has been invisibilised in reframing better healthcare as an insurance problem for which data needs to be generated. Each policy innovation is then characterised by further marginalisation of those that were originally identified as underserved. This is a result of increasing repercussions of the data-divide, with access to benefits increasingly being mediated by technology.</p>
<h3><strong>Concluding Remarks</strong></h3>
<blockquote>The idea that any person in India can go to any health service provider/ practitioner, any diagnostic center or any pharmacy and yet be able to access and have fully integrated and always available health records in an electronic format is not only empowering but also the vision for efficient 21st century healthcare delivery.<br />
— Ministry of Health and Family Welfare, Electronic Health Record Standards For India (2013)</blockquote>
<p>The objective of health data collection has evolved over the course of the institution of the HIS in 2011, to the development of the NHPS and National Health Policy in 2017. What began as a solution to measure and address gaps in access and quality in healthcare provisioning through data analysis has morphed into data centralisation and insurance coverage. Shifting goalposts can also be found in the objectives behind introducing digital systems to collect data.</p>
<p>In recent iterations of the healthcare imaginary, such as the IHIP and the NHS, data ownership by the beneficiaries is stressed upon. In the absence of a rights-based framework dictating the use of data, the role of ownership should be interrogated, especially in the context of a prevalent data divide (Tisne 2019). The legitimisation of data capture can be seen in the emergence of opt-in models of consent, data fiduciaries managing consent on the data subject’s behalf, etc. (Zuboff 2019).</p>
<p>This framing forecloses a discussion about the quality and kind of data being used. The push towards datafication needs to be questioned for its re-indexing of categorical meaning away from the complexities of narrative, context and history (Cheney-Lippold 2018). Instead, the proposed solution is one that stores datafied elements within a closed set (reproductive health= [abortion, aids, contraceptive,...vaccination, womb]). While this set may be editable, so new interpretations can be codified, it inherently remains stable, assuming a static relationship between words and meaning. Health is then treated as having an empirically definable meaning, thus losing the dynamism of what the health and wellness discourse could entail.</p>
<p>It has been historically demonstrated in the Indian context that multiple tools and databases for health data management are a barrier to an efficient HIS. However, generating centralised or federated databases without addressing concerns in data flows, quality, uses in existing data structures, and the digital divide across health workers and beneficiaries alike will lead to the amplification of existing exclusions in data and, consequently, service provisioning.</p>
<h3><strong>Acknowledgements</strong></h3>
<p>The author would like to express his gratitude to Sumandro Chattapadhyay and Ambika Tandon for their inputs and editorial work on this contribution. This work was supported by the Big Data for Development Network established by International Development Research Centre (Canada).</p>
<h3><strong>Notes</strong></h3>
<p><strong>[1]</strong> Section 2 (a) of the Clinical Establishments (Registration and Regulation) Act, 2010: A hospital, maternity home, nursing home, dispensary, clinic, sanatorium or institution by whatever name called that offers services, facilities requiring diagnosis, treatment or care for illness, injury, deformity, abnormality or pregnancy in any recognised system of medicine established and administered or maintained by any person or body of persons, whether incorporated or not.</p>
<p><strong>[2]</strong> The National Health Stack, then, is the latest manifestation of the Indian government’s push for a “Digital India.” A key component of Digital India has been e-governance, financial inclusion, and digitisation of transaction services. The nudge towards cashless modes of transaction and delivery, also accelerated by India’s demonetisation drive in November 2016, has led to rapid uptake of digital payment services in particular, and that of the IndiaStack initiative in general. Developed by iSPIRT, IndiaStack (https://indiastack.org/) aspires to transform service delivery by public and private actors alike through its “presence-less, paperless, and cashless” mandate.</p>
<h3><strong>References</strong></h3>
<p>Allan, J and Jane Englebright (2000): “Patient-Centered Documentation,” JONA: The Journal of Nursing Administration, Vol 30, No 2, pp 90–95.</p>
<p>Bach, Peter, Hoangmai Pham, Deborah Schrag, Ramsey Tate and J Lee Hargraves (2004): “Primary Care Physicians Who Treat Blacks and Whites,” New England Journal of Medicine, Vol 351, pp 575–84.</p>
<p>Cheney-Lippold, John (2018): We Are Data: Algorithms and the Making of Our Digital Selves, New Delhi: Sage.</p>
<p>Daly, Jeanette, Buckwalter Kathleen and Meridean Maas (2002): “Written and Computerized Care Plans,” Journal of Gerontological Nursing, Vol 28, No 9, pp 14–23.</p>
<p>EMR Standards Committee (2013): “Recommendations on Electronic Medical Records Standards in India,” Ministry of Health and Family Welfare, Government of India, New Delhi, https://mohfw.gov.in/sites/default/files/24539108839988920051EHR%20Standards-v5%20Apr%202013.pdf.</p>
<p>Federation of Indian Chambers of Commerce and Industry (2015): "A Guiding Framework for OPD and Preventive Health Insurance in India: Supply and Demand Side Analysis," http://ficci.in/spdocument/20678/P&P-helath-insurance.pdf.</p>
<p>Fraser, Hamish, Paul Biondich, Deshendran Moodley, Sharon Choi, Burke Mamlin and Peter Szolovits (2005): “Implementing Electronic Medical Record Systems in Developing Countries,” Journal of Innovation in Health Informatics, Vol 13 No 2, pp 83–95.</p>
<p>Häyrinen, Kristiina, Kaija Saranto and Pirkko Nykänen (2008): “Definition, Structure, Content, Use and Impacts of Electronic Health Records: A Review of the Research Literature,” International Journal of Medical Informatics, Vol 77, No 5, pp 291–304.</p>
<p>Healthcare Information and Management Systems Society (2007): “Electronic Health Records: A Global Perspective,” http://www.providersedge.com/ehdocs/ehr_articles/Electronic_Health_Records-A_Global_Perspective-Exec_Summary.pdf.</p>
<p>Holzemer, William and S B Henry (1992): “Computer-supported Versus Manually-generated Nursing Care Plans: A Comparison of Patient Problems, Nursing Interventions, and AIDS Patient Outcomes,” Computers in Nursing, Vol 10 No 1, pp 19–24.</p>
<p>Jha, Ashish, Catherine DesRoches, Eric Campbell, Karen Donelan, Sowmya Rao, Timothy Ferris, Alexandra Shields, Sarah Rosenbaum and David Blumenthal (2009): "Use of Electronic Health Records in U.S. Hospitals," New England Journal of Medicine, Vol 360 No 16, pp 1628–1638.</p>
<p>Jyoti, Archana (2018): “States Give Clinical Establishment Act Cold Shoulder," Pioneer, https://www.dailypioneer.com/2018/india/states-give-clinical-establishment-act-cold-shoulder.html.</p>
<p>Kandhari, Ruhi (2017): “Why a Backdoor Push Towards eHealth,” Ken, https://the-ken.com/story/why-backdoor-push-towards-ehealth/.</p>
<p>Kovner, Christine, Lynda Schuchman and Catherin Mallard (1997): “The Application of Pen-Based Computer Technology to Home Health Care,” CIN: Computers, Informatics and Nursing, Vol 15, No 5, pp 237–44.</p>
<p>Krishnamurthy, R (2018): “Integrated Health Information Platform for Integrated Disease Surveillance Program,” Training of the Trainer Workshop, World Health Organisation, New Delhi, https://idsp.nic.in/WriteReadData/IHIP/IHIP%20ToT-Overview-Presentation.pdf.</p>
<p>Kuperman, Gilad and Richard Gibson (2003): “Computer Physician Order Entry: Benefits, Costs, and Issues,” Annals of Internal Medicine, Vol 139 No 1, pp 31–9.</p>
<p>Leung, Gabriel, Philip Yu, Irene Wong, Janice Johnston and Keith Tin (2003): “Incentives and Barriers That Influence Clinical Computerization in Hong Kong: A Population-based Physician Survey,” Journal of the American Medical Informatics Association, Vol 10 No 2, pp 201–12.</p>
<p>McGinn Carrie Anna, Sonya Grenier, Julie Duplantie, Nicola Shaw, Claude Sicotte, Luc Mathieu, Yvan Leduc, France Légaré and Marie-Pierre Gagnon (2011): “Comparison of User Groups' Perspectives of Barriers and Facilitators to Implementing Electronic Health Records: A Systematic Review,” BMC Medicine, Vol 9 No 46.</p>
<p>Miklin, Daniel, Sameera Vangara, Alan Delamater and Kenneth Goodman (2019): “Understanding of and Barriers to Electronic Health Record Patient Portal Access in a Culturally Diverse Pediatric Population,” JMIR Medical Informatics, Vol 7, No 2.</p>
<p>Ministry of Finance (2018): “Budget 2018-19: Speech of Arun Jaitley,” New Delhi, https://www.indiabudget.gov.in/ub2018-19/bs/bs.pdf.</p>
<p>Ministry of Health and Family Welfare, Government of India (2008): "4 Years of Transforming India-Healthcare for All," New Delhi. https://mohfw.gov.in/ebook2018/gvtbook.html.</p>
<p>Ministry of Health and Family Welfare, Government of India (2013): “Electronic Health Record Standards For India,” Government of India, New Delhi, https://www.nhp.gov.in/NHPfiles/ehr_2013.pdf.</p>
<p>Ministry of Health and Family Welfare, Government of India (2017): Request for Proposal: Development and Implementation of Integrated Health Information Platform (IHIP), Centre for Health Informatics, National Institute of Health and Family Welfare, New Delhi, https://nhp.gov.in/NHPfiles/IHIP_RFP%20.pdf.</p>
<p>Ministry of Health and Family Welfare, Government of India (2018): “IDSP Segment of Integrated Health Information Platform,” New Delhi, https://idsp.nic.in/index4.php?lang=1&level=0&linkid=454&lid=3977.</p>
<p>National Health Authority (nd): “About Pradhan Mantri Jan Arogya Yojana (PM-JAY) | Ayushmaan Bharat,” https://www.pmjay.gov.in/about-pmjay.</p>
<p>NITI Aayog (2018): “National Health Stack- Strategy and Approach,” NITI Aayog, New Delhi, http://www.niti.gov.in/writereaddata/files/document_publication/NHS-Strategy-and-Approach-Document-for-consultation.pdf.</p>
<p>Organisation for Economic Co-operation and Development (2013): “Strengthening Health Information Infrastructure for Health Care Quality Governance: Good Practices, New Opportunities and Data Privacy Protection Challenges,” OECD Health Policy Studies, Paris, OECD Publishing, https://read.oecd-ilibrary.org/social-issues-migration-health/strengthening-health-information-infrastructure-for-health-care-quality-governance_9789264193505-en.</p>
<p>Poon, Eric, David Blumenthal, Tonushree Jaggi, Melissa Honour, David Bates and Rainu Kaushal (2004): “Overcoming Barriers to Adopting and Implementing Computerized Physician Order Entry Systems in U.S. Hospitals,” Health Affairs, Vol 23 No 4, pp 184–90.</p>
<p>Productnation Network (2019): “India’s Health Leapfrog–Towards A Holistic Healthcare Ecosystem,” iSpirt, https://pn.ispirt.in/towards-a-holistic-healthcare-ecosystem/.</p>
<p>Rathi, Aayush and Ambika Tandon (2019): “Data Infrastructures and Inequities: Why Does Reproductive Health Surveillance in India Need Our Urgent Attention?” EPW Engage, https://www.epw.in/engage/article/data-infrastructures-inequities-why-does-reproductive-health-surveillance-india-need-urgent-attention.</p>
<p>Sequist, Thomas, Theresa Cullen, Howard Hays, Maile Taualii, Steven Simon, and David Bates (2007): “Implementation and Use of an Electronic Health Record Within the Indian Health Service,” Journal of the American Medical Informatics Association, Vol 14, No 2, pp 191–97.</p>
<p>World Bank (nd): Physicians (per 1,000 people) | Data, https://data.worldbank.org/indicator/SH.MED.PHYS.ZS.</p>
<p>Tierney, William et al. (2010): “Experience Implementing Electronic Health Records in Three East African Countries,” Studies in Health Technology and Informatics, Vol 160, No 1, pp 371–75.</p>
<p>Tisne, Martin (2018): “It’s Time for a Bill of Data Rights,” MIT Technology Review, https://www.technologyreview.com/s/612588/its-time-for-a-bill-of-data-rights/.</p>
<p>World Health Organization (2016): “Global Diffusion of eHealth: Making Universal Health Coverage Achievable,” https://apps.who.int/iris/bitstream/handle/10665/252529/9789241511780-eng.pdf;jsessionid=9DD5F8603C67EEF35549799B928F3541?sequence=1.</p>
<p>Zuboff, Soshana (2019): The Age of Surveillance Capitalism, New York: PublicAffairs.</p>
<p> </p>
<p>
For more details visit <a href='http://editors.cis-india.org/raw/is-indias-digital-health-system-foolproof'>http://editors.cis-india.org/raw/is-indias-digital-health-system-foolproof</a>
</p>
No publisheraayushEHRBig DataBig Data for DevelopmentResearchBD4DHealthcareResearchers at Work2019-12-30T17:58:00ZBlog EntryReport on Understanding Aadhaar and its New Challenges
http://editors.cis-india.org/internet-governance/blog/report-on-understanding-aadhaar-and-its-new-challenges
<b>The Trans-disciplinary Research Cluster on Sustainability Studies at Jawaharlal Nehru University collaborated with the Centre for Internet and Society, and other individuals and organisations to organise a two day workshop on “Understanding Aadhaar and its New Challenges” at the Centre for Studies in Science Policy, JNU on May 26 and 27, 2016. The objective of the workshop was to bring together experts from various fields, who have been rigorously following the developments in the Unique Identification (UID) Project and align their perspectives and develop a shared understanding of the status of the UID Project and its impact. Through this exercise, it was also sought to develop a plan of action to address the welfare exclusion issues that have arisen due to implementation of the UID Project.</b>
<p> </p>
<h4>Report: <a href="http://editors.cis-india.org/internet-governance/files/report-on-understanding-aadhaar-and-its-new-challenges/at_download/file">Download</a> (PDF)</h4>
<hr />
<p style="text-align: justify;">This Report is a compilation of the observations made by participants at the workshop relating to myriad issues under the UID Project and various strategies that could be pursued to address these issues. In this Report we have classified the observations and discussions into following themes:</p>
<p><strong>1.</strong> <a href="#1">Brief Background of the UID Project</a></p>
<p><strong>2.</strong> <a href="#2">Legal Status of the UIDAI Project</a></p>
<ul>
<li><a href="#21">Procedural issues with passage of the Act</a></li>
<li><a href="#22">Status of related litigation</a></li></ul>
<p><strong>3.</strong> <a href="#3">National Identity Projects in Other Jurisdictions</a></p>
<ul>
<li><a href="#31">Pakistan</a></li>
<li><a href="#32">United Kingdom</a></li>
<li><a href="#33">Estonia</a></li>
<li><a href="#34">France</a></li>
<li><a href="#35">Argentina</a></li></ul>
<p><strong>4.</strong> <a href="#4">Technologies of Identification and Authentication</a></p>
<ul>
<li><a href="#41">Use of Biometric Information for Identification and Authentication</a></li>
<li><a href="#42">Architectures of Identification</a></li>
<li><a href="#43">Security Infrastructure of CIDR</a></li></ul>
<p><strong>5.</strong> <a href="#5">Aadhaar for Welfare?</a></p>
<ul>
<li><a href="#51">Social Welfare: Modes of Access and Exclusion</a></li>
<li><a href="#52">Financial Inclusion and Direct Benefits Transfer</a></li></ul>
<p><strong>6.</strong> <a href="#6">Surveillance and UIDAI</a></p>
<p><strong>7.</strong> <a href="#7">Strategies for Future Action</a></p>
<p><strong>Annexure A</strong> <a href="#AA">Workshop Agenda</a></p>
<p><strong>Annexure B</strong> <a href="#AB">Workshop Participants</a></p>
<hr />
<h3 id="1" style="text-align: justify;"><strong>1. Brief Background of the UID Project</strong></h3>
<p style="text-align: justify;">In the year 2009, the UIDAI was established and the UID project was conceived by the Planning Commission under the UPA government to provide unique identification for each resident in India and to be used for delivery of welfare government services in an efficient and transparent manner, along with using it as a tool to monitor government schemes. The objective of the scheme has been to issue a unique identification number by the Unique Identification Authority of India, which can be authenticated and verified online. It was conceptualized and implemented as a platform to facilitate identification and avoid fake identity issues and delivery of government benefits based on the demographic and biometric data available with the Authority.</p>
<p style="text-align: justify;">The Aadhaar (Targeted Delivery of Financial and Other Subsidies, Benefits and Services) Act, 2016 (the “<strong>Act</strong>”) was passed as a money bill on March 16, 2016 and was notified in the gazette March 25, 2016 upon receiving the assent of the President. However, the enforceability date has not been mentioned due to which the bill has not come into force.</p>
<p style="text-align: justify;">The Act provides that the Aadhaar number can be used to validate a person’s identity, but it cannot be used as a proof of citizenship. Also, the government can make it mandatory for a person to authenticate her/his identity using Aadhaar number before receiving any government subsidy, benefit, or service. At the time of enrolment, the enrolling agency is required to provide notice to the individual regarding how the information will be used, the type of entities the information will be shared with and their right to access their information. Consent of an individual would be obtained for using his/her identity information during enrolment as well as authentication, and would be informed of the nature of information that may be shared. The Act clearly lays that the identity information of a resident shall not be sued for any purpose other than specified at the time of authentication and disclosure of information can be made only pursuant to an order of a court not inferior to that of a District Judge and/or disclosure made in the interest of national security.</p>
<h3 id="2" style="text-align: justify;"><strong>2. Legal Status of the UIDAI Project</strong></h3>
<p style="text-align: justify;">In this section, we have summarised the discussions on the procedural issues with the passage of the Act. The participants had criticised the passage of the Act as a money bill in the Parliament. The participants also assessed the litigation pending in the Supreme Court of India that would be affected by this law. These discussions took place in the session titled, ‘Current Status of Aadhaar’ and have been summarised below.</p>
<h3 id="21" style="text-align: justify;">Procedural Issues with Passage of the Act</h3>
<p style="text-align: justify;">The participants contested the introduction of the Act in the form of a money bill. The rationale behind this was explained at the session and is briefly explained here. Article 110 (1) of the Constitution of India defines a money bill as one containing provisions only regarding the matters enumerated or any matters incidental to the following: a) imposition, regulation and abolition of any tax, b) borrowing or other financial obligations of the Government of India, c) custody, withdrawal from or payment into the Consolidated Fund of India (CFI) or Contingent Fund of India, d) appropriation of money out of CFI, e) expenditure charged on the CFI or f) receipt or custody or audit of money into CFI or public account of India. The Act makes references to benefits, subsidies and services which are funded by the Consolidated Fund of India (CFI), however the main objectives of the Act is to create a right to obtain a unique identification number and provide for a statutory mechanism to regulate this process. The Act only establishes an identification mechanism which facilitates distribution of benefits and subsidies funded by the CFI and this identification mechanism (Aadhaar number) does not give it the character of a money bill. Further, money bills can be introduced only in the Lok Sabha, and the Rajya Sabha cannot make amendments to such bills passed by the Lok Sabha. The Rajya Sabha can suggest amendments, but it is the Lok Sabha’s choice to accept or reject them. This leaves the Rajya Sabha with no effective role to play in the passage of the bill.</p>
<p style="text-align: justify;">The participants also briefly examined the writ petition that has been filed by former Union minister Jairam Ramesh challenging the constitutionality and legality of the treatment of this Act as a money bill which has raised the question of judiciary’s power to review the decisions of the speaker. Article 122 of the Constitution of India provides that this power of judicial review can be exercised to look into procedural irregularities. The question remains whether the Supreme Court will rule that it can determine the constitutionality of the decision made by the speaker relating to the manner in which the Act was introduced in the Lok Sabha. A few participants mentioned that similar circumstances had arisen in the case of Mohd. Saeed Siddiqui v. State of U.P. <a href="#ftn1">[1]</a>.</p>
<p style="text-align: justify;">where the Supreme Court refused to interfere with the decision of the Uttar Pradesh legislative assembly speaker certifying an amendment bill to increase the tenure of the Lokayukta as a money bill, despite the fact that the bill amended the Uttar Pradesh Lokayukta and Up-Lokayuktas Act, 1975, which was passed as an ordinary bill by both houses. The Court in this case held that the decision of the speaker was final and that the proceedings of the legislature being important legislative privilege could not be inquired into by courts. The Court added, “the question whether a bill is a money bill or not can be raised only in the state legislative assembly by a member thereof when the bill is pending in the state legislature and before it becomes an Act.”</p>
<p style="text-align: justify;">However, it is necessary to carve a distinction between Rajya Sabha and State Legislature. Unlike the State Legislature, constitution of Rajya Sabha is not optional therefore significance of the two bodies in the parliamentary process cannot be considered the same. Participants also made another significant observation about a similar bill on the UID project (National Identification Authority of India (NIDAI) Bill) that was introduced before by the UPA government in 2010 and was deemed unacceptable by the standing committee on finance, headed by Yashwant Sinha. This bill was subsequently withdrawn.</p>
<h3 id="22" style="text-align: justify;">Status of Related Litigation</h3>
<p style="text-align: justify;">A panellist in this session briefly summarised all the litigation that was related to or would be affected by the Act. The panellist also highlighted several Supreme Court orders in the case of <em>KS Puttuswamy v. Union of India</em> <a href="#ftn2">[2]</a> which limited the use of Aadhaar. We have reproduced the presentation below.</p>
<ul>
<li style="text-align: justify;"><em>KS Puttuswamy v. Union of India</em> - This petition was filed in 2012 with primary concern about providing Aadhaar numbers to illegal immigrants in India. It was contended that this could not be done without a law establishing the UIDAI and amendment to the Citizenship laws. The petitioner raised concerns about privacy and fallibility of biometrics.</li>
<li style="text-align: justify;"> Sudhir Vombatkere & Bezwada Wilson <a href="#ftn3">[3]</a> - This petition was filed in 2013 on grounds of infringement of right to privacy guaranteed under Article 21 of the Constitution of India and the security threat on account of data convergence.</li>
<li style="text-align: justify;">Aruna Roy & Nikhil Dey <a href="#ftn4">[4]</a> - This petition was filed in 2013 on the grounds of large scale exclusion of people from access to basic welfare services caused by UID. After their petition, no. of intervention applications were filed. These were the following:</li>
<li style="text-align: justify;">Col. Mathew Thomas <a href="#ftn5">[5]</a> - This petition was filed on the grounds of threat to national security posed by the UID project particularly in relation to arrangements for data sharing with foreign companies (with links to foreign intelligence agencies).</li>
<li style="text-align: justify;">Nagrik Chetna Manch <a href="#ftn6">[6]</a> - This petition was filed in 2013 and led by Dr. Anupam Saraph on the grounds that the UID project was detrimental to financial service regulation and financial <em>inclusion.</em></li>
<li style="text-align: justify;">S. Raju <a href="#ftn7">[7] </a> - This petition was filed on the grounds that the UID project had implications on the federal structure of the State and was detrimental to financial inclusion.</li>
<li style="text-align: justify;"><em>Beghar Foundation</em> - This petition was filed in 2013 in the Delhi High Court on the grounds invasion of privacy and exclusion specifically in relation to the homeless. It subsequently joined the petition filed by Aruna Roy and Nikhil Dey as an intervener.</li>
<li style="text-align: justify;">Vickram Crishna – This petition was originally filed in the Bombay High Court in 2013 on the grounds of surveillance and invasion of privacy. It was later transferred to the Supreme Court.</li>
<li style="text-align: justify;">Somasekhar – This petition was filed on the grounds of procedural unreasonableness of the UID project and also exclusion & privacy. The petitioner later intervened in the petition filed by Aruna Roy and Nikhil Dey in 2013.</li>
<li style="text-align: justify;">Rajeev Chandrashekhar– This petition was filed on the ground of lack of legal sanction for the UID project. He later intervened in the petition filed by Aruna Roy and Nikhil Dey in 2013. His position has changed now.</li>
<li style="text-align: justify;">Further, a petition was filed by Mr. Jairam Ramesh initially challenging the passage of the Act as a money bill but subsequently, it has been amended to include issues of violation of right to privacy and exclusion of the poor and has advocated for five amendments that were suggested to the Aadhaar Bill by the Rajya Sabha.</li></ul>
<h3 id="23" style="text-align: justify;">Relevant Orders of the Supreme Court</h3>
<p>There are six orders of the Supreme Court which are noteworthy.</p>
<ul>
<li style="text-align: justify;">Order of Sept. 23, 2013 - The Supreme court directed that: 1) no person shall suffer for not having an aadhaar number despite the fact that a circular by an authority makes it mandatory; 2) it should be checked if a person applying for aadhaar number voluntarily is entitled to it under the law; and 3) precaution should be taken that it is not be issued to illegal immigrants.</li>
<li style="text-align: justify;">Order of 26th November, 2013 – Applications were filed by UIDAI, Ministry of Petroleum & Natural Gas, Govt of India, Indian Oil Corporation, BPCL and HPCL for modifying the September 23rd order and sought permission from the Supreme Court to make aadhaar number mandatory. The Supreme Court held that the order of September 23rd would continue to be effective.</li>
<li style="text-align: justify;">Order of 24th March, 2014 – This order was passed by the Supreme Court in a special leave petition filed in the case of <em>UIDAI v CBI</em> <a href="#ftn8">[8] </a> wherein UIDAI was asked to UIDAI to share biometric information of all residents of a particular place in Goa to facilitate a criminal investigation involving charges of rape and sexual assault. The Supreme Court restrained UIDAI from transferring any biometric information of an individual without to any other agency without his consent in writing. The Supreme Court also directed all the authorities to modify their forms/circulars/likes so as to not make aadhaar number mandatory.</li>
<li style="text-align: justify;">Order of 16th March, 2015 - The SC took notice of widespread violations of the order passed on September 23rd, 2013 and directed the Centre and the states to adhere to these orders to not make aadhaar compulsory.</li>
<li style="text-align: justify;">Orders of August 11, 2015 – In the first order, the Central Government was directed to publicise the fact that aadhaar was voluntary. The Supreme Court further held that provision of benefits due to a citizen of India would not be made conditional upon obtaining an aadhaar number and restricted the use of aadhaar to the PDS Scheme and in particular for the purpose of distribution of foodgrains, etc. and cooking fuel, such as kerosene and the LPG Distribution Scheme. The Supreme Court also held that information of an individual that was collected in order to issue an aadhaar number would not be used for any purpose except when directed by the Court for criminal investigations. Separately, the status of fundamental right to privacy was contested and accordingly the Supreme Court directed that the issue be taken up before the Chief Justice of India.</li>
<li style="text-align: justify;">Orders of October 16, 2015 – The Union of India, the states of Gujarat, Maharashtra, Himachal Pradesh and Rajasthan, and authorities including SEBI, TRAI, CBDT, IRDA , RBI applied for a hearing before the Constitution Bench for modification of the order passed by the Supreme Court on August 11 and allow use of aadhaar number schemes like The Mahatma Gandhi National Rural Employment Guarantee Scheme MGNREGS), National Social Assistance Programme (Old Age Pensions, Widow Pensions, Disability Pensions) Prime Minister's Jan Dhan Yojana (PMJDY) and Employees' Providend Fund Organisation (EPFO). The Bench allowed the use of aadhaar number for these schemes but stressed upon the need to keep aadhaar scheme voluntary until the matter was finally decided.</li></ul>
<p style="text-align: justify;">Status of these orders<br />The participants discussed the possible impact of the law on the operation of these orders. A participant pointed out that matters in the Supreme Court had not become infructuous because fundamental issues that were being heard in the Supreme Court had not been resolved by the passage of the Act. Several participants believed that the aforementioned orders were effective because the law had not come into force. Therefore, aadhaar number could only be used for purposes specified by the Supreme Court and it could not be made mandatory. Participants also highlighted that when the Act was implemented, it would not nullify the orders of the Supreme Court unless Union of India asked the Supreme Court for it specifically and the Supreme Court sanctioned that.</p>
<h3 id="3" style="text-align: justify;"><strong>3. National Identity Projects in Other Jurisdictions</strong></h3>
<p style="text-align: justify;">A panellist had provided a brief overview of similar programs on identification that have been launched in other jurisdictions including Pakistan, United Kingdom, France, Estonia and Argentina in the recent past in the session titled ‘Aadhaar - International Dimensions’. This presentation mainly sought to assess the incentives that drove the governments in these jurisdictions to formulate these projects, mandatory nature of their adoption and their popularity. The Report has reproduced the presentation here.</p>
<h3 id="31" style="text-align: justify;">Pakistan</h3>
<p style="text-align: justify;">The Second Amendment to the Constitution of Pakistan in 2000 established the National Database and Regulation Authority in the country, which regulates government databases and statistically manages the sensitive registration database of the citizens of Pakistan. It is also responsible for issuing national identity cards to the citizens of Pakistan. Although the card is not legally compulsory for a Pakistani citizen, it is mandatory for:</p>
<ul>
<li>Voting</li>
<li>Obtaining a passport</li>
<li>Purchasing vehicles and land</li>
<li>Obtaining a driver licence</li>
<li>Purchasing a plane or train ticket</li>
<li>Obtaining a mobile phone SIM card</li>
<li>Obtaining electricity, gas, and water</li>
<li>Securing admission to college and other post-graduate institutes</li>
<li>Conducting major financial transactions</li></ul>
<p style="text-align: justify;">Therefore, it is pretty much necessary for basic civic life in the country. In 2012, NADRA introduced the Smart National Identity Card, an electronic identity card, which implements 36 security features. The following information can be found on the card and subsequently the central database: Legal Name, Gender (male, female, or transgender), Father's name (Husband's name for married females), Identification Mark, Date of Birth, National Identity Card Number, Family Tree ID Number, Current Address, Permanent Address, Date of Issue, Date of Expiry, Signature, Photo, and Fingerprint (Thumbprint). NADRA also records the applicant's religion, but this is not noted on the card itself. (This system has not been removed yet and is still operational in Pakistan.)</p>
<h3 id="32" style="text-align: justify;">United Kingdom</h3>
<p style="text-align: justify;">The Identity Cards Act was introduced in the wake of the terrorist attacks on 11th September, 2001, amidst rising concerns about identity theft and the misuse of public services. The card was to be used to obtain social security services, but the ability to properly identify a person to their true identity was central to the proposal, with wider implications for prevention of crime and terrorism. The cards were linked to a central database (the National Identity Register), which would store information about all of the holders of the cards. The concerns raised by human rights lawyers, activists, security professionals and IT experts, as well as politicians were not to do with the cards as much as with the NIR. The Act specified 50 categories of information that the NIR could hold, including up to 10 fingerprints, digitised facial scan and iris scan, current and past UK and overseas places of residence of all residents of the UK throughout their lives. The central database was purported to be a prime target for cyber attacks, and was also said to be a violation of the right to privacy of UK citizens. The Act was passed by the Labour Government in 2006, and repealed by the Conservative-Liberal Democrat Coalition Government as part of their measures to “reverse the substantial erosion of civil liberties under the Labour Government and roll back state intrusion.”</p>
<h3 id="33" style="text-align: justify;">Estonia</h3>
<p style="text-align: justify;">The Estonian i-card is a smart card issued to Estonian citizens by the Police and Border Guard Board. All Estonian citizens and permanent residents are legally obliged to possess this card from the age of 15. The card stores data such as the user's full name, gender, national identification number, and cryptographic keys and public key certificates. The cryptographic signature in the card is legally equivalent to a manual signature, since 15 December 2000. The following are a few examples of what the card is used for:</p>
<ul>
<li>As a national ID card for legal travel within the EU for Estonian citizens</li>
<li>As the national health insurance card</li>
<li>As proof of identification when logging into bank accounts from a home computer</li>
<li>For digital signatures</li>
<li>For i-voting</li>
<li>For accessing government databases to check one’s medical records, file taxes, etc.</li>
<li>For picking up e-Prescriptions</li>
<li>(This system is also operational in the country and has not been removed)</li></ul>
<h3 id="34" style="text-align: justify;">France</h3>
<p style="text-align: justify;">The biometric ID card was to include a compulsory chip containing personal information, such as fingerprints, a photograph, home address, height, and eye colour. A second, optional chip was to be implemented for online authentication and electronic signatures, to be used for e-government services and e-commerce. The law was passed with the purpose of combating “identity fraud”. It was referred to the Constitutional Council by more than 200 members of the French Parliament, who challenged the compatibility of the bill with the citizens’ fundamental rights, including the right to privacy and the presumption of innocence. The Council struck down the law, citing the issue of proportionality. “Regarding the nature of the recorded data, the range of the treatment, the technical characteristics and conditions of the consultation, the provisions of article 5 touch the right to privacy in a way that cannot be considered as proportional to the meant purpose”.</p>
<h3 id="35" style="text-align: justify;">Argentina</h3>
<p style="text-align: justify;">Documento Nacional de Identidad or DNI (which means National Identity Document) is the main identity document for Argentine citizens, as well as temporary or permanent resident aliens. It is issued at a person's birth, and updated at 8 and 14 years of age simultaneously in one format: a card (DNI tarjeta); it's valid if identification is required, and is required for voting. The front side of the card states the name, sex, nationality, specimen issue, date of birth, date of issue, date of expiry, and transaction number along with the DNI number and portrait and signature of the card's bearer. The back side of the card shows the address of the card's bearer along with their right thumb fingerprint. The front side of the DNI also shows a barcode while the back shows machine-readable information. The DNI is a valid travel document for entering Argentina, Bolivia, Brazil, Chile, Colombia, Ecuador, Paraguay, Peru, Uruguay, and Venezuela. (System still operational in the country)</p>
<h3 id="4" style="text-align: justify;"><strong>4. Technologies of Identification and Authentication</strong></h3>
<p style="text-align: justify;">The panel in the session titled ‘Aadhaar: Science, Technology, and Security’ explained the technical aspects of use of biometrics and privacy concerns, technology architecture for identification and inadequacy of infrastructure for information security. In this section, we have summarised the presentation and the ensuing discussions on these issues.</p>
<h3 id="41" style="text-align: justify;">Use of Biometric Information for Identification and Authentication</h3>
<p style="text-align: justify;">The panelists explained with examples that identification and authentication were different things. Identity provides an answer to the question “who are you?” while authentication is a challenge-response process that provides a proof of the claim of identity. Common examples of identity are User ID (Login ID), cryptographic public keys and ATM or Smart cards while common authenticators are passwords (including OTPs), PINs and cryptographic private keys. Identity is public information but an authenticator must be private and known only to the user. Authentication must necessarily be a conscious process and active participation by the user is a must. It should also always be possible to revoke an authenticator. After providing this understanding of the two processes the panellist then explained if biometric information could be used for identification or authentication under the UID Project. Biometric information is clearly public information and it is questionable if it can be revoked. Therefore it should never be used for authentication, but only for identity verification. There is a possibility of authentication by fingerprints under the UID Project, without conscious participation of the user. One could trace the fingerprints of an individual from any place the individual has been in contact with. Therefore, authentication must certainly be done by other means. The panellist pointed out that there were five kinds of authentication under the UID Project, out of which two-factor authentication and one time password were considered suitable but use of biometric information and demographic information was extremely threatening and must be withdrawn.</p>
<h3 id="42" style="text-align: justify;">Architectures of Identification</h3>
<p style="text-align: justify;">The panelists explained the architecture of the UID Project that has been designed for identification purposes, highlighted its limitations and suggested alternatives. His explanations are reproduced below.</p>
<p style="text-align: justify;">Under the UID Project, there is a centralised means of identification i.e. the aadhaar number and biometric information stored in one place, Central Identification Data Repository (CIDR). It is better to have multiple means of identification than one (as contemplated under the UID Project) for preservation of our civil liberties. The question is what the available alternatives are. Web of trust is a way for operationalizing distributed identification but the challenge is how one brings people from all social levels to participate in it. There is a need for registrars who will sign keys and public databases for this purpose.</p>
<p style="text-align: justify;">The aadhaar number functions as a common index and facilitates correlation of data across Government databases. While this is tremendously attractive it raises several privacy concerns as more and more information relating to an individual is available to others and is likely to be abused.</p>
<p style="text-align: justify;">The aadhaar number is available in human readable form. This raises the risk of identification without consent and unauthorised profiling. It cannot be revoked. Potential for damage in case of identity theft increases manifold.</p>
<p style="text-align: justify;">Under the UID Project, for the purpose of information security, Authentication User Agencies (“<strong>AUA</strong>”) are required to use local identifiers instead of aadhaar numbers but they are also required to map these local identifiers to the aadhaar numbers. Aadhaar numbers are not cryptographically secured; in fact they are publicly available. Hence this exercise for securing information is useless. An alternative would be to issue different identifiers for different domains and cryptographically embed a “master identifier” (in this case, equivalent of aadhaar number) into each local identifier.</p>
<p style="text-align: justify;">All field devices (for example POS machines) should be registered and must communicate directly with UIDAI. In fact, UIDAI must verify the authenticity (tamper proof) of the field device during run time and a UIDAI approved authenticity certificate must be issued for field devices. This certificate must be made available to users on demand. Further, the security and privacy frameworks within which AUAs work must be appropriately defined by legal and technical means.</p>
<h3 id="43" style="text-align: justify;">Security Infrastructure of CIDR</h3>
<p style="text-align: justify;">The panelists also enumerated the security features of the UID Project and highlighted the flaws in these features. These have been summarised below.</p>
<p>The security and privacy infrastructure of UIDAI has the following main features:</p>
<ul>
<li>2048 bit PKI encryption of biometric data in transit</li>
<li>End-to-end encryption from enrolment/POS to CIDR</li>
<li>HMAC based tamper detection of PID blocks</li>
<li>Registration and authentication of AUAs</li>
<li>Within CIDR only a SHA 1 Hash of Aadhaar number is stored</li>
<li>Audit trails are stored SHA 1 encrypted. Tamper detection?</li>
<li>Only hashes of passwords and PINs are stored. (biometric data stored in original form though!)</li>
<li>Authentication requests have unique session keys and HMAC</li>
<li>Resident data stored using 100 way sharding (vertical partitioning). First two digits of Aadhaar number as shard keys</li>
<li>All enrolment and update requests link to partitioned databases using Ref IDs (coded indices)</li>
<li>All accesses through a hardware security module</li>
<li>All analytics carried out on anonymised data</li></ul>
<p style="text-align: justify;">The panellists pointed out the concerns about information security on account of design flaws, lack of procedural safeguards, openness of the system and too much trust imposed on multiple players. All symmetric and private keys and hashes are stored somewhere within UIDAI. This indicates that trust is implicitly assumed which is a glaring design flaw. There is no well-defined approval procedure for data inspection, whether it is for the purpose of investigation or for data analytics. There is a likelihood of system hacks, insider leaks, and tampering of authentication records and audit trails. The ensuing discussions highlighted that the UIDAI had admitted to these security risks. The enrolment agencies and the enrolment devices cannot be trusted. AUAs cannot be trusted with biometric and demographic data; neither can they be trusted with sensitive user data of private nature. There is a need for an independent third party auditor for distributed key management, auditing and approving UIDAI programs, including those for data inspection and analytics, whitebox cryptographic compilation of critical parts of the UIDAI programs, issue of cryptographic keys to UIDAI programs for functional encryption, challenge-response for run-time authentication and certification of UIDAI programs. The panellist recommended that there was a need to to put a suitable legal framework to execute this.</p>
<p style="text-align: justify;">The participants also discussed that information infrastructure must not be made of proprietary software (possibility for backdoors for US) and there must be a third party audit with a non-negotiable clause for public audit.</p>
<h3 id="5" style="text-align: justify;"><strong>5. Aadhaar for Welfare?</strong></h3>
<p style="text-align: justify;">The Report has summarised the discussions that took place in the sessions on ‘Direct Benefits Transfers’ and ‘Aadhaar: Broad Issues - II’ where the panellists critically analysed the claims of benefits and inclusion of Aadhaar made by the government in light of the ground realities in states where Aadhaar has been adopted for social welfare schemes.</p>
<h3 id="51" style="text-align: justify;">Social Welfare: Modes of Access and Exclusion</h3>
<p style="text-align: justify;">Under the Act, a person may be required to authenticate or give proof of the aadhaar number in order to receive subsidy from the government (Section 7). A person is required to punch their fingerprints on POS machines in order to receive their entitlement under the social welfare schemes such as LPG and PDS. It was pointed out in the discussions that various states including Rajasthan and Delhi had witnessed fingerprint errors while doling out benefits at ration shops under the PDS scheme. People have failed to receive their entitled benefits because of these fingerprint errors thus resulting in exclusion of beneficiaries <a href="#ftn9">[9]</a>. A panellist pointed out that in Rajasthan, dysfunctional biometrics had led to further corruption in ration shops. Ration shop owners often lied to the beneficiaries about functioning of the biometric machines (POS Machines) and kept the ration for sale in the market therefore making a lot of money at the expense of uninformed beneficiaries and depriving them of their entitlements.</p>
<p style="text-align: justify;">Another participant organisation also pointed out similar circumstances in the ration shops in Patparganj and New Delhi constituencies. Here, the dealers had maintained the records of beneficiaries who had been categorized as follows: beneficiaries whose biometrics did not match, beneficiaries whose biometrics matched and entitlements were provided, beneficiaries who never visited the ration shop. It had been observed that there were no entries in the category of beneficiaries whose biometrics did not match however, the beneficiaries had a different story to tell. They complained that their biometrics did not match despite trying several times and there was no mechanism for a manual override. Consequently, they had not been able to receive any entitlements for months. The discussions also pointed out that the food authorities had placed complete reliance on authenticity of the POS machines and claim that this system would weed out families who were not entitled to the benefits. The MIS was also running technical glitches as a result there was a problem with registering information about these transactions hence, no records had been created with the State authority about these problems. A participant also discussed the plight of 30,000 widows in Delhi, who were entitled to pension and used to collect their entitlement from post offices, faced exclusion due to transition problems under the Jan Dhan Yojana (after the Jandhan was launched the money was transferred to their bank accounts in order to resolve the problem of misappropriation of money at the hands of post office officials). These widows were asked to open bank accounts to receive their entitlements and those who did not open these accounts and did not inform the post office were considered bogus.</p>
<p style="text-align: justify;">In the discussions, the participants also noted that this unreliability of fingerprints as a means of authentication of an individual’s identity was highlighted at the meeting of Empowered Group of Ministers in 2011 by J Dsouza, a biometrics scientist. He used his wife’s fingerprints to demonstrate that fingerprints may change overtime and in such an event, one would not be able to use the POS machine anymore as the machine would continue to identify the impressions collected initially.</p>
<p style="text-align: justify;">The participants who had been working in the field had contributed to the discussions by busting the myth that the UID Project helped to identify who was poor and resolve the problem of exclusion due to leakages in the social welfare programs. These discussions have been summarised below.</p>
<ul>
<li style="text-align: justify;">It is important to understand that the UID Project is merely an identification and authentication system. It only helps in verifying if an individual is entitled to benefits under a social security scheme. It does not ensure plugging of leakages and reducing corruption in social security schemes as has been claimed by the Government. The reduction in leakage of PDS, for instance, should be attributed to digitization and not UID. The Government claims, that it has saved INR 15000 crore in provision of LPG on identification of 3.34 crore inactive accounts on account of the UID Project. This is untrue because the accounts were weeded by using mechanisms completely unrelated to the UID Project. Consequently, the savings on account of UID are only of INR 120 crore and not 15000 crore.</li>
<li style="text-align: justify;">The UID Project has resulted in exclusion of people either because they do not have an aadhaar number, or they have a wrong identification, or there are errors of classification or wilful misclassification. About 99.7% people who were given aadhaar numbers already had an identification document. In fact, during enrolment a person is required to produce one of 14 identification documents listed under the law in order to get an aadhaar number which makes it very difficult for a person with no identity to become entitled to a social welfare scheme.</li></ul>
<p style="text-align: justify;">A participant condemned the Government’s claim that the UID Project had helped in removing fake, bogus and duplicate cards and said that these terms could not be used synonymously and the authorities had no clarity about the difference between the meanings of these terms. The UID Project had only helped in removal of duplicate cards but had not helped in combating the use of fake and bogus cards.</p>
<h3 id="52" style="text-align: justify;">Financial Inclusion and Direct Benefits Transfer</h3>
<p style="text-align: justify;">The participants also engaged in the discussions about the impact of the UID project on financial inclusion in India in the sessions titled ‘Aadhaar: Broad Issues - I & II’. We have summarised these discussions below.</p>
<p style="text-align: justify;">The UID Project seeks to directly transfer money to a bank account in order to combat corruption. The discussions highlighted that this was nothing but introducing a neo liberal thrust in social policy and that it was not feasible for various reasons. First, 95% of rural India did not have functioning banks and banks are quite far away. Second, in order to combat this dearth of banks the idea of business correspondents, who handled banking transactions and helped in opening of bank accounts, had been introduced which had created various problems. The Reserve Bank of India reported that there was dearth of business correspondents as there was very little incentive to become one; their salary is merely INR 4000. Third, there were concerns about how an aadhaar number was considered a valid document for Know Your Customer (KYC) checks. There was a requirement for scrutiny and auditing of documents submitted during the time of enrolment which, in the present scheme of things, could not be verified. Fourth, there were no restrictions on number of bank accounts that could be opened with a single aadhaar number which gave rise to a possibility of opening multiple and shell accounts on a single aadhaar number. Therefore, records only showed transactions when money was transferred from an aadhaar number to another aadhaar number as opposed to an account-to-account transfer. The discussion relied on NPCI data which shows which bank an aadhaar number is associated with but does not show if a transaction by an aadhaar number is overwritten by another bank account belonging to the same aadhaar number.</p>
<h3 id="6" style="text-align: justify;"><strong>6. Surveillance and UIDAI</strong></h3>
<p style="text-align: justify;">The participants had discussed the possibility of an alternative purpose for enrolling Aadhaar in the session titled ‘Privacy, Surveillance, and Ethical Dimensions of Aadhaar’. The discussion traced the history of this project to gain insight on this issue. We have summarised below the key take aways from this discussion.</p>
<p style="text-align: justify;">There are claims that the main objective of launching the UID Project is not to facilitate implementation of social security schemes but to collect personal (financial and non-financial) information of the citizens and residents of the country to build a data monopoly. For this purpose, PDS was chosen as a suitable social security scheme as it has the largest coverage. Several participants suggested that numerous reports authored by FICCI, KPMG and ASSOCHAM contained proposals for establishing a national identity authority which threw some light on the commercial intentions behind information collection under the UID Project.</p>
<p style="text-align: justify;">It was also pointed out that there was documented proof that information collected under the UID Project might have been shared with foreign companies. There are suggestions about links established between proponents of the UID Project and companies backed by CIA or the French Government which run security projects and deal in data sharing in several jurisdictions.</p>
<h3 id="7" style="text-align: justify;"><strong>7. Strategies for Future Action</strong></h3>
<p>The participants laid down a list of measures that must be taken to take the discussions forward. We have enumerated these recommendations below.</p>
<ul>
<li>Prepare and compile an anthology of articles as an output of this workshop. </li>
<li>Prepare position papers on specific issues related to the UID Project </li>
<li>Prepare pamphlets/brochures on issues with the UID Project for public consumption </li>
<li>Prepare counter-advertisements for Aadhaar</li>
<li>Publish existing empirical evidence on the flaws in Aadhaar.</li>
<li>Set up an online portal dedicated to providing updates on the UID Project and allows discussions on specific issues related to Aadhaar.</li>
<li>Use Social Media to reach out to the public. Regularly track and comment on social media pages of relevant departments of the government.</li>
<li>Create groups dedicated to research and advocacy of specific aspects of the UID Project. </li>
<li>Create a Coordination Committee preferably based in Delhi which would be responsible for regularly holding meetings and for preparing a coordinated plan of action. Employ permanent to staff to run the Committee.</li>
<li>Organise an advocacy campaign against use of Aadhaar in collaboration with other organisations and build public domain acceptance. </li>
<li>The campaign must specifically focus on the unfettered scope of UID and expanse, misrepresentation of the success of Aadhaar by highlighting real savings, technological flaws, status of pilot programs and increasing corruption on account of the UID Project</li>
<li>Prepare a statement of public concern regarding the UID Project and collect signatures from eminent persons including academics, technical experts, civil society groups and members of parliament.</li>
<li>Organise events and discussions on issues relating to Aadhaar and invite members og government departments to speak and discuss the issues. </li>
<li style="text-align: justify;">Write to Members of Parliament and Members of Legislative Assemblies raising questions on their or their parties’ support for Aadhaar and silence on the problems created by the UID Project. </li>
<li style="text-align: justify;">Organise public hearings in states like Rajasthan to observe and document ground realities of the UID Project and share these outcomes with the state government and media. </li>
<li>Plan a national social audit and public hearing on the working of UID Project in the country. </li>
<li style="text-align: justify;">File Contempt Petitions in the Supreme Court and High Courts against mandatory use of Aadhaar number for services not allowed by the Supreme Court. </li>
<li style="text-align: justify;">Reach out to and engage with various foreign citizens and organisations that have been fighting on similar issues. The organisations and individuals who could be approached would include EPIC, Electronic Frontier foundation, David Moss, UK, Roger Clarke, Australia, Prof. Ian Angel, Snowden, Assange and Chomsky.</li>
<li style="text-align: justify;">Work towards increasing awareness about the UID Project and gaining support from the student and research community, student organisations, trade unions, and other associations and networks in the unorganised sector.</li></ul>
<h3 id="AA" style="text-align: justify;"><strong>Annexure A – Workshop Agenda</strong></h3>
<h4>May 26, 2016</h4>
<table>
<tbody>
<tr>
<td>
<p>9:00-9:30</p>
</td>
<td>
<p><strong>Registration</strong></p>
</td>
</tr>
<tr>
<td>
<p>9:30-10:00</p>
</td>
<td>
<p>Prof. Dinesh Abrol - <em>Welcome</em><br />
<em>Self-introduction and expectations of participants</em><br />
Dr. Usha Ramanathan - <em>Overview of the Workshop</em></p>
</td>
</tr>
<tr>
<td>
<p>10:00-11:00</p>
</td>
<td>
<p><strong>Session 1: Current Status of Aadhaar</strong><br />
Dr. Usha Ramanathan, Legal Researcher, New Delhi - <em>What the 2016 Law Says, and How it Came into Being</em><br />
S. Prasanna, Advocate, New Delhi - <em>Status and Force of Supreme Court Orders on Aadhaar</em><br /> <em>Discussion</em></p>
</td>
</tr>
<tr>
<td>
<p>11:00-11:30</p>
</td>
<td>
<p><strong>Tea Break</strong></p>
</td>
</tr>
<tr>
<td>
<p>11:30-13:30</p>
</td>
<td>
<p><strong>Session 2: Direct Benefits Transfers</strong><br />
Prof. Reetika Khera, Indian Institute of Technology, Delhi - <em>Welfare Needs Aadhaar like a Fish Needs a Bicycle</em><br />
Prof. R. Ramakumar, Tata Institute of Social Sciences, Mumbai - <em>Aadhaar and the Social Sector: A critical analysis of the claims of benefits and inclusion</em><br />
Ashok Rao, Delhi Science Forum - <em>Cash Transfers Study</em><br />
<em>Discussion</em></p>
</td>
</tr>
<tr>
<td>
<p>13:30-14:30</p>
</td>
<td>
<p><strong>Lunch</strong></p>
</td>
</tr>
<tr>
<td>
<p>14:30-16:00</p>
</td>
<td>
<p><strong>Session 3: Aadhaar: Science, Technology, and Security</strong><br />
Prof. Subashis Banerjee, Dept of Computer Science & Engineering, IIT, Delhi - <em>Privacy and Security Issues Related to the Aadhaar Act</em><br />
Pukhraj Singh, Former National Cyber Security Manager, Aadhaar, New Delhi - <em>Aadhaar: Security and Surveillance Dimensions</em><br />
<em>Discussion</em></p>
</td>
</tr>
<tr>
<td>
<p>16:00-16:30</p>
</td>
<td>
<p><strong>Tea Break</strong></p>
</td>
</tr>
<tr>
<td>
<p>16:30-17:30</p>
</td>
<td>
<p><strong>Session 4: Aadhaar - International Dimensions</strong><br />
Joshita Pai, Center for Communication Governance, National Law University, Delhi - <em>Biometrics and Mandatory IDs in Other Parts of the World</em><br />
Dr. Gopal Krishna, Citizens Forum for Civil Liberties - <em>International Dimensions of Aadhaar</em><br />
<em>Discussion</em></p>
</td>
</tr>
<tr>
<td>
<p>17:30-18:00</p>
</td>
<td>
<p><strong>High Tea</strong></p>
</td>
</tr>
</tbody>
</table>
<h4>May 27, 2016</h4>
<table>
<tbody>
<tr>
<td>
<p>9:30-11:00</p>
</td>
<td>
<p><strong>Session 5: Privacy, Surveillance and Ethical Dimensions of Aadhaar</strong><br />
Prabir Purkayastha, Free Software Movement of India, New Delhi - <em>Surveillance Capitalism and the Commodification of Personal Data</em><br />
Arjun Jayakumar, SFLC - <em>Surveillance Projects Amalgamated</em><br />
Col Mathew Thomas, Bengaluru - <em>The Deceit of Aadhaar<em></em><br />
<em>Discussion</em></em></p>
<em>
</em></td>
</tr>
<tr>
<td>
<p>11:00-11:30</p>
</td>
<td>
<p><strong>Tea Break</strong></p>
</td>
</tr>
<tr>
<td>
<p><em>11:30-13:00</em></p>
</td>
<td>
<p><strong>Session 6: Aadhaar - Broad Issues I</strong><br />
Prof. G Nagarjuna, Homi Bhabha Center for Science Education, Tata Institute of Fundamental Research, Mumbai - <em>How to prevent linked data in the context of Aadhaar</em><br />
Dr. Anupam Saraph, Pune - <em>Aadhaar and Moneylaundering</em><br />
<em>Discussion</em></p>
</td>
</tr>
<tr>
<td>
<p>13:00-14:00</p>
</td>
<td>
<p><strong>Lunch</strong></p>
</td>
</tr>
<tr>
<td>
<p>14:00-15:30</p>
</td>
<td>
<p><strong>Session 7: Aadhaar - Broad Issues II</strong><br />
Prof. MS Sriram, Visiting Faculty, Indian Institute of Management, Bangalore - <em>Financial lnclusion</em><br />
Nikhil Dey, MKSS, Rajasthan - <em>Field witness: Technology on the Ground</em><br />
Prof. Himanshu, Centre for Economic Studies & Planning, JNU - <em>UID Process and Financial Inclusion</em><br />
<em>Discussion</em></p>
</td>
</tr>
<tr>
<td>
<p>15:30-16:00</p>
</td>
<td>
<p><strong>Session 8: Conclusion</strong></p>
</td>
</tr>
<tr>
<td>
<p>16:00-18:00</p>
</td>
<td>
<p><strong>Informal Meetings</strong></p>
</td>
</tr>
</tbody>
</table>
<h3 id="AB" style="text-align: justify;"><strong>Annexure B – Workshop Participants</strong></h3>
<p>Anjali Bhardwaj, Satark Nagrik Sangathan</p>
<p>Dr. Anupam Saraph</p>
<p>Arjun Jayakumar, Software Freedom Law Centre</p>
<p>Ashok Rao, Delhi Science Forum</p>
<p>Prof. Chinmayi Arun, National Law University, Delhi</p>
<p>Prof. Dinesh Abrol, Jawaharlal Nehru University</p>
<p>Prof. G Nagarjuna, Homi Bhabha Center for Science Education, Tata Institute of Fundamental Research, Mumbai</p>
<p>Dr. Gopal Krishna, Citizens Forum for Civil Liberties</p>
<p>Prof. Himanshu, Jawaharlal Nehru University</p>
<p>Japreet Grewal, the Centre for Internet and Society</p>
<p>Joshita Pai, National Law University, Delhi</p>
<p>Malini Chakravarty, Centre for Budget and Governance Accountability</p>
<p>Col. Mathew Thomas</p>
<p>Prof. MS Sriram, Indian Institute of Management, Bangalore</p>
<p>Nikhil Dey, Mazdoor Kisan Shakti Sangathan</p>
<p>Prabir Purkayastha, Knowledge Commons and Free Software Movement of India</p>
<p>Pukhraj Singh, Bhujang</p>
<p>Rajiv Mishra, Jawaharlal Nehru University</p>
<p>Prof. R Ramakumar, Tata Institute of Social Sciences, Mumbai</p>
<p>Dr. Reetika Khera, Indian Institute of Technology, Delhi</p>
<p>Dr. Ritajyoti Bandyopadhyay, Indian Institute of Science Education and Research, Mohali</p>
<p>S. Prasanna, Advocate</p>
<p>Sanjay Kumar, Science Journalist</p>
<p>Sharath, Software Freedom Law Centre</p>
<p>Shivangi Narayan, Jawaharlal Nehru University</p>
<p>Prof. Subhashis Banerjee, Indian Institute of Technology, Delhi</p>
<p>Sumandro Chattapadhyay, the Centre for Internet and Society</p>
<p>Dr. Usha Ramanathan, Legal Researcher</p>
<p><em>Note: This list is only indicative, and not exhaustive.</em></p>
<hr />
<p><a name="ftn1"><strong>[1]</strong></a> Civil Appeal No. 4853 of 2014</p>
<p><a name="ftn2"><strong>[2]</strong></a> WP(C) 494/2012</p>
<p><a name="ftn3"><strong>[3]</strong> </a>. WP(C) 829/2013</p>
<p><a name="ftn4"><strong>[4]</strong></a> WP(C) 833/2013</p>
<p><a name="ftn5"><strong>[5]</strong></a> WP (C) 37/2015; (Earlier intervened in the Aruna Roy petition in 2013)</p>
<p><a name="ftn6"><strong>[6]</strong></a> WP (C) 932/2015</p>
<p><a name="ftn7"><strong>[7]</strong></a> Transferred from Madras HC 2013.</p>
<p style="text-align: justify;"><a name="ftn8"><strong>[8]</strong></a> SLP (Crl) 2524/2014 filed against the order of the Goa Bench of the Bombay HC in CRLWP 10/2014 wherein the High Court had directed UIDAI to share biometric information held by them of all residents of a particular place in Goa to help with a criminal investigation in a case involving charges of rape and sexual assault.</p>
<p><a name="ftn9"><strong>[9]</strong></a> See :http://scroll.in/article/806243/rajasthan-presses-on-with-aadhaar-after-fingerprint-readers-fail-well-buy-iris-scanners</p>
<p> </p>
<p>
For more details visit <a href='http://editors.cis-india.org/internet-governance/blog/report-on-understanding-aadhaar-and-its-new-challenges'>http://editors.cis-india.org/internet-governance/blog/report-on-understanding-aadhaar-and-its-new-challenges</a>
</p>
No publisherJapreet Grewal, Vanya Rakesh, Sumandro Chattapadhyay, and Elonnai HickockBig DataData SystemsPrivacyResearchers at WorkInternet GovernanceAadhaarWelfare GovernanceBiometricsBig Data for DevelopmentUID2019-03-16T04:42:52ZBlog EntryBig Data and Reproductive Health in India: A Case Study of the Mother and Child Tracking System
http://editors.cis-india.org/raw/big-data-reproductive-health-india-mcts
<b>In this case study undertaken as part of the Big Data for Development (BD4D) network, Ambika Tandon evaluates the Mother and Child Tracking System (MCTS) as data-driven initiative in reproductive health at the national level in India. The study also assesses the potential of MCTS to contribute towards the big data landscape on reproductive health in the country, as the Indian state’s imagination of health informatics moves towards big data.</b>
<p> </p>
<h4>Case study: <a href="https://github.com/cis-india/website/raw/master/bd4d/CIS_CaseStudy_AT_BigDataReproductiveHealthMCTS.pdf" target="_blank">Download</a> (PDF)</h4>
<hr />
<h3>Introduction</h3>
<p>The reproductive health information ecosystem in India comprises of a range of different databases across state and national levels. These collect data through a combination of manual and digital tools. Two national-level databases have been launched by the Ministry of Health and Family Welfare - the Health Management Information System (HMIS) in 2008, and the MCTS in 2009. 4 The MCTS focuses on collecting data on maternal and child health. It was instituted due to reported gaps in the HMIS, which records monthly data across health programmes including reproductive health. There are several other state-level initiatives on reproductive health data that have either been subsumed into, or run in
parallel with, the MCTS.</p>
<p>With this case study, we aim to evaluate the MCTS as data-driven initiative in reproductive health at the national level. It will also assess its potential to contribute towards the big data landscape on reproductive health in the country, as the Indian state’s imagination of health informatics moves towards big data. The methodology for the case study involved a desk-based review of existing literature on the use of health information systems globally, as well as analysis of government reports, journal articles, media coverage, policy documents, and other material on the MCTS.</p>
<p>The first section of this report details the theoretical framing of the case study, drawing on the feminist critique of reproductive data systems. The second section maps the current landscape of reproductive health data produced by the state in India, with a focus on data flows, and barriers to data collection and analysis at the local and national level. The case of abortion data is used to further the argument of flawed data collection systems at the
national level. Section three briefly discusses the state’s imagination of reproductive health policy and the role of data systems through a discussion on the National Health Policy, 2017 and the National Health Stack, 2018. Finally, we make some policy recommendations and identify directions for future research, taking into account the ongoing shift towards big data globally to democratise reproductive healthcare.</p>
<p> </p>
<p>
For more details visit <a href='http://editors.cis-india.org/raw/big-data-reproductive-health-india-mcts'>http://editors.cis-india.org/raw/big-data-reproductive-health-india-mcts</a>
</p>
No publisherambikaBig DataData SystemsResearchers at WorkReproductive and Child HealthResearchFeaturedPublicationsBD4DHealthcareBig Data for Development2019-12-06T04:57:55ZBlog EntryThe Mother and Child Tracking System - understanding data trail in the Indian healthcare systems
http://editors.cis-india.org/internet-governance/blog/privacy-international-ambika-tandon-october-17-2019-mother-and-child-tracking-system-understanding-data-trail-indian-healthcare
<b>Reproductive health programmes in India have been digitising extensive data about pregnant women for over a decade, as part of multiple health information systems. These can be seen as precursors to current conceptions of big data systems within health informatics. In this article, published by Privacy International, Ambika Tandon presents some findings from a recently concluded case study of the MCTS as an example of public data-driven initiatives in reproductive health in India. </b>
<p> </p>
<h4>This article was first published by <a href="https://privacyinternational.org/news-analysis/3262/mother-and-child-tracking-system-understanding-data-trail-indian-healthcare" target="_blank">Privacy International</a>, on October 17, 2019</h4>
<h4>Case study of MCTS: <a href="https://cis-india.org/raw/big-data-reproductive-health-india-mcts" target="_blank">Read</a></h4>
<hr />
<p>On October 17th 2019, the UN Special Rapporteur (UNSR) on Extreme Poverty and Human Rights, Philip Alston, released his thematic report on digital technology, social protection and human rights. Understanding the impact of technology on the provision of social protection – and, by extent, its impact on people in vulnerable situations – has been part of the work the Centre for Internet and Society (CIS) and Privacy International (PI) have been doing.</p>
<p>Earlier this year, <a href="https://privacyinternational.org/advocacy/2996/privacy-internationals-submission-digital-technology-social-protection-and-human" target="_blank">PI responded</a> to the UNSR's consultation on this topic. We highlighted what we perceived as some of the most pressing issues we had observed around the world when it comes to the use of technology for the delivery of social protection and its impact on the right to privacy and dignity of benefit claimants.</p>
<p>Among them, automation and the increasing reliance on AI is a topic of particular concern - countries including Australia, India, the UK and the US have already started to adopt these technologies in digital welfare programmes. This adoption raises significant concerns about a quickly approaching future, in which computers decide whether or not we get access to the services that allow us to survive. There's an even more pressing problem. More than a few stories have emerged revealing the extent of the bias in many AI systems, biases that create serious issues for people in vulnerable situations, who are already exposed to discrimination, and made worse by increasing reliance on automation.</p>
<p>Beyond the issue of AI, we think it is important to look at welfare and automation with a wider lens. In order for an AI to function it needs to be trained on a dataset, so that it can understand what it is looking for. That requires the collection large quantities of data. That data would then be used to train and AI to recognise what fraudulent use of public benefits would look like. That means we need to think about every data point being collected as one that, in the long run, will likely be used for automation purposes.</p>
<p>These systems incentivise the mass collection of people's data, across a huge range of government services, from welfare to health - where women and gender-diverse people are uniquely impacted. CIS have been looking specifically at reproductive health programmes in India, work which offers a unique insight into the ways in which mass data collection in systems like these can enable abuse.</p>
<p>Reproductive health programmes in India have been digitising extensive data about pregnant women for over a decade, as part of multiple health information systems. These can be seen as precursors to current conceptions of big data systems within health informatics. India’s health programme instituted such an information system in 2009, the Mother and Child Tracking System (MCTS), which is aimed at collecting data on maternal and child health. The Centre for Internet and Society, India, <a href="https://cis-india.org/raw/big-data-reproductive-health-india-mcts" target="_blank">undertook a case study of the MCTS</a> as an example of public data-driven initiatives in reproductive health. The case study was supported by the <a href="http://bd4d.net/" target="_blank">Big Data for Development network</a> supported by the International Development Research Centre, Canada. The objective of the case study was to focus on the data flows and architecture of the system, and identify areas of concern as newer systems of health informatics are introduced on top of existing ones. The case study is also relevant from the perspective of Sustainable Development Goals, which aim to rectify the tendency of global development initiatives to ignore national HIS and create purpose-specific monitoring systems.</p>
<p>After being launched in 2011, 120 million (12 crore) pregnant women and 111 million (11 crore) children have been registered on the MCTS as of 2018. The central database collects data on each visit of the woman from conception to 42 days postpartum, including details of direct benefit transfer of maternity benefit schemes. While data-driven monitoring is a critical exercise to improve health care provision, publicly available documents on the MCTS reflect the complete absence of robust data protection measures. The risk associated with data leaks are amplified due to the stigma associated with abortion, especially for unmarried women or survivors of rape.</p>
<p>The historical landscape of reproductive healthcare provision and family planning in India has been dominated by a target-based approach. Geared at population control, this approach sought to maximise family planning targets without protecting decisional autonomy and bodily privacy for women. At the policy level, this approach was shifted in favour of a rights-based approach to family planning in 1994. However, targets continue to be set for women’s sterilisation on the ground. Surveillance practices in reproductive healthcare are then used to monitor under-performing regions and meet sterilisation targets for women, this continues to be the primary mode of contraception offered by public family planning initiatives.</p>
<p>More recently, this database - among others collecting data about reproductive health - is adding biometric information through linkage with the Aadhaar infrastructure. This data adds to the sensitive information being collected and stored without adhering to any publicly available data protection practices. Biometric linkage is aimed to fulfill multiple functions - primarily authentication of welfare beneficiaries of the national maternal benefits scheme. Making Aadhaar details mandatory could directly contribute to the denial of service to legitimate patients and beneficiaries - as has already been seen in some cases.</p>
<p>The added layer of biometric surveillance also has the potential to enable other forms of abuse of privacy for pregnant women. In 2016, the union minister for Women and Child Development under the previous government suggested the use of strict biometric-based monitoring to discourage gender-biased sex selection. Activists critiqued the policy for its paternalistic approach to reduce the rampant practice of gender-biased sex selection, rather than addressing the root causes of gender inequality in the country.</p>
<p>There is an urgent need to rethink the objectives and practices of data collection in public reproductive health provision in India. Rather than continued focus on meeting high-level targets, monitoring systems should enable local usage and protect the decisional autonomy of patients. In addition, the data protection legislation in India - expected to be tabled in the next session in parliament - should place free and informed consent, and informational privacy at the centre of data-driven practices in reproductive health provision.</p>
<p>This is why the systematic mass collection of data in health services is all the more worrying. When the collection of our data becomes a condition for accessing health services, it is not only a threat to our right to health that should not be conditional on data sharing but also it raises questions as to how this data will be used in the age of automation.</p>
<p>This is why understanding what data is collected and how it is collected in the context of health and social protection programmes is so important.</p>
<p> </p>
<p>
For more details visit <a href='http://editors.cis-india.org/internet-governance/blog/privacy-international-ambika-tandon-october-17-2019-mother-and-child-tracking-system-understanding-data-trail-indian-healthcare'>http://editors.cis-india.org/internet-governance/blog/privacy-international-ambika-tandon-october-17-2019-mother-and-child-tracking-system-understanding-data-trail-indian-healthcare</a>
</p>
No publisherambikaBig DataData SystemsPrivacyResearchers at WorkInternet GovernanceResearchBD4DHealthcareBig Data for Development2019-12-30T17:18:05ZBlog EntryYou auto-complete me: romancing the bot
http://editors.cis-india.org/raw/maya-indira-ganesh-you-auto-complete-me-romancing-the-bot
<b>This is an excerpt from an essay by Maya Indira Ganesh, written for and published as part of the Bodies of Evidence collection of Deep Dives. The Bodies of Evidence collection, edited by Bishakha Datta and Richa Kaul Padte, is a collaboration between Point of View and the Centre for Internet and Society, undertaken as part of the Big Data for Development Network supported by International Development Research Centre, Canada. </b>
<p> </p>
<h4>Please read the full essay on Deep Dives: <a href="https://deepdives.in/you-auto-complete-me-romancing-the-bot-f2f16613fec8" target="_blank">You auto-complete me: romancing the bot</a></h4>
<h4>Maya Indira Ganesh: <a href="https://bodyofwork.in/" target="_blank">Website</a> and <a href="https://twitter.com/mayameme" target="_blank">Twitter</a></h4>
<hr />
<p>I feel like Kismet the Robot.</p>
<p>Kismet is a flappy-eared animatronic head with oversized eyeballs and bushy eyebrows. Connected to cameras and sensors, it exhibits the six primary human emotions identified by psychologist Paul Ekman: happiness, sadness, disgust, surprise, anger, and fear.</p>
<p>Scholar Katherine Hayles says that Kismet was built as an ‘ecological whole’ to respond to both humans and the environment. ‘The community,’ she writes, ‘understood as the robot plus its human interlocutors, is greater than the sum of its parts, because the robot’s design and programming have been created to optimise interactions with humans.’</p>
<p>In other words, Kismet may have ‘social intelligence’.</p>
<p>Kismet’s creator Cynthia Breazal explains this through a telling example. If someone comes too close to it, Kismet retracts its head as if to suggest that its personal space is being violated, or that it is shy. In reality, it is trying to adjust its camera so that it can properly see whatever is in front of it. But it is the human interacting with Kismet who interprets this retraction as the robot requiring its own space by moving back. Breazal says, ‘Human interpretation and response make the robot’s actions more meaningful than they otherwise would be.’</p>
<p>In other words, humans interpret Kismet’s social intelligence as ‘emotional intelligence’...</p>
<p>Kismet was built at the start of a new field called affective computing, which is now branded as ‘emotion AI’. Affective computing is about analysing human facial expressions, gait and stance into a map of emotional states. Here is what Affectiva, one of the companies developing this technology, says about how it works:</p>
<p>‘Humans use a lot of non-verbal cues, such as facial expressions, gesture, body language and tone of voice, to communicate their emotions. Our vision is to develop Emotion AI that can detect emotion just the way humans do. Our technology first identifies a human face in real time or in an image or video. Computer vision algorithms then identify key landmarks on the face…[and] deep learning algorithms analyse pixels in those regions to classify facial expressions. Combinations of these facial expressions are then mapped to emotions.’</p>
<p>But there is also a more sinister aspect to this digitised love-fest. Our faces, voices, and selfies are being used to collect data to train future bots to be more realistic. There is an entire industry of Emotion AI that harvests human emotional data to build technologies that we are supposed to enjoy because they appear more human. But it often comes down to a question of social control, because the same emotional data is used to track, monitor and regulate our own emotions and behaviours...</p>
<p> </p>
<p>
For more details visit <a href='http://editors.cis-india.org/raw/maya-indira-ganesh-you-auto-complete-me-romancing-the-bot'>http://editors.cis-india.org/raw/maya-indira-ganesh-you-auto-complete-me-romancing-the-bot</a>
</p>
No publishersumandroBodies of EvidenceResearchers at WorkResearchPublicationsBD4DBotsBig Data for Development2019-12-06T05:00:19ZBlog EntryBig Data Governance Frameworks for 'Data Revolution for Sustainable Development'
http://editors.cis-india.org/internet-governance/blog/big-data-governance-frameworks-for-data-revolution-for-sustainable-development
<b>A key component of the process to achieve the Sustainable Development Goals is the call for a global 'data revolution' to better understand, monitor, and implement development interventions. Recently there has been several international proposals to use big data, along with reconfigured national statistical systems, to operationalise this 'data revolution for sustainable development.' This analysis by Meera Manoj highlights the different models of collection, management, sharing, and governance of global development data that are being discussed.</b>
<p> </p>
<p><strong>1.</strong> <a href="#1">What are the Sustainable Development Goals?</a></p>
<p><strong>2.</strong> <a href="#2">The Need for a Data Revolution</a></p>
<p><strong>3.</strong> <a href="#3">Big Data: Characteristics and Use for Development</a></p>
<p><strong>3.1.</strong> <a href="#3-1">Characteristics of Big Data</a></p>
<p><strong>3.2.</strong> <a href="#3-2">Using Big Data for Development</a></p>
<p><strong>4.</strong> <a href="#4">Sustainable Development and Data Rights</a></p>
<p><strong>5.</strong> <a href="#5">Governance Frameworks Proposed</a></p>
<p><strong>5.1.</strong> <a href="#5-1">UN Sustainable Development Solutions Network</a></p>
<p><strong>5.2.</strong> <a href="#5-2">The UN DATA Revolution Group</a></p>
<p><strong>5.3.</strong> <a href="#5-3">Organization for Economic Co-Operation and Development</a></p>
<p><strong>5.4.</strong> <a href="#5-4">The Global Partnership for Sustainable Development of Data</a></p>
<p><strong>5.5.</strong> <a href="#5-5">The World Economic Forum (WEF)</a></p>
<p><strong>5.6.</strong> <a href="#5-6">Dr. Julia Lane - A Quadruple Data Helix</a></p>
<p><strong>5.7.</strong> <a href="#5-7">Data Pop Alliance</a></p>
<p><strong>6.</strong> <a href="#6">Conclusion</a></p>
<p><strong>7.</strong> <a href="#7">Endnotes</a></p>
<p><strong>8.</strong> <a href="#8">Author Profile</a></p>
<hr />
<p>Speaking on Big Data, Dan Ariely commented that, "<em>Everyone talks about it, nobody really knows how to do it, and everyone thinks everyone else is doing it, so everyone claims they are doing it</em>" <strong>[1]</strong>. This offers a useful insight into the lack of adequate discourse on the kind of governance and accountability frameworks that are needed to facilitate the developmental, sustainable, and responsible uses of big data.</p>
<p>In light of the recent international proposals to use big data to track the Sustainable Development Goals, this paper highlights the different models of management, sharing, and governance of data that are being discussed, and concurrently, how they conceptualise the various rights around big data and how are they to be protected.</p>
<p> </p>
<h2 id="1">1. What are the Sustainable Development Goals?</h2>
<p>The Sustainable Development Goals, otherwise known as the Global Goals, build on the Millennium Development Goals (MDGs). Adopted on 1 January 2016, these universally applicable 17 goals of the 2030 Agenda for Sustainable Development, seek to end all forms of poverty, fight inequalities, tackle climate change and address a range of social needs like education, health, social protection and job opportunities over the next 15 years <strong>[2]</strong>.</p>
<p> </p>
<img src="https://raw.githubusercontent.com/cis-india/website/master/img/big-data-gov-framework_un-sdg.png" alt="Sustainable Development Goals" />
<h6>Source: UN Data Revolution Group, <em><a href="http://www.undatarevolution.org/wp-content/uploads/2014/12/A-World-That-Counts2.pdf">A World that Counts</a></em>, 2014, p.12.<br /></h6>
<p> </p>
<h2 id="2">2. The Need for a Data Revolution</h2>
<p>An overwhelming cause of concern regarding the precursor to the SDGs, the MDGs, is the data unavailability to monitor their progress. For instance, the figure below indicates that there is no five-year period when the availability of MDG related data is more than 70% of what is required. Entire groups of people and key issues remain invisible <strong>[3]</strong>. Lack of data is not only a problem for global statisticians, but also for people whose needs and demands remain invisible due to lack of quantitative representation of the same. For instance, the incidences of gender related crimes when not recorded could lead to a misconception on the achievement of the MDG of gender equality.</p>
<img src="https://raw.githubusercontent.com/cis-india/website/master/img/big-data-gov-framework_undrg_mdg-data.png" alt="UN Stats - Percentage of MDG data currently available for developing countries by nature of source." />
<h6>Source: UN, <a href="http://i0.wp.com/www.un.org/sustainabledevelopment/wp-content/uploads/2015/12/english_SDG_17goals_poster_all_languages_with_UN_emblem_1.png">Sustainable Development Goals</a>.<br /></h6>
<p>As the new goals (SDGs) cover a wider range of issues it is clear that a far higher level of detail is required. To this effect the High-Level Panel of Eminent Persons on the post-2015 agenda has called for a "data revolution for sustainable development" <strong>[4]</strong>.</p>
<p>The world is experiencing a Data Revolution and a "data deluge." One estimate has it that 90% of the data in the world has been created in the last 2 years. As Eric Schmidt of Google in 2010 famously said, "<em>There were 5 exabytes of information created between the dawn of civilization through 2003, but that much information is now created every 2 days</em> <strong>[5]</strong>.</p>
<p>In its report <em>A World that Counts</em>, the UN Data Revolution Group defines the data revolution as an explosion in the volume of data, the speed with which data are produced, the number of producers of data, the dissemination of data, and the range of things on which there is data, coming from new technologies such as mobile phones and the “internet of things”, and from other sources, such as qualitative data, citizen-generated data and perceptions data <strong>[6]</strong>.</p>
<p>This data revolution in the context of sustainable development has been defined by the UN Secretary General’s Independent Expert Advisory Group (IEAG) as follows:</p>
<blockquote>[T]he integration of data coming from new technologies with traditional data in order to produce relevant high‐quality information with more details and at higher frequencies to foster and monitor sustainable development. This revolution also entails the increase in accessibility to data through much more openness and transparency, and ultimately more empowered people for better policies, better decisions and greater participation and accountability, leading to better outcomes for the people and the planet <strong>[7]</strong>.</blockquote>
<p>The majority of such “data coming from new technologies” is what can be called big data. It is data being generated in real-time, in high velocity and volume, in a variety of forms and formats, and on an increasing range of phenomenon that are being mediated by digital technologies – from governance to human communication. Further, a good part of such big data is not about the content of the phenomenon concerned but about its process – for example, Call Detail Records are generated for each mobile phone call a person makes and it contains data about the process of the call (time, location, duration, recipient, etc.) but not about the content of the call. Big data about various governmental and human processes are becoming a crucial instrument for documenting and monitoring of the same.</p>
<p> </p>
<h2 id="3">3. Big Data: Characteristics and Use for Development</h2>
<h3 id="3-1">3.1. Characteristics of Big Data</h3>
<p>The simplest definition of big data is that it is a dataset of more than 1 petabyte. The US Bureau of Labour Statistics terms it to be non-sampled data, characterized by the creation of databases from electronic sources whose primary purpose is something other than statistical inference <strong>[8]</strong>.</p>
<p>The characteristics which broadly distinguish Big Data are sometimes called the “3 V’s”: more volume, more variety and higher rates of velocity <strong>[9]</strong>. Big data sources generally share some or all of these features <strong>[10]</strong>:</p>
<ul><li>Digitally generated,</li>
<li>Passively produced,</li>
<li>Automatically collected,</li>
<li>Geographically or temporally trackable, and</li>
<li>Continuously analysed.</li></ul>
<p>Increasingly, Big Data is recognised as creating "new possibilities for international development" <strong>[11]</strong>. It could provide faster, cheaper, more granular data and help meet growing and changing demands. It was claimed, for example, that "<em>Google knows or is in a position to know more about France than INSEE</em>" <strong>[12]</strong>, its highly resourceful national statistical agency. To illustrate, Global Pulse gives the example of a hypothetical small household facing soaring commodity prices, particularly food and fuel <strong>[13]</strong>. They have the options of:</p>
<ul><li>Getting part of their food at a nearby World Food Programme distribution centre,</li>
<li>Reducing mobile usage,</li>
<li>Temporarily taking their children out of school,</li>
<li>Calling a health hotline when children show signs of malnutrition related diseases, and</li>
<li>Venting about their frustration on social media.</li></ul>
<p>Such a systemic shock of food insecurity will prompt thousands of households to react in roughly similar ways. These collective behavioural changes may show up in different digital data sources:</p>
<ul><li>WFP might record that it serves twice as many meals a day,</li>
<li>The local mobile operator may see reduced usage,</li>
<li>UNICEF data may indicate that school attendance has dropped,</li>
<li>Health hotlines might see increased volumes of calls reporting malnutrition, and</li>
<li>Tweets mentioning the difficulty to “afford food” might begin to rise.</li></ul>
<p>Thus the power of real-time, digital data to predict paths for development is immense. Amassing such a large volume of data which tracks practically every aspect of social behavious can revolutionize the field of official statistics and policy making.</p>
<p>Two points to be noted are: 1) all these data sources are not available for comparison in the real-time by default, so one task before using big data in developmental work is to make data from different sources available across agencies and make them comparable, and 2) finding repeating patterns within large data sets, sourced from varied origins, can not only allow for monitoring but also (statistically) predicting future possibilities and implications for development action.</p>
<h3 id="3-2">3.2. Using Big Data for Development</h3>
<p>There are several international organizations attempting to use such data.</p>
<p>Global Pulse, a United Nations initiative, launched by the Secretary-General in 2009, seeks to leverage innovations in digital data, rapid data collection and analysis to help decision-makers gain a real-time understanding of how crises impact vulnerable populations. To this end, Global Pulse is establishing an integrated, global network of Pulse Labs, anchored in Pulse Lab New York, to pilot the approach at country level <strong>[14]</strong>.</p>
<p>The Global Working Group on Big Data for Official Statistics, created in May 2014, pursuant to Statistical Commission, makes an inventory of ongoing activities and examples regarding the use of big data, addresses concerns related to methodology, human resources, quality and confidentiality, and develops guidelines on classifying various types of big data sources <strong>[15]</strong>.</p>
<p>There have been applications even on a national and individual level. For instance, in 2013, various sources reported that the CIA had admitted to the “full monitoring of Facebook, Twitter, and other social networks” to identify links between events and sequences or paths leading to national security threats, ultimately leading to forecasting future activities and events <strong>[16]</strong>.</p>
<p>In the field of conflict prevention is the emerging applications to map and analyse unstructured data generated by politically active Internet use by academics, activists, civil society organizations, and even general citizens. In reference to Iran’s post-election crisis beginning in 2009, it is possible to detect web-based usage of terms that reflect a general shift from awareness towards mobilization, and eventually action within the population <strong>[17]</strong>.</p>
<p>The "Big Data, Small Credit" report proposes that financial inclusion can be promoted by allowing consumers with mobile phones to access credit formally as customers <strong>[18]</strong>.</p>
<p>At a national level, the biggest challenge for most big data projects is the limited or restricted access the government agencies have to potential big data sets owned by the private sector <strong>[19]</strong>. The overall consensus is that Big Data to track SDGs must complement traditional data sources <strong>[20]</strong>. This is because big data may not always be available for the entire population, or include a diverse enough sample of the population. Moreover most big data projects measure development indicators through a correlation which may not always be correct unlike official data. For instance big data might help in predicting lowered household income through reducing mobile bills while traditional data directly collects income statistics.</p>
<p>In a survey by the Global Working Group on Big Data for Official Statistics <strong>[21]</strong>, it was found that only a few countries have developed a long-term vision for the use of big data, while many are formulating a big data strategy. Most countries have not yet defined business processes for integrating big data sources and results into their work and do not have a defined structure for managing big data projects.</p>
<p>Thus there exists a need to identify a governance framework for big data for sustainable development, not only at national level, but also at the international level.</p>
<p> </p>
<h2 id="4">4. Sustainable Development and Data Rights</h2>
<p>Any discussion on governance frameworks would be incomplete without defining the kind of data rights they must seek to protect.</p>
<p>In the famous parable of the six blind men and the elephant they conclude that the elephant is like a wall, snake, spear, tree, fan or rope, depending upon where they touch. Similarly Internet experiences of individual users (what they touch) often contrast drastically with different views (what they conclude) on what would constitute data rights.</p>
<p>The IEAG in its report has identified the following set of data related rights, but has not defined any actual framework or process for ensuring them (yet) <strong>[22]</strong>:</p>
<ul><li>Right to be counted,</li>
<li>Right to an identity,</li>
<li>Right to privacy and to ownership of personal data,</li>
<li>Right to due process (for example when data is used as evidence in proceedings, or in administrative decisions),</li>
<li>Freedom of expression,</li>
<li>Right to participation,</li>
<li>Right to non-discrimination and equality, and</li>
<li>Principles of consent.</li></ul>
<p>Personal data is broadly defined as "<em>any information relating to an identified or identifiable individual</em>" <strong>[23]</strong>. Often primary data producers (users of services and devices generating data) are unaware of individual privacy infringements <strong>[24]</strong>.</p>
<p>A survey by the Global Working Group on Big Data for Official Statistics found that only a few countries have a specific privacy framework for big data, while most apply the privacy framework for traditional statistics to big data as well <strong>[25]</strong>.</p>
<p>Conventionally, safeguards against the re-use of big data to protect data rights have involved the “anonymization” or “de-identification” of data, to conceal individual identities. Global Pulse, for instance, is putting forth the concept of Data Philanthropy, whereby "<em>corporations take the initiative to anonymize (strip out all personal information) their data sets and provide this data to social innovators to mine the data for insights, patterns and trends in real-time or near real-time</em>" <strong>[26]</strong>. There however exists a debate on whether data can actually be anonymized effectively. Several state that data can never be effectively de-anonymized due to technological challenges <strong>[27]</strong>. For instance, when the New York City government released de-anonymised data sets of New York cab drivers were made re-identifiable by approaching a separate method. Within less than 2 hours work, researchers knew which driver drove every single trip in this entire dataset. It would be even be easy to calculate drivers’ gross income, or infer where they live <strong>[28]</strong>.</p>
<p>Even the OECD opines that the current model of limiting identifiability of individuals is unsustainable. It recommends moving towards one where the focus is on transparency around how data is being used, rather than preventing specific types of use, stating that - "<em>research funding agencies and data protection authorities should collaborate to develop an internationally recognized framework code of conduct covering the use of new forms of personal data, particularly those generated via network communication. This framework, built on best practice procedures for consent from data subjects, data sharing and re-use, anonymization methods, etc., could be adapted as necessary for specific national circumstances</em>" <strong>[29]</strong>.</p>
<p>Thus, there is a push for the arguement that the historical approaches to protecting privacy and confidentiality — namely, <em>informed consent</em> and <em>anonymity</em> — no longer hold <strong>[30]</strong>. Some have even suggested using big data itself to keep track of user permissions for each piece of data to act as a legal contract <strong>[31]</strong>.</p>
<p>There is an overall consensus that any legal or regulatory mechanisms set up to mobilise the 'data revolution for sustainable development' should protect the data rights of the people <strong>[32]</strong>, without any clear agreement on what these rights may be.</p>
<p> </p>
<h2 id="5">5. Governance Frameworks Proposed</h2>
<p>A largely unanswered question that is posed in light of the emerging consensus on the use of Big Data for monitoring SDGs is within what sort of governance frameworks these data collection and analysis methods will operate. Methods of collection and the key actors involved in data analysis, management, storage and coordination. The role of NGOs and CSOs, if any, within these systems must be delineated. Certain key global organizations and eminent researchers have suggested the following models.</p>
<h3 id="5-1">5.1. UN Sustainable Development Solutions Network</h3>
<p>In 2012, the UN Secretary-General launched the UN Sustainable Development Solutions Network (SDSN) to mobilize global scientific and technological expertise to promote practical problem solving for sustainable development, including the design and implementation of the Sustainable Development Goals (SDGs) <strong>[33]</strong>. It has proposed the following.</p>
<p><strong>Collection</strong></p>
<p>The Inter-Agency and Expert Group on Sustainable Development Goal Indicators (IAEGSDG) and the United Nations Statistical Commission are to establish roadmaps for strengthening specific data collection tools that enable the monitoring of SDG indicators.</p>
<p><strong>Analysis</strong></p>
<p>Based on discussions with a large number of statistical offices, including Eurostat, BPS Indonesia, the OECD, the Philippines, the UK, and many others, 100 is recommended to be the maximum number of global indicators to analyse data for which NSOs can report and communicate effectively in a harmonized manner. This conclusion was strongly endorsed during the 46th UN Statistical Commission and the Expert Group Meeting on SDG indicators <strong>[34]</strong>.</p>
<p>Specialist indicators developed by thematic communities must be used for data analysis as they include input and process metrics that are helpful complements to official indicators, which tend to be more outcome-focused. For example, the UN Inter-Agency Group on Child Mortality Estimation has developed a specialist hub responsible for analysing, checking, and improving mortality estimation. This is a leading source for child morality information for both governments and non-governmental actors <strong>[35]</strong>.</p>
<p>Research arms of private companies such as Microsoft Research, IBM research, SAS, and R&D arms of telecom companies could directly partner with official statistical systems to share sophisticated analysing techniques <strong>[36]</strong>.</p>
<p><strong>Management</strong></p>
<p>Four levels of monitoring, national, regional, global, and thematic, should be "<em>organized in an integrated architecture</em>" <strong>[37]</strong>.</p>
<p>Countries must decide individually whether official data must be complemented with non-official indicators from big data which can add richness to the monitoring of the SDGs.</p>
<p>Where possible, regional monitoring should build on existing regional mechanisms, such as the Regional Economic Commissions, the Africa Peer Review Mechanism, or the Asia-Pacific Forum on Sustainable Development <strong>[38]</strong>.</p>
<p>To coordinate thematic monitoring under the SDGs, each thematic initiative may have one or more lead specialist agencies or “custodians” as per the IAEG-MDG monitoring processes. Lead agencies would be responsible for convening multi-stakeholder groups, compiling detailed thematic reports, and encouraging ongoing dialogues on innovation. These thematic groups can become testing grounds in launching a data revolution for the SDGs, trialling new measurements and metrics that in time can feed into the global monitoring process with annual reports <strong>[39]</strong>.</p>
<img src="https://raw.githubusercontent.com/cis-india/website/master/img/big-data-gov-framework_unsdsn_monitoring.png" alt="UN Sustainable Development Solutions Network - Schematic illustration with explanation of the indicators for national, regional, global, and thematic monitoring." />
<h6>Schematic illustration with explanation of the indicators for national, regional, global, and thematic monitoring.<br />Source: UN Sustainable Development Solutions Network, <em><a href="http://unsdsn.org/wp-content/uploads/2015/05/150612-FINAL-SDSN-Indicator-Report1.pdf">Indicators and a Monitoring Framework for the Sustainable Development Goals: Launching a Data Revolution for the SDGs</a></em>, 2015, p.3.<br /></h6>
<p><strong>Role of NSOs</strong></p>
<p>Monitoring the SDG agenda will require substantive improvements in national statistical capacity. Assessments of existing capacity to fulfil SDG monitoring expectations must be undertaken and needs be integrated into National Strategies for the Development of Statistics (NSDSs) <strong>[40]</strong>.</p>
<p><strong>Coordination</strong></p>
<p>A Global Partnership for Sustainable Development Data must be established and a World Forum on Sustainable Development Data be convened in 2016 to create mechanisms for ongoing collaboration and innovation.</p>
<p>A high-level, powerful group of businesses and states must convene the various data and transparency sustainable development initiatives under one umbrella.</p>
<p>To ensure comparability, Global Monitoring Indicators must be harmonized across countries by one lead technical or specialist agency which will additionally coordinate data standards and collection and provide technical support.</p>
<p>The following table indicates the suggested Lead Agencies for individual SDGs <strong>[41]</strong>.</p>
<table>
<tbody>
<tr>
<td><strong>Number</strong></td>
<td><strong>Sustainable Development Goal</strong></td>
<td><strong>Lead Agencies</strong></td>
</tr>
<tr>
<td>1.</td>
<td>No Poverty</td>
<td>World Bank, UNDP, UNSD, UNICEF, ILO, FAO, UN-Habitat, UNISDR, WHO, CRED, UNFPA, and UN Population Division</td>
</tr>
<tr>
<td>2.</td>
<td>No Hunger</td>
<td>FAO, WHO, UNICEF, and Internal Fertilizer Industry Associaton (IFA)</td>
</tr>
<tr>
<td>3.</td>
<td>Good Health</td>
<td>WHO, UN Population Division, UNICEF, World Bank, GAVI, UN AIDS, and UN-Habitat</td>
</tr>
<tr>
<td>4.</td>
<td>Quality Education</td>
<td>UNESCO, UNICEF, and World Bank</td>
</tr>
<tr>
<td>5.</td>
<td>Gender Equality</td>
<td>UNICEF, UN Women, WHO, UNSD, ILO, UN Population Division, and UNFPA</td>
</tr>
<tr>
<td>6.</td>
<td>Clean Water and Sanitation</td>
<td>WHO/UNICEF Joint Monitoring Programme (JMP), FAO, UN Water, and UNEP</td>
</tr>
<tr>
<td>7.</td>
<td>Renewable Energy</td>
<td>Sustainable Energy for All, IEA, WHO, World Bank, and UNFCC</td>
</tr>
<tr>
<td>8.</td>
<td>Good Jobs and Economic Growth</td>
<td>IMF, World Bank, UNSD, and ILO</td>
</tr>
<tr>
<td>9.</td>
<td>Innovation and Infrastructure</td>
<td>World Bank, OECD, UNIDO, UNFCC, UNESCO, and ITU</td>
</tr>
<tr>
<td>10.</td>
<td>Reduced Inequalities</td>
<td>UNSD, World Bank, and OECD</td>
</tr>
<tr>
<td>11.</td>
<td>Sustainable Cities and Communities</td>
<td>UN-Habitat, Global City Indicators Facility, WHO, CRED, UNISDR, FAO, and UNEP</td>
</tr>
<tr>
<td>12.</td>
<td>Responsible Consumption</td>
<td>EITI, UNCTAD, UN Global Compact, FAO, UNEP Ozone Secretariat, WBCSD, GRI, IIRC, and Global Compact</td>
</tr>
<tr>
<td>13.</td>
<td>Climate Action</td>
<td>OECD DAC, UNFCCC, and IEA</td>
</tr>
<tr>
<td>14.</td>
<td>Life below Water</td>
<td>UNEP-WCMC, IUCN, and FMC</td>
</tr>
<tr>
<td>15.</td>
<td>Life on Land</td>
<td>FAO, UNEP, IUCN, and UNEP- WCMC</td>
</tr>
<tr>
<td>16.</td>
<td>Peace and Justice</td>
<td>UNODC, WHO, UNOCHA, UNCHR, IOM, OCHA, OECD, UN Global Compact, EITI, UNCTAD, UNICEF, UNESCO, and Transparency International</td>
</tr>
<tr>
<td>17.</td>
<td>Partnership for the Goals</td>
<td>BIS, IASB, IFRS, IMF, WIPO, WTO, UNSD, OECD, World Bank, OECD DAC, and SDSN</td>
</tr>
</tbody>
</table>
<h3 id="5-2">5.2. The UN DATA Revolution Group</h3>
<p>The group constituted by the UN Secretary-General Ban Ki-moon in August 2014, is an Independent Expert Advisory Group with the aim of making concrete recommendations on bringing about a 'data revolution for sustainable development' <strong>[42]</strong>. In its report, <em>A World that Counts</em>, it makes the following recommendations <strong>[43]</strong>.</p>
<p><strong>Collection</strong></p>
<p>Clear standards on data collection methods must be developed based on the UN Fundamental Principles of Official Statistics. Periodic audits must be conducted by professional and independent third parties to ensure data quality.</p>
<p>Governments, civil society, academia and the philanthropic sector must work together strengthening statistical literacy so that all people have capacity to input into and evaluate the quality of data.</p>
<p>Social entrepreneurs, private sector, academia, media, civil society and other individuals and institutions must be engaged globally with incentives (prizes, data challenges) to encourage data sharing.</p>
<p><strong>Analysis</strong></p>
<p>A SDGs Analysis and Visualisation Platform is to be set up for fostering private-public partnerships and community-led peer-production efforts for data analysis.</p>
<p>A dashboard on ”the state of the world” will engage the UN, think-tanks, academics and NGOs in analysing, and auditing data.</p>
<p>Academics and scientists are to analyse data to provide long-term perspectives, knowledge and data resources at all levels.</p>
<p>The “Global Forum of SDG-Data Users” will ensure feedback loops between data producers, processors and users to improve the usefulness of data and information produced.</p>
<p>A “SDGs data lab” to support the development of a first wave of SDG indicators is to be established mobilizing key public, private and civil society data providers, academics and stakeholders working with the Sustainable Development Solutions Network.</p>
<p><strong>Storage</strong></p>
<p>A “world statistics cloud” will store data and metadata produced by different institutions but according to common standards, rules and specifications.</p>
<p><strong>Role of NSOs</strong></p>
<p>Civil society organisations must share data and processing methods with private and public counterparts on the basis of agreements. They must hold governments and companies accountable using evidence on the impact of their actions, provide feedback to data producers, develop data literacy and help communities and individuals generate and use data.</p>
<p>NSOs are the central players of the Data Revolution. Their autonomy must be strengthened to maintain data quality. They must abandon expensive and cumbersome production processes, incorporate new data sources like big data that is human and machine-readable, compatible with geospatial information systems and available quickly enough to ensure that the data cycle matches the decision cycle. Collaborations with the private sector can boost technical and financial investments.</p>
<p><strong>Coordination</strong></p>
<p>Key stakeholders must create a “Global Consensus on Data”, to adopt principles concerning legal, technical, privacy, geospatial and statistical standards. Best practices related to public data such as the Open Government Partnership (OGP) and the G8 Open Data Charter are recommended foundations for such principles.</p>
<p>A UN-led “Global Partnership for Sustainable Development Data” is proposed, to coordinate and broker key global public-private partnerships for data sharing <strong>[44]</strong>.</p>
<p>A “World Forum on Sustainable Development Data” and “Network of Data Innovation Networks” will be a converging point for the data ecosystem to share ideas and experiences for improvements, innovation and technology transfer.</p>
<h3 id="5-3">5.3. Organization for Economic Co-Operation and Development (OECD)</h3>
<p>The Organisation for Economic Co-operation and Development (OECD) is an inter-governmental organization that seeks to promote policies that will improve the economic and social well-being of people globally. It has made the following proposals <strong>[45]</strong>.</p>
<p><strong>Collection</strong></p>
<p>Data is to be collected from National statistical agencies, national and international researchers and international organisations.</p>
<p><strong>Role of NSOs</strong></p>
<p>By leveraging the expertise of telecommunications companies and software developers, for instance, national statistical systems could potentially reduce costs and improve the availability of data to monitor development goals <strong>[46]</strong>.</p>
<p><strong>Coordination</strong></p>
<p>National Data Forums for Social Science Data must be created for the development of social science data for improved coordination between social scientists, data producers (national statistical agencies, government departments, large private sector businesses and sources undertaking academic direction), and data curators.</p>
<p>Social science research communities must contribute to national plans of action after a needs assessment <strong>[47]</strong>. Research funding agencies must collaborate at the international level for a common system for referencing datasets in research publications <strong>[48]</strong>.</p>
<h3 id="5-4">5.4. The Global Partnership for Sustainable Development of Data</h3>
<p>The partnership is a global network of governments, NGOs, and businesses working to strengthen the inclusivity, trust, and innovation in the way that data is used to address the world’s sustainable development efforts <strong>[49]</strong>.</p>
<p><strong>Analysis</strong></p>
<p>There must be a common framework for information processing. At minimum, a simple lexicon must tag each datum specifying:</p>
<ul><li><strong>What:</strong> i.e. the type of information contained in the data,</li>
<li><strong>Who:</strong> the observer or reporter,</li>
<li><strong>How:</strong> the channel through which the data was acquired,</li>
<li><strong>How much:</strong> whether the data is quantitative or qualitative, and</li>
<li><strong>Where and when:</strong> the spatio-temporal granularity of the data.</li></ul>
<p>Analysis of data involves filtering relevant information, summarising keywords and categorising into indicators. This intensive mining of socioeconomic data, known as “reality mining,” can be done by: (1) Continuous analysis of real time streaming data, (2) Digestion of semi-structured and unstructured data to determine perceptions, needs and wants. (3) Real-time correlation of streaming data with slowly accessible historical data repositories.</p>
<p>Use of big data for developmental goals can draw upon all three techniques to various degrees depending on availability of data and the specific needs.</p>
<p><strong>Role of NSOs</strong></p>
<p>NSOs have a pivotal part to play in the data revolution. Countries and organizations believe that big data cannot replace traditional official statistical data as it is based more on perception than facts. To quote Winston Churchill, "<em>Do not trust any statistics that you did not fake yourself</em>."</p>
<p>For instance, a study found that Google Flu Trends, to detect influenza epidemics, predicted nonspecific flu-like respiratory illnesses well but not actual flu. The mismatch was due to popular misconceptions on influenza symptoms. This has important policy implications. Doctors using Google Flu Trends may overstock on flu vaccines or be overly inclined to diagnose normal respiratory illnesses as influenza <strong>[50]</strong>.</p>
<p>However Big Data if understood correctly, can inform where further targeted investigation is necessary and give immediate responses to favourably change outcomes.</p>
<h3 id="5-5">5.5. The World Economic Forum (WEF)</h3>
<p>The WEF is an International Organization for Public-Private Cooperation. It engages the foremost political, business and other leaders of society to shape global, regional and industry agendas <strong>[51]</strong>. In the report titled <em>Big Data, Big Impact: New Possibilities for International Development</em>, it makes the following recommendations <strong>[52]</strong>.</p>
<p><strong>Collection</strong></p>
<p>Data production and development actors include individuals, public sector and the private sector. Each produce different kinds of data that have unique requirements. The private sector maintains vast troves of transactional data, much of which is "data exhaust," or data created as a by-product of other transactions. The public sector maintains enormous datasets in the form of census data, health indicators, and tax and expenditure information. The following figure highlights the different kinds of data that each sector collects and what incentives they have to share the data along with requirements to maintain such data.</p>
<img src="https://raw.githubusercontent.com/cis-india/website/master/img/big-data-gov-framework_wef_01.png" alt="" />
<h6>World Economic Forum - Diagram on Data Commons.<br />
Source: World Economic Forum, <em><a href="http://www3.weforum.org/docs/WEF_TC_MFS_BigDataBigImpact_Briefing_2012.pdf">Big Data, Big Impact: New Possibilities for International Development</a></em>, 2012, p.4.<br /></h6>
<p>Business models must be created to provide the appropriate incentives for private-sector actors to share data. Such models already exist in the Internet environment. For instance companies in search and social networking profit from products they offer at no charge to end users because the usage data these products generate is valuable to other ecosystem actors. Similar models could be created in garnering Big Data for SDGs. The following flowchart illustrates how different sectors must work together to incentivise data collection and sharing.</p>
<img src="https://raw.githubusercontent.com/cis-india/website/master/img/big-data-gov-framework_wef_02.png" alt="" />
<h6>World Economic Forum - Diagram on Global Coordination.<br />
Source: World Economic Forum, <em><a href="http://www3.weforum.org/docs/WEF_TC_MFS_BigDataBigImpact_Briefing_2012.pdf">Big Data, Big Impact: New Possibilities for International Development</a></em>, 2012, p.7.<br /></h6>
<h3 id="5-6">5.6. Dr. Julia Lane - A Quadruple Data Helix</h3>
<p>Dr. Julia Lane is a Professor in the Wagner School of Public Policy at New York University; and also a Provostial Fellow in Innovation Analytics and a Professor in the Center for Urban Science and Policy <strong>[53]</strong>. She has done extensive research on the uses of big data. In her paper titled "Big Data for Public Policy: A Quadruple Data Helix," she makes the following suggestions <strong>[54]</strong>.</p>
<p><strong>Collection</strong></p>
<p>In the future there will exist a model of a quadruple data helix for data collection which will have four strands — state and city agencies, universities, private data providers, and federal agencies.i</p>
<p>A new set of institution, city/university data facilities, must be established. These institutions should form the backbone of the quadruple helix, with direct connections to the private sector and to the federal statistical agencies.</p>
<p><strong>Analysis</strong></p>
<p>There is a need for graduate training for non-traditional students, who need to understand how to use data science tools as part of their regular employment. They must identify and capture the appropriate data, understand how data science models and tools can be applied, and determine how associated errors and limitations can be identified from a social science perspective.i</p>
<p>Universities can act as a trusted independent third party to process, store, analyze, and disseminate data. ii</p>
<p><strong>Management</strong></p>
<p>The new infrastructure must ensure that data from disparate sources are collected managed and used in a manner that is informed by end users. There are many technical challenges: disparate data sets must be ingested, their provenance determined, and metadata documented. Researchers must be able to query data sets to know what data are available and how they can be used. And if data sets are to be joined, they must be joined in a scientific manner, which means that workflows need to be traced and managed in such a way that the research can be replicated.</p>
<p><strong>Coordination</strong></p>
<p>The role of State and City agencies is to address immediate policy issues, rather than to build long-term data infrastructures as their mandate is to work with city data than the full spectrum of available data.</p>
<h3 id="5-7">5.7. Data-Pop Alliance</h3>
<p>Data-Pop Alliance is a global coalition on Big Data and development created by the Harvard Humanitarian Initiative, MIT Media Lab, and Overseas Development Institute that brings together researchers, experts, practitioners, and activists to promote a people-centred big data revolution through collaborative research, capacity building, and community engagement <strong>[55]</strong>. It makes the following suggestions.</p>
<p><strong>Collection</strong></p>
<p>The idea of <em>shared responsibility</em> between the public and private sector is a proposed operational principles to create a deliberative space. Mechanisms and legal frameworks must be devised for private companies to share their big data under formalized and stable arrangements instead of being compelled by ad hoc requests from researchers and policymakers.</p>
<p>The media too, could avoid publishing statistical data collected by unexplained methodologies by employing "statistical editors" and disseminate verified information.</p>
<p><strong>Role of NSOs</strong></p>
<p>For official statistics, engaging with Big Data is not a technical consideration but a political obligation. In a two tier system of official and non-official statistics, the public and investors tend to distrust official figures. For instance, the results of the 2010 census in the UK are being disputed on the basis of sewage data.</p>
<p>It is imperative for NSOs to retain, or regain, their primary role as the legitimate custodian of knowledge and creator of a deliberative public space to democratically drive human development <strong>[56]</strong>.</p>
<p> </p>
<h2 id="6">6. Conclusion</h2>
<p>The Big data frameworks provide some useful insights on monitoring mechanisms though some questions remain unanswered in each model. Key actors that have been proposed include city and state agencies like NSOs, private companies, social scientists, private individuals and international research agencies. Data analysis can be through public-private collaborations, data philanthropy, and using indicators by thematic communities.</p>
<p><strong>Collection</strong></p>
<p>There appears consensus across models that collection must be effected through public private partnerships while providing incentives.</p>
<p><strong>Analysis</strong></p>
<p>While several methods of analysis have been proposed by the Global Partnership it is unclear on who will be conducting the analysis. The UNSDSN has suggested that it be conducted by academics and scientists with Julia Lane stating it must be through public private partnerships which appear more feasible and transparent.</p>
<p><strong>Role of NSOs</strong></p>
<p>All frameworks agree on the pivotal role of NSOs and acknowledge them as the key players and coordinators at the national level. They must be strengthened financially, technologically and politically. Most frameworks seek to empower national agencies which will coordinate collaborations with the private sector through incentives while protecting personal data.</p>
<p><strong>Coordination</strong></p>
<p>Several international fora have been proposed to enable coordination while there is consensus that the NSOs. A Global Partnership for Sustainable Development Data, a Global Consensus on Data and a World Forum on Sustainable Development Data have been suggested. UN organizations appear to be suggesting more responsibility for those in the UN framework with UNSDSN giving an extensive list of lead agencies (UNDP, UN Women, Who etc) while the WEF emphasises on the private sector, Data Pop Alliance on NSOs, and Prof. Lane on State and City agencies.</p>
<p>On an international level countries can opt to join international organization that are being setup for the purpose. It remains to be seen whether all countries globally can achieve such a feat in a coordinated manner without infringing on data rights when unanswerable to any set international organization. The burden appears to fall on civil society and market forces within the private sector to regulate this process. For instance when a private sector company starts providing large un-anonymized data sets for government use, the privacy concerns of civil society that result in them opting for the company’s competitor’s more privacy friendly products will result in a regulation through market forces. However these forces may have disparate strengths in different contexts and countries depending on market practices and information asymmetry resulting in the lack of a uniform accountability mechanism.</p>
<p> </p>
<h2 id="7">7. Endnotes</h2>
<p><strong>[1]</strong> Dan Ariely, Facebook, January 06, 2013, <a href="https://www.facebook.com/dan.ariely/posts/904383595868">https://www.facebook.com/dan.ariely/posts/904383595868</a>.</p>
<p><strong>[2]</strong> United Nations Organizations, 'Sustainable Development Goals' (United Nations Sustainable Development, 26 September 2015), <a href="http://www.un.org/sustainabledevelopment/sustainable-development-goals/">http://www.un.org/sustainabledevelopment/sustainable-development-goals/</a>, accessed 6 June 2016.</p>
<p><strong>[3]</strong> Data Revolution Group, 'A World that Counts: Mobilising the Data Revolution for Sustainable Development' (November 2014), <a href="http://www.undatarevolution.org/wp-content/uploads/2014/12/A-World-That-Counts2.pdf">http://www.undatarevolution.org/wp-content/uploads/2014/12/A-World-That-Counts2.pdf</a>, accessed 8 June 2016.</p>
<p><strong>[4]</strong> High level panel on the post-2015 development agenda , 'A New Global Partnership: Eradicate Poverty and Transform Economies through Sustainable Development'(Post2015hlp,0rg, July 2012), <a href="http://www.post2015hlp.org/">http://www.post2015hlp.org/</a>, accessed 8 June 2016.</p>
<p><strong>[5]</strong> Gary King, 'Ensuring the Data-Rich Future of the Social Sciences' [2011] 3(2) Science, <a href="http://gking.harvard.edu/files/datarich.pdf">http://gking.harvard.edu/files/datarich.pdf</a>, accessed 8 June 2016.</p>
<p><strong>[6]</strong> See <strong>[3]</strong>.</p>
<p><strong>[7]</strong> Ibid.</p>
<p><strong>[8]</strong> Michael Horrigan, 'Big Data: A Perspective from the BLS' (Amstatorg, 1 January 2013) <a href="http://magazine.amstat.org/blog/2013/01/01/sci-policy-jan2013/">http://magazine.amstat.org/blog/2013/01/01/sci-policy-jan2013/</a>, accessed 4 June 2016.</p>
<p><strong>[9]</strong> UN Global Pulse, 'Big Data for Development: Challenges & Opportunities' (6 May 2012) <a href="http://www.unglobalpulse.org/sites/default/files/BigDataforDevelopment-UNGlobalPulseJune2012.pdf">http://www.unglobalpulse.org/sites/default/files/BigDataforDevelopment-UNGlobalPulseJune2012.pdf</a>, accessed 5 June 2016.</p>
<p><strong>[10]</strong> Emmanuel Letouzé and Johannes Jütting, 'Official Statistics, Big Data and Human Development: Towards a New Conceptual and Operational Approach' (2014) 12(3), Data-Pop Alliance White papers Series, <a href="https://www.odi.org/sites/odi.org.uk/files/odi-assets/events-documents/5161.pdf">https://www.odi.org/sites/odi.org.uk/files/odi-assets/events-documents/5161.pdf</a>, accessed 4 June 2016.</p>
<p><strong>[11]</strong> See <strong>[9]</strong>.</p>
<p><strong>[12]</strong> See <strong>[10]</strong>.</p>
<p><strong>[13]</strong> See <strong>[9]</strong>.</p>
<p><strong>[14]</strong> UN Global Pulse, 'About: United Nations Global Pulse' (2016) <a href="http://www.unglobalpulse.org/about-new">http://www.unglobalpulse.org/about-new</a>, accessed 7 June 2016.</p>
<p><strong>[15]</strong> UN Stats, 'Global Working Group' (2014) <a href="http://unstats.un.org/unsd/bigdata/">http://unstats.un.org/unsd/bigdata/</a>, accessed 8 June 2016.</p>
<p><strong>[16]</strong> New York City Press Release, ‘Mayor Bloomberg, Police Commissioner Kelly and Microsoft Unveil New, State-of-the-Art Law Enforcement Technology that Aggregates and Analyzes Existing Public Safety Data in Real Time to Provide a Comprehensive View of Potential Threats and Criminal Activity’ (New York City, 8 August 2012), <a href="http://www1.nyc.gov/office-of-the-mayor/news/291-12/mayor-bloomberg-police-commissioner-kelly-microsoft-new-state-of-the-art-law">http://www1.nyc.gov/office-of-the-mayor/news/291-12/mayor-bloomberg-police-commissioner-kelly-microsoft-new-state-of-the-art-law</a>, accessed 2 July 2016.</p>
<p><strong>[17]</strong> Francesco Mancini, 'New Technology and the Prevention of Violence and Conflict' (Reliefwebint, April 2013), <a href="http://reliefweb.int/sites/reliefweb.int/files/resources/ipi-e-pub-nw-technology-conflict-prevention-advance.pdf">http://reliefweb.int/sites/reliefweb.int/files/resources/ipi-e-pub-nw-technology-conflict-prevention-advance.pdf</a>, accessed 2 July 2016.</p>
<p><strong>[18]</strong> Arjuna Costa, Anamitra Deb, and Michael Kubzansky, 'Big Data, Small Credit: The Digital Revolution and Its Impact on Emerging Market Consumers,' (Omidyar, 3 March 2013) <a href="https://www.omidyar.com/sites/default/files/file_archive/insights/Big%20Data,%20Small%20Credit%20Report%202015/BDSC_Digital%20Final_RV.pdf">https://www.omidyar.com/sites/default/files/file_archive/insights/Big%20Data,%20Small%20Credit%20Report%202015/BDSC_Digital%20Final_RV.pdf</a>, accessed 2 July 2016.</p>
<p><strong>[19]</strong> United Nations Economic and Social Council, 'Report of the Global Working Group on Big Data for Official Statistics' (UN Stats, 3 March 2015), <a href="http://unstats.un.org/unsd/statcom/doc15/2015-4-BigData-E.pdf">http://unstats.un.org/unsd/statcom/doc15/2015-4-BigData-E.pdf</a>, accessed 8 June 2016.</p>
<p><strong>[20]</strong> Ibid.</p>
<p><strong>[21]</strong> Ibid.</p>
<p><strong>[22]</strong> See <strong>[3]</strong>.</p>
<p><strong>[23]</strong> OECD, 'OECD Guidelines on the Protection of Privacy and Transborder Flows of Personal Data' (23 September 1980), <a href="http://www.oecd.org/sti/ieconomy/oecdguidelinesontheprotectionofprivacyandtransborderflowsofpersonaldata.htm">http://www.oecd.org/sti/ieconomy/oecdguidelinesontheprotectionofprivacyandtransborderflowsofpersonaldata.htm</a>, accessed 29 May 2016.</p>
<p><strong>[24]</strong> Amir Efrati, ''Like' Button Follows Web Users' (WSJ, 18 May 2011) <a href="http://www.wsj.com/articles/SB10001424052748704281504576329441432995616">http://www.wsj.com/articles/SB10001424052748704281504576329441432995616</a>, accessed 23 May 2016.</p>
<p><strong>[25]</strong> See <strong>[15]</strong>.</p>
<p><strong>[26]</strong> Robert Kirkpatrick, 'Data Philanthropy: Public and Private Sector Data Sharing for Global Resilience' (UN Global Pulse, 16 September 2011), <a href="http://www.unglobalpulse.org/blog/data-philanthropy-public-private-sector-data-sharing-global-resilience">http://www.unglobalpulse.org/blog/data-philanthropy-public-private-sector-data-sharing-global-resilience</a>, accessed 4 June 2016.</p>
<p><strong>[27]</strong> Ibid.</p>
<p><strong>[28]</strong> Arvind Narayanan, 'No silver bullet: De-identification still doesn't work' (1 April 2016), <a href="http://randomwalker.info/publications/no-silver-bullet-de-identification.pdf">http://randomwalker.info/publications/no-silver-bullet-de-identification.pdf</a>, accessed 3 July 2016.</p>
<p><strong>[29]</strong> OECD Global Science Forum, 'New Data for Understanding the Human Condition: International Perspectives,' (February 2013) <a href="http://www.oecd.org/sti/sci-tech/new-data-for-understanding-the-human-condition.pdf">http://www.oecd.org/sti/sci-tech/new-data-for-understanding-the-human-condition.pdf</a>, accessed 2 June 2016.</p>
<p><strong>[30]</strong> S. Barocas, 'The Limits of Anonymity and Consent in the Big Data Age,' in <em>Privacy, Big Data, and the public good: Frameworks for Engagement</em> (Cambridge University Press, 2014).</p>
<p><strong>[31]</strong> A. Pentland, 'Institutional Controls: The New Deal on Data,' in <em>Privacy, Big Data, and the public good: Frameworks for Engagement</em> (Cambridge University Press, 2014).</p>
<p><strong>[32]</strong> See <strong>[3]</strong>.</p>
<p><strong>[33]</strong> UN Sustainable Development Solutions Network, 'About Us: Vision and Organization' (2012) <a href="http://unsdsn.org/about-us/vision-and-organization/">http://unsdsn.org/about-us/vision-and-organization/</a>, accessed 2 June 2016.</p>
<p><strong>[34]</strong> UN Sustainable Development Solutions Network, 'Indicators and a Monitoring Framework for the Sustainable Development Goals: Launching a data revolution for the SDGs' (12 June 2015) <a href="http://unsdsn.org/wp-content/uploads/2015/05/150612-FINAL-SDSN-Indicator-Report1.pdf">http://unsdsn.org/wp-content/uploads/2015/05/150612-FINAL-SDSN-Indicator-Report1.pdf</a>, accessed 4 June 2016.</p>
<p><strong>[35]</strong> UNICEF, 'CME Info - Child Mortality Estimates' (2014) <a href="http://www.childmortality.org/">http://www.childmortality.org/</a>, accessed 1 June 2016.</p>
<p><strong>[36]</strong> See <strong>[10]</strong>.</p>
<p><strong>[37]</strong> UNESCO, 'Technical report by the Bureau of the United Nations Statistical Commission (UNSC) on the process of the development of an indicator framework for the goals and targets of the post-2015 development agenda' (6 March 2015) <a href="http://www.uis.unesco.org/ScienceTechnology/Documents/unsc-post-2015-draft-indicators.pdf">http://www.uis.unesco.org/ScienceTechnology/Documents/unsc-post-2015-draft-indicators.pdf</a>, accessed 3 June 2016.</p>
<p><strong>[38]</strong> UN, 'The Road to Dignity by 2030: Ending Poverty, Transforming All Lives and Protecting the Planet ' (4 December 2014) <a href="http://www.un.org/disabilities/documents/reports/SG_Synthesis_Report_Road_to_Dignity_by_2030.pdf">http://www.un.org/disabilities/documents/reports/SG_Synthesis_Report_Road_to_Dignity_by_2030.pdf</a>, accessed 7 June 2016.</p>
<p><strong>[39]</strong> Ibid.</p>
<p><strong>[40]</strong> UN Sustainable Development Solutions Network, 'Data for Development: An Action Plan to Finance the Data Revolution for Sustainable Development' (10 July 2015) <a href="http://unsdsn.org/wp-content/uploads/2015/04/Data-For-Development-An-Action-Plan-July-2015.pdf">http://unsdsn.org/wp-content/uploads/2015/04/Data-For-Development-An-Action-Plan-July-2015.pdf</a>, accessed 3 June 2016.</p>
<p><strong>[41]</strong> See <strong>[34]</strong>.</p>
<p><strong>[42]</strong> UN Data Revolution Group, 'About the Independent Expert Advisory Group' (6 November 2014) <a href="http://www.undatarevolution.org/about-ieag/">http://www.undatarevolution.org/about-ieag/</a>, accessed 4 June 2016.</p>
<p><strong>[43]</strong> See <strong>[3]</strong>.</p>
<p><strong>[44]</strong> The Partnership has already been established, and it is developing a further framework.</p>
<p><strong>[45]</strong> Organisation for Economic Co-Operation and Development), 'The Organisation for Economic Co-operation and Development (OECD): About' (2016) <a href="http://www.oecd.org/about/">http://www.oecd.org/about/</a>, accessed 2 June 2016.</p>
<p><strong>[46]</strong> Organisation for Economic Co-Operation and Development, 'Strengthening National Statistical Systems to Monitor Global Goals' (2015) <a href="http://www.oecd.org/dac/POST-2015%20P21.pdf">http://www.oecd.org/dac/POST-2015%20P21.pdf</a>, accessed 1 June 2016.</p>
<p><strong>[47]</strong> Ibid.</p>
<p><strong>[48]</strong> OECD Global Science Forum, 'New Data for Understanding the Human Condition: International Perspectives' (February 2013) <a href="http://www.oecd.org/sti/sci-tech/new-data-for-understanding-the-human-condition.pdf">http://www.oecd.org/sti/sci-tech/new-data-for-understanding-the-human-condition.pdf</a>, accessed 2 June 2016.</p>
<p><strong>[49]</strong> The Global Partnership On Sustainable Development Data, 'Who We Are: The Data Ecosystem and the Global Partnership' (2016) <a href="http://www.data4sdgs.org/who-we-are/">http://www.data4sdgs.org/who-we-are/</a>, accessed 5 June 2016.</p>
<p><strong>[50]</strong> World Economic Forum, 'Big Data, Big Impact: New Possibilities for International Development' (22 January 2012) <a href="http://www3.weforum.org/docs/WEF_TC_MFS_BigDataBigImpact_Briefing_2012.pdf">http://www3.weforum.org/docs/WEF_TC_MFS_BigDataBigImpact_Briefing_2012.pdf</a>, accessed 8 June 2016.</p>
<p><strong>[51]</strong> World Economic Forum, 'Our Mission: The World Economic Forum' (12 January 2016) <a href="https://www.weforum.org/about/world-economic-forum/">https://www.weforum.org/about/world-economic-forum/</a>, accessed 7 June 2016.</p>
<p><strong>[52]</strong> See <strong>[50]</strong>.</p>
<p><strong>[53]</strong> Julia Lane, Homepage, <a href="http://www.julialane.org/">http://www.julialane.org/</a>.</p>
<p><strong>[54]</strong> Julia Lane, 'Big Data for Public Policy: The Quadruple Helix' (2016) 8(1) <em>Journal of Policy Analysis and Management</em>, <a href="http://onlinelibrary.wiley.com/doi/10.1002/pam.21921/abstract">DOI:10.1002/pam.21921</a>, accessed 1 June 2016.</p>
<p><strong>[55]</strong> Data-Pop Alliance, 'Data-Pop Alliance: Our Mission' (May 2014) <a href="http://datapopalliance.org/">http://datapopalliance.org/</a>, accessed 1 June 2016.</p>
<p><strong>[56]</strong> See <strong>[10]</strong>.</p>
<p> </p>
<h2 id="8">8. Author Profile</h2>
<p>Meera Manoj is a law student at the Gujarat National Law University, Gandhinagar and has completed her first year. She is passionate about civil rights, feminism, economics in law and anything involving paneer. She aspires to travel the world and build up a vast library, with unparalleled sections on International Law and Archie comics.</p>
<p> </p>
<p>
For more details visit <a href='http://editors.cis-india.org/internet-governance/blog/big-data-governance-frameworks-for-data-revolution-for-sustainable-development'>http://editors.cis-india.org/internet-governance/blog/big-data-governance-frameworks-for-data-revolution-for-sustainable-development</a>
</p>
No publisherMeera ManojDevelopmentBig DataData SystemsInternet GovernanceBig Data for DevelopmentSustainable Development Goals2016-07-05T13:13:32ZBlog Entry