The Centre for Internet and Society
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Artificial Intelligence in India: A Compendium
http://editors.cis-india.org/internet-governance/blog/artificial-intelligence-in-india-a-compendium
<b>Artificial Intelligence (AI) is fast emerging as a key technological paradigm in different sectors across the globe including India.</b>
<p style="text-align: justify;">Towards understanding the state of AI in India, challenges to the development and adoption of the same, and ethical concerns that arise out of the use of AI - CIS is undertaking research to understand and document national developments, discourse, and impact (actual and potential) to ethical and regulatory solutions and compare the same against global developments in the space. As part of this, CIS is creating a compendium of reports that dive into the use of AI across sectors including healthcare, manufacturing, governance, and finance.</p>
<p style="text-align: justify;">Each report seeks to map the present state of AI in the respective sector. In doing so, it explores: <strong>Use</strong>: What is the present use of AI in the sector? What is the narrative and discourse around AI in the sector? <strong>Actors</strong>: Who are the key stakeholders involved in the development, implementation and regulation of AI in the sector? <strong> Impact: </strong>What is the potential and existing impact of AI in the sector? <strong>Regulation</strong>: What are the challenges faced in policy making around AI in the sector?</p>
<p style="text-align: justify;">The reports are as follows:</p>
<ul>
<li>
<div><a href="http://editors.cis-india.org/internet-governance/ai-and-healthcare-report" class="internal-link" title="AI and Healthcare Report">AI and the Healthcare Industry in India</a></div>
</li>
<li>
<div><a class="external-link" href="http://cis-india.org/internet-governance/files/AIManufacturingandServices_Report_02.pdf">AI and the Manufacturing and Services Sector in India</a></div>
</li>
<li><a href="http://editors.cis-india.org/internet-governance/files/ai-in-banking-and-finance" class="internal-link" title="AI in Banking and Finance">AI and the Banking and Finance Industry in India</a>: (19th June 2018 Update: This case study has been modified to remove interview quotes, which are in the process of being confirmed. The link above is the latest draft of the report.)</li><li><a href="http://editors.cis-india.org/internet-governance/ai-and-governance-case-study-pdf" class="internal-link" title="AI and Governance Case Study pdf">AI in the Governance Sector in India<br /></a></li></ul>
<div> </div>
<div> </div>
<hr />
The research is funded by Google India. Comments and feedback are welcome. The reports are drafts.
<p>
For more details visit <a href='http://editors.cis-india.org/internet-governance/blog/artificial-intelligence-in-india-a-compendium'>http://editors.cis-india.org/internet-governance/blog/artificial-intelligence-in-india-a-compendium</a>
</p>
No publisherCentre for Internet & SocietyInternet GovernanceArtificial Intelligence2023-05-09T06:56:25ZBlog EntryRoundtable on AI and Finance in India
http://editors.cis-india.org/internet-governance/events/roundtable-on-ai-and-finance-in-india
<b>Centre for Internet & Society (CIS) will hold a roundtable on artificial intelligence and finance in India on Wednesday, February 7, 2018 in association with HasGeek and the 50p Conference. The roundtable will take place from 2 p.m. to 5 p.m at TERI (The Energy Resources Institute) in Domlur, Bengaluru.</b>
<p style="text-align: justify; ">We invite you all to participate in this roundtable to share and build knowledge about trajectories of AI deployment across sub-sectors of banking in India and the emergent regulatory and public policy concerns.</p>
<p style="text-align: justify; ">The objective of the roundtable is to bring together various actors active across the fields of artificial intelligence, machine learning, cognitive computing, financial technologies,and big data credit scoring and online lending, to discuss pressing public policy issues in regards to the utilisation and implementation of AI in the banking and finance sectors of India.</p>
<p style="text-align: justify; ">These sectors currently find themselves at the early stages of AI adoption. Such technologies are being implemented to facilitate both front-end and back-end processes by a variety of players with the aim of improving the accessibility, customised user engagement, and quality of current financial services. Leading commercial banks in India have all been working to develop and deploy AI technologies either in house or in partnership with small and large-scale tech companies. Such initiatives have seen the deployment of numerous chatbots and humanoid robots for the purposes of customer service. More significant, however, is the use of such technology by banks and fintech actors to facilitate decision making behind the scenes, on a variety of financial issues including but not limited to credit-worthiness, fraud detection, and investments.</p>
<p style="text-align: justify; ">While these sectors are no strangers to the use of big data analytics and similar technologies in aiding with financial decision making and daily operations, the deployment of technologies such as machine learning and natural language processing is still very new. Due to the nascent nature of this phenomenon, little is known about the details of their implications for both producers and consumers. Furthermore, concerns regarding data ownership, liability, and consumer rights have all been raised in light of AI adoption. This roundtable will present us with an opportunity to discuss such issues and begin to fill this knowledge gap.</p>
<p style="text-align: justify; ">For agenda and event brochure <strong><a class="external-link" href="http://cis-india.org/internet-governance/files/ai-and-finance">click here</a>. </strong>For RSVP <a class="external-link" href="https://docs.google.com/forms/d/e/1FAIpQLSd1QFN8a5R3FPPLklDR0XQb1izzGFWzWtAilI5-UNO4EApAFQ/viewform">click here</a>. Read the <a class="external-link" href="http://cis-india.org/internet-governance/files/draft-roundtable-report-on-ai-and-banking">event report here</a></p>
<p>
For more details visit <a href='http://editors.cis-india.org/internet-governance/events/roundtable-on-ai-and-finance-in-india'>http://editors.cis-india.org/internet-governance/events/roundtable-on-ai-and-finance-in-india</a>
</p>
No publishersamanInternet GovernanceEventArtificial Intelligence2018-03-11T14:58:55ZEventRoundtable on A.I. and Manufacturing and Services
http://editors.cis-india.org/internet-governance/events/roundtable-on-ai-and-manufacturing-and-services
<b>The Centre for Internet and Society (CIS), Bangalore is organizing a roundtable on ‘A.I. and Manufacturing and Services’ on the 19th of January, 2018 from 2 to 5 pm at ‘The Energy and Resources Institute’ (TERI) Bangalore. The Roundtable seeks to discuss the various issues and challenges surrounding the implementation of AI and related technologies on manufacturing processes and services.</b>
<p style="text-align: justify; ">Since the Industrial Revolution machines have substituted human labour and helped industries save time and money. This was succeeded by the advent of computers and technology which helped in completing tasks with better speed and accuracy than the human brain. The emergence of machine-learning technology and artificial intelligence has now made machines capable of doing work that was earlier considered to be something that could only be done by humans. From the use of AI in understanding customer shopping trends to its use in making automobiles, AI is becoming more of a norm than an exception. The analytics of how customers shop is now helping companies forecast their manufacturing needs. The synergy of technology and machines i.e. smart manufacturing, not only changes manufacturing and shipping but also improves worker safety. Different forms of smart manufacturing are also starting to come up in India: Wipro and Infosys have launched AI platforms, and the Indian Institute of Science is developing a smart factory with support from Boeing Company and General Electric. Infosys has also released an AI platform, ‘Nia’, which is programmed to forecast revenue and understand customer behaviour.</p>
<p style="text-align: justify; ">The instances of use of machines to substitute human workforce, in some cases, has brought about a sense of worry. Recent trends in factory hiring show that jobs are being lost to automated forms of labour, further evidenced by a report from the research firm HorsesforSources, which predicts that India is set to lose 640,000 low-skilled job positions to automation by the year 2021.The IT sector in India is also under risk from the use of AI. Reports have also found that the rising unemployment in the IT sector has led to increased pressure on labour regulators.</p>
<p style="text-align: justify; ">Although there are some studies that state that the use of AI would bring about a market for people who would need to work along with AI, the FICCI and EY’s 2016 Report on the Future of jobs and its implication on Indian higher education suggests that one of the ways to combat the loss of jobs was reskilling and upskilling the labour force. India has taken the first step towards this by launching the National Skill Development Mission.</p>
<p style="text-align: justify; ">From the use of neural networks to monitor steel plants for packing and shipping groceries, the use of intelligent machines has begun disrupting traditional business models in the industry. However, these advancements raise questions around labour, ethics, liability, and machine-human cooperation. Dialogue and debate are needed to understand how AI is being used in manufacturing, the potential benefits, and challenges of the same, and a way forward that optimizes innovation and protects human rights.</p>
<h2 style="text-align: justify; ">Roundtable Agenda</h2>
<p>Friday 19th January | 2:00 p.m - 5:00 p.m.</p>
<div id="_mcePaste">2:00 - 2:30 Introduction and setting the scene</div>
<div id="_mcePaste">2:30 - 3:30 Discussion on the AI landscape in the manufacturing and services industry:</div>
<div></div>
<ul>
<li>Manner and extent of integration of AI into manufacturing and services</li>
<li>Relevant stakeholders and their roles in implementing AI in manufacturing and services</li>
<li>Future of AI and related technologies in AI in manufacturing and services </li>
<li>Impact on work and labour</li>
</ul>
<p>3:30 - 4:30 Discussion on challenges and solutions towards regulating AI in India:</p>
<ul>
<li>Challenges faced in the conception and implementation of the AI product/ service, and reasons for such challenges.</li>
<li>Regulatory provisions for implementation of AI in the manufacturing and services under the existing laws, and need for reforms.</li>
<li>Challenges posed by AI to existing policy and regulatory frameworks in the Indian as well as the global context, and possible solutions.</li>
</ul>
<p>4.30 - 5.00 Conclusion and way forward</p>
<p>
For more details visit <a href='http://editors.cis-india.org/internet-governance/events/roundtable-on-ai-and-manufacturing-and-services'>http://editors.cis-india.org/internet-governance/events/roundtable-on-ai-and-manufacturing-and-services</a>
</p>
No publisherAdminInternet GovernanceEventArtificial Intelligence2018-01-18T13:44:15ZEventArtificial Intelligence - Literature Review
http://editors.cis-india.org/internet-governance/blog/artificial-intelligence-literature-review
<b>With origins dating back to the 1950s Artificial Intelligence (AI) is not necessarily new. However, interest in AI has been rekindled over the last few years, in no small measure due to the rapid advancement of the technology and its applications to real- world scenarios. In order to create policy in the field, understanding the literature regarding existing legal and regulatory parameters is necessary. This Literature Review is the first in a series of reports that seeks to map the development of AI, both generally and in specific sectors, culminating in a stakeholder analysis and contributions to policy-making. This Review analyses literature on the historical development of the technology, its compositional makeup, sector- specific impacts and solutions and finally, overarching regulatory solutions.</b>
<p>Edited by Amber Sinha and Udbhav Tiwari; Research Assistance by Sidharth Ray</p>
<hr />
<p style="text-align: justify; ">With origins dating back to the 1950s Artificial Intelligence (AI) is not necessarily new. With an increasing number of real-world implications over the last few years, however, interest in AI has been reignited over the last few years.</p>
<p style="text-align: justify; ">The rapid and dynamic pace of development of AI have made it difficult to predict its future path and is enabling it to alter our world in ways we have yet to comprehend. This has resulted in law and policy having stayed one step behind the development of the technology.</p>
<p style="text-align: justify; ">Understanding and analyzing existing literature on AI is a necessary precursor to subsequently recommending policy on the matter. By examining academic articles, policy papers, news articles, and position papers from across the globe, this literature review aims to provide an overview of AI from multiple perspectives.</p>
<p style="text-align: justify; ">The structure taken by the literature review is as follows:</p>
<ol>
<li>Overview of historical development</li>
<li>Definitional and compositional analysis</li>
<li>Ethical & Social, Legal, Economic and Political impact and sector-specific solutions</li>
<li>The regulatory way forward</li>
</ol>
<p style="text-align: justify; ">This literature review is a first step in understanding the existing paradigms and debates around AI before narrowing the focus to more specific applications and subsequently, policy-recommendations.</p>
<p style="text-align: justify; "><a class="external-link" href="http://cis-india.org/internet-governance/files/artificial-intelligence-literature-review"><b>Download the full literature review</b></a></p>
<p>
For more details visit <a href='http://editors.cis-india.org/internet-governance/blog/artificial-intelligence-literature-review'>http://editors.cis-india.org/internet-governance/blog/artificial-intelligence-literature-review</a>
</p>
No publisherShruthi AnandInternet GovernanceArtificial IntelligencePrivacy2017-12-18T15:12:52ZBlog EntryRoundtable on Artificial Intelligence & Healthcare
http://editors.cis-india.org/internet-governance/events/roundtable-on-artificial-intelligence-and-healthcare
<b>Centre for Internet & Society (CIS) is organizing a roundtable on artificial intelligence (AI) and healthcare at 'The Energy and Resources Institute' (TERI) in Bengaluru on November 30, 2017 from 2 p.m. to 5 p.m. The roundtable seeks to discuss the various issues and challenges surrounding the implementation of AI and related technologies in the Indian healthcare sector.</b>
<p style="text-align: justify; ">The Indian healthcare industry, powered by Artificial Intelligence, is moving into a new era of increased innovation and independence. With multiple new healthcare start-ups and large ICT companies such as Microsoft, IBM, and Google offering AI solutions to healthcare challenges in the country, it is evident that AI is attempting to enhance the accessibility, affordability, quality and awareness of healthcare in India. Major target areas sought to be enhanced by use of AI in healthcare include addressing the uneven ratio of skilled doctors to patients and making doctors more efficient at their jobs, delivery of personalized and high-quality healthcare to rural areas, and training doctors and nurses in complex procedures.</p>
<p style="text-align: justify; ">Through the application of machine learning, data mining, natural language processing (NLP), and advanced analytics, AI can help doctors in speedy diagnosis of diseases. AI is also mobilised as ‘smart advisors’ or virtual humans who are capable of making informed decisions by better comprehending data and information through sensing interfaces and analytics, in various forms.</p>
<p style="text-align: justify; ">Some of these forms include ‘customer service agents’ that can expedite simple tasks like appointment scheduling, or more complex decisions like selecting health plan benefits, ‘clinicians’ that can help with primary screening in understaffed rural areas possibly substituting for human labour, and ‘cognitive agents’ that can efficiently manage existing clinical knowledge alongside physicians, nurses and researchers, thereby reducing the cognitive load on humans. AI based Indian healthcare start-ups such as SigTuple, Aindra, Ten3T, Touchkin and many others are offering a range of solutions including automation of medical diagnosis, automated analysis of medical tests, detection and screening of diseases, wearable sensor based medical devices and monitoring equipment, patient management systems, predictive healthcare diagnosis and disease prevention.</p>
<p style="text-align: justify; ">However, AI in healthcare raises many potential concerns, a common one being the lack of comprehensive, representative, interoperable, and clean data - a challenge that is beginning to be addressed through the Electronic Health Records Standards developed by the Ministry of Health and Family Welfare in 2016 by the Ministry of Health and Family Welfare. Other major challenges include patient adoption and the need for personal interaction with doctors, concerns over mass-scale job losses, distrust in technology, and ethical concerns.</p>
<p style="text-align: justify; ">It is imperative to note that implementing AI in healthcare, which is bound to disrupt it, does not imply replacing doctors but augmenting their efforts to create a more efficient healthcare landscape in the country. A harmonious collaboration of man and machine is expected to bring about a meaningful and long-lasting impact and stakeholders should be prepared to adapt to this change and the challenges that come with it.</p>
<hr />
<h3 style="text-align: justify; ">Roundtable Agenda</h3>
<p dir="ltr"><span>Thursday, November 30, 2017, 2:00pm - 5:00pm </span></p>
<p dir="ltr"><span>2:00 - 2:30: Introduction and setting the scene </span></p>
<p dir="ltr"><span>2:30 - 3:30: Discussion on the AI landscape in health in India: </span></p>
<ul>
</ul>
<ul>
<li><span>Manner and extent of integration of AI into products/services of healthcare companies.</span><span></span></li>
<li><span>Relevant stakeholders and their roles in implementing AI into products/services of healthcare companies.</span><span></span></li>
<li><span>Future of AI and related technologies in the healthcare sector</span><span></span></li>
</ul>
<ul>
</ul>
<p dir="ltr" style="text-align: justify; "><span>3:30 - 4:30: Discussion on challenges and solutions towards regulating AI in India: </span></p>
<ul>
<li dir="ltr" style="list-style-type:disc; "><span>Challenges faced in the conception and implementation of the AI product/service, and reasons for such challenges.</span><span></span></li>
<li dir="ltr" style="list-style-type:disc; "><span>Regulatory provisions for implementation of AI in healthcare products/services under the existing laws, and need for reforms.</span><span></span></li>
<li dir="ltr" style="list-style-type:disc; "><span>Challenges posed by AI to existing policy and regulatory frameworks in the Indian as well as the global context, and possible solutions. </span></li>
</ul>
<hr />
<p><a class="external-link" href="http://cis-india.org/internet-governance/files/a-i-and-manufacturing-and-services">Click to download the invite</a></p>
<p>
For more details visit <a href='http://editors.cis-india.org/internet-governance/events/roundtable-on-artificial-intelligence-and-healthcare'>http://editors.cis-india.org/internet-governance/events/roundtable-on-artificial-intelligence-and-healthcare</a>
</p>
No publisherAdminEventArtificial IntelligenceHealthcare2018-01-02T13:49:14ZEventCISxScholars Delhi - Harsh Gupta - FAT ML for Lawyers and Lawmakers (June 29, 5:30 pm)
http://editors.cis-india.org/raw/cisxscholars-harsh-gupta-machine-learning-for-lawyers-and-lawmakers-20170629
<b>We are proud to announce that Harsh Gupta will discuss "FAT ML (Fairness, Accountability, and Transparency in Machine Learning) for Lawyers and Lawmakers" at the CIS office in Delhi on Thursday, June 29, at 5:30 pm. This will be a two and half hour session: beginning with a 45 minute talk, followed by 15 minute break, another talk for 45 minutes, and then a discussion session. Please RSVP if you are joining us: <raw@cis-india.org>. </b>
<p> </p>
<p><em>CISxScholars are informal events organised by CIS for presentation, discussion, and exchange of academic research and policy analysis.</em></p>
<hr />
<h3><strong>FAT ML (Fairness, Accountability, and Transparency in Machine Learning) for Lawyers and Lawmakers</strong></h3>
<p>From tagging people in photos to determining risk of loan defaults, use of data based tools is affecting more and areas of our lives. In some areas there have been very successful applications of such tools, in others areas they has been found to not only reflect the existing bias and discrimination found in today's society but also exaggerate it.</p>
<h3><strong>Harsh Gupta</strong></h3>
<p>Harsh Gupta is a recent graduate from IIT Kharagpur with B.Sc and M.Sc in Mathematics and Computing and will be joining JP Morgan and Chase as a data scientist. He completed his master's thesis in "Discrimination Aware Machine Learning". He was also an intern at The Center for Internet and Society during summer of 2016.</p>
<p> </p>
<p>
For more details visit <a href='http://editors.cis-india.org/raw/cisxscholars-harsh-gupta-machine-learning-for-lawyers-and-lawmakers-20170629'>http://editors.cis-india.org/raw/cisxscholars-harsh-gupta-machine-learning-for-lawyers-and-lawmakers-20170629</a>
</p>
No publishersumandroFAT MLCISxScholarsBig DataMachine LearningResearchers at WorkEventArtificial Intelligence2017-06-27T09:16:48ZEventBig Data in India: Benefits, Harms, and Human Rights - Workshop Report
http://editors.cis-india.org/internet-governance/big-data-in-india-benefits-harms-and-human-rights-a-report
<b>The Centre for Internet and Society held a one-day workshop on “Big Data in India: Benefits, Harms and Human Rights” at India Habitat Centre, New Delhi on the 1st of October, 2016. This report is a compilation of the the issues discussed, ideas exchanged and challenges recognized during the workshop. The objective of the workshop was to discuss aspects of big data technologies in terms of harms, opportunities and human rights. The discussion was designed around an extensive study of current and potential future uses of big data for governance in India, that CIS has undertaken over the last year with support from the MacArthur Foundation.</b>
<p> </p>
<p><strong>Contents</strong></p>
<p><a href="#1"><strong>Big Data: Definitions and Global South Perspectives</strong></a></p>
<p><a href="#2"><strong>Aadhaar as Big Data</strong></a></p>
<p><a href="#3"><strong>Seeding</strong></a></p>
<p><a href="#4"><strong>Aadhaar and Data Security</strong></a></p>
<p><a href="#5"><strong>Aadhaar’s Relational Arrangement with Big Data Scheme</strong></a></p>
<p><a href="#6"><strong>The Myths surrounding Aadhaar</strong></a></p>
<p><a href="#7"><strong>IndiaStack and FinTech Apps</strong></a></p>
<p><a href="#8"><strong>Problems with UID</strong></a></p>
<hr />
<h2 id="1">Big Data: Definitions and Global South Perspectives</h2>
<div style="text-align: justify;" dir="ltr"> </div>
<p style="text-align: justify;" dir="ltr">“Big Data” has been defined by multiple scholars till date. The first consideration at the workshop was to discuss various definitions of big data, and also to understand what could be considered Big Data in terms of governance, especially in the absence of academic consensus. One of the most basic ways to define it, as given by the National Institute of Standards and Technology, USA, is to take it to be the data that is beyond the computational capacity of current systems. This definition has been accepted by the UIDAI of India. Another participant pointed out that Big Data is not only indicative of size, but rather the nature of data which is unstructured, and continuously flowing. The Gartner definition of Big Data relies on the three Vs i.e. Volume (size), Velocity (infinite number of ways in which data is being continuously collected) and Variety (the number of ways in which data can be collected in rows and columns).</p>
<p style="text-align: justify;" dir="ltr">The presentation also looked at ways in which Big Data is different from traditional data. It was pointed out that it can accommodate diverse unstructured datasets, and it is ‘relational’ i.e. it needs the presence of common field(s) across datasets which allows these fields to be conjoined. For e.g., the UID in India is being linked to many different datasets, and they don’t constitute Big Data separately, but do so together. An increasingly popular definition is to define data as “Big Data” based on what can be achieved through it. It has been described by authors as the ability to harness new kinds of insight which can inform decision making. It was pointed out that CIS does not subscribe to any particular definition, and is still in the process of coming up with a comprehensive definition of Big Data.</p>
<p style="text-align: justify;" dir="ltr">Further, discussion touched upon the approach to Big Data in the Global South. It was pointed out that most discussions about Big Data in the Global South are about the kind of value that it can have, the ways in which it can change our society. The Global North, on the other hand, has moved on to discussing the ethics and privacy issues associated with Big Data.</p>
<p style="text-align: justify;" dir="ltr">After this, the presentation focussed on case studies surrounding key Central Government initiatives and projects like Aadhaar, Predictive Policing, and Financial Technology (FinTech).</p>
<h2 id="2">Aadhaar as Big Data</h2>
<p style="text-align: justify;" dir="ltr">In presenting CIS’ case study on Aadhaar, it was pointed out that initially, Aadhaar, with its enrollment dataset was by itself being seen as Big Data. However, upon careful consideration in light of definitions discussed above, it can be seen as something that enables Big Data. The different e-governance projects within Digital India, along with Aadhaar, constitute Big Data. The case study discussed the Big Data implications of Aadhaar, and in particular looked at a ‘cradle to grave’ identity mapping through various e-government projects and the datafication of various transaction generated data.</p>
<h2 id="3">Seeding</h2>
<p style="text-align: justify;" dir="ltr">Any digital identity like Aadhaar typically has three features: 1. Identification i.e. a number or card used to identify yourself; 2. Authentication, which is based on your number or card and any other digital attributes that you might have; 3. Authorisation: As bearers of the digital identity, we can authorise the service providers to take some steps on our behalf. The case study discussed ‘seeding’ which enables the Big Data aspects of Digital India. In the process of seeding, different government databases can be seeded with the UID number using a platform called Ginger. Due to this, other databases can be connected to UIDAI, and through it, data from other databases can be queried by using your Aadhaar identity itself. This is an example of relationality, where fractured data is being brought together. At the moment, it is not clear whether this access by UIDAI means that an actual physical copy of such data from various sources will be transferred to UIDAI’s servers or if they will just access it through internet, but the data remains on the host government agency’s server. An example of even private parties becoming a part of this infrastructure was raised by a participant when it was pointed out that Reliance Jio is now asking for fingerprints. This can then be connected to the relational infrastructure being created by UIDAI. The discussion then focused on how such a structure will function, where it was mentioned that as of now, it cannot be said with certainty that UIDAI will be the agency managing this relational infrastructure in the long run, even though it is the one building it.</p>
<h2 id="4">Aadhaar and Data Security</h2>
<p style="text-align: justify;" dir="ltr">This case study also dealt with the sheer lack of data protection legislation in India except for S.43A of the IT Act. The section does not provide adequate protection as the constitutionality of the rules and regulations under S.43A is ambivalent. More importantly, it only refers to private bodies. Hence, any seeding which is being done by the government is outside the scope of data protection legislation. Thus, at the moment, no legal framework covers the processes and the structures being used for datasets. Due to the inapplicability of S.43A to public bodies, questions were raised as to the existence of a comprehensive data protection policy for government institutions. Participants answered the question in the negative. They pointed out that if any government department starts collecting data, they develop their own privacy policy. There are no set guidelines for such policies and they do not address concerns related to consent, data minimisation and purpose limitation at all. Questions were also raised about the access and control over Big Data with government institutions. A tentative answer from a participant was that such data will remain under the control of the domain specific government ministry or department, for e.g. MNREGA data with the Ministry of Rural Development, because the focus is not on data centralisation but rather on data linking. As long as such fractured data is linked and there is an agency that is responsible to link them, this data can be brought together. Such data is primarily for government agencies. But the government is opening up certain aspects of the data present with it for public consumption for research and entrepreneurial purposes.The UIDAI provides you access to your own data after paying a minimal fee. The procedure for such access is still developing.</p>
<h2 id="5">Aadhaar’s Relational Arrangement with Big Data Scheme</h2>
<p style="text-align: justify;" dir="ltr">The various Digital India schemes brought in by the government were elucidated during the workshop. It was pointed out that these schemes extend to myriad aspects of a citizen’s daily life and cover all the essential public services like health, education etc. This makes Aadhaar imperative even though the Supreme Court has observed that it is not mandatory for every citizen to have a unique identity number. The benefits of such identity mapping and the ecosystem being generated by it was also enumerated during the discourse. But the complete absence of any data ethics or data confidentiality principles make us unaware of the costs at which these benefits are being conferred on us. Apart from surveillance concerns, the knowledge gap being created between the citizens and the government was also flagged. Three main benefits touted to be provided by Aadhaar were then analysed. The first is the efficient delivery of services. This appears to be an overblown claim as the Aadhaar specific digitisation and automation does not affect the way in which employment will be provided to citizens through MNREGA or how wage payment delays will be overcome. These are administrative problems that Aadhaar and associated technologies cannot solve. The second is convenience to the citizens. The fallacies in this assertion were also brought out and identified. Before the Aadhaar scheme was rolled in, ration cards were issued based on certain exclusion and inclusion criteria.. The exclusion and inclusion criteria remain the same while another hurdle in the form of Aadhaar has been created. As India is still lacking in supporting infrastructure such as electricity, server connectivity among other things, Aadhaar is acting as a barrier rather than making it convenient for citizens to enroll in such schemes.The third benefit is fraud management. Here, a participant pointed out that this benefit was due to digitisation in the form of GPS chips in food delivery trucks and electronic payment and not the relational nature of Aadhaar. Aadhaar is only concerned with the linking up or relational part. About deduplication, it was pointed out how various government agencies have tackled it quite successfully by using technology different from biometrics which is unreliable at the best of times.</p>
<h2 id="6">The Myths surrounding Aadhaar</h2>
<p style="text-align: justify;" dir="ltr">The discussion also reflected on the fact that Aadhaar is often considered to be a panacea that subsumes all kinds of technologies to tackle leakages. However, this does not take into account the fact that leakages happen in many ways. A system should have been built to tackle those specific kinds of leakages, but the focus is solely on Aadhaar as the cure for all. Notably, participants who have been a part of the government pointed out how this myth is misleading and should instead be seen as the first step towards a more digitally enhanced country which is combining different technologies through one medium.</p>
<h2 id="7">IndiaStack and FinTech Apps</h2>
<h3 id="71">What is India Stack?</h3>
<p style="text-align: justify;" dir="ltr">The focus then shifted to another extremely important Big Data project, India Stack, being conceptualised and developed by a team of private developers called iStack, for the NPCI. It builds on the UID project, Jan Dhan Yojana and mobile services trinity to propagate and develop a cashless, presence-less, paperless and granular consent layer based on UID infrastructure to digitise India.</p>
<p style="text-align: justify;" dir="ltr">A participant pointed out that the idea of India Stack is to use UID as a platform and keep stacking things on it, such that more and more applications are developed. This in turn will help us to move from being a ‘data poor’ country to a ‘data rich’ one. The economic benefits of this data though as evidenced from the TAGUP report - a report about the creation of National Information Utilities to manage the data that is present with the government - is for the corporations and not the common man. The TAGUP report openly talks about privatisation of data.</p>
<h3 id="72">Problems with India Stack</h3>
<p style="text-align: justify;" dir="ltr">The granular consent layer of India Stack hasn’t been developed yet but they have proposed to base it on MIT Media Lab’s OpenPDS system. The idea being that, on the basis of the choices made by the concerned person, access to a person’s personal information may be granted to an agency like a bank. What is more revolutionary is that India Stack might even revoke this access if the concerned person expresses a wish to do so or the surrounding circumstances signal to India Stack that it will be prudent to do so. It should be pointed out that the the technology required for OpenPDS is extremely complex and is not available in India. Moreover, it’s not clear how this system would work. Apart from this, even the paperless layer has its faults and has been criticised by many since its inception, because an actual government signed and stamped paper has been the basis of a claim.. In the paperless system, you are provided a Digilocker in which all your papers are stored electronically, on the basis of your UID number. However, it was brought to light that this doesn’t take into account those who either do not want a Digilocker or UID number or cases where they do not have access to their digital records. How in such cases will people make claims?</p>
<h3 id="73">A Digital Post-Dated Cheque: It’s Ramifications</h3>
<p style="text-align: justify;" dir="ltr">A key change that FinTech apps and the surrounding ecosystem want to make is to create a digital post-dated cheque so as to allow individuals to get loans from their mobiles especially in remote areas. This will potentially cut out the need to construct new banks, thus reducing the capital expenditure , while at the same time allowing the credit services to grow. The direct transfer of money between UID numbers without the involvement of banks is a step to further help this ecosystem grow. Once an individual consents to such a system, however, automatic transfer of money from one’s bank accounts will be affected, regardless of the reason for payment. This is different from auto debt deductions done by banks presently, as in the present system banks have other forms of collateral as well. The automatic deduction now is only affected if these other forms are defaulted upon. There is no knowledge as to whether this consent will be reversible or irreversible. As Jan Dhan Yojana accounts are zero balance accounts, the account holder will be bled dry. The implication of schemes such as “Loan in under 8 minutes” were also discussed. The advantage of such schemes is that transaction costs are reduced.The financial institution can thus grant loans for the minimum amount without any additional enquiries. It was pointed out that this new system is based on living on future income much like the US housing bubble crash. Interestingly, in Public Distribution Systems, biometrics are insisted upon even though it disrupts the system. This can be seen as a part of the larger infrastructure to ensure that digital post-dated cheques become a success.</p>
<h3 id="74">The Role of FinTech Apps</h3>
<p style="text-align: justify;" dir="ltr">FinTech ‘apps’ are being presented with the aim of propagating financial inclusion. The Technology Advisory Group for Unique Projects report stated that as managing such information sources is a big task, just like electricity utilities, a National Information Utilities (NIU) should be set up for data sources. These NIUs as per the report will follow a fee based model where they will be charging for their services for government schemes. The report identified two key NIUs namely the National Payments Corporation of India (NPCI) and the Goods and Services Tax Network (GSTN). The key usage that FinTech applications will serve is credit scoring. The traditional credit scoring data sources only comprised a thin file of records for an individual, but the data that FinTech apps collect - a person’s UID number, mobile number. and bank account number all linked up, allow for a far more comprehensive credit rating. Government departments are willing to share this data with FinTech apps as they are getting analysis in return. Thus, by using UID and the varied data sources that have been linked together by UID, a ‘thick file’ is now being created by FinTech apps. Banking apps have not yet gone down the route of FinTech apps to utilise Big Data for credit scoring purposes.</p>
<p style="text-align: justify;" dir="ltr"> </p>
<p style="text-align: justify;" dir="ltr">The two main problems with such apps is that there is no uniform way of credit scoring. This distorts the rate at which a person has to pay interest. The consent layer adds another layer of complication as refusal to share mobile data with a FinTech app may lead to the app declaring one to be a risky investment thus, subjecting that individual to a higher rate of interest .</p>
<div style="text-align: justify;" dir="ltr"> </div>
<h3 id="75">Regulation of FinTech Apps and the UID Infrastructure</h3>
<p style="text-align: justify;" dir="ltr"> India Stack and the applications that are being built on it, generate a lot of transaction metadata that is very intimate in nature. The privacy aspects of the UID legislation doesn't cover such data. The granular consent layer which has been touted to cover this still has to come into existence. Also, Big Data is based on sharing and linking of data. Here, privacy concerns and Big Data objectives clash. Big Data by its very nature challenges privacy principles like data minimisation and purpose limitation.The need for regulation to cover the various new apps and infrastructure which are being developed was pointed out.</p>
<h2 id="8">Problems with UID</h2>
<p style="text-align: justify;" dir="ltr">It has been observed that any problem present with Aadhaar is usually labelled as a teething problem, it’s claimed that it will be solved in the next 10 years. But, this begs the question - why is the system online right now?</p>
<div style="text-align: justify;" dir="ltr"> </div>
<p style="text-align: justify;" dir="ltr">Aadhaar is essentially a new data condition and a new exclusion or inclusion criteria. Data exclusion modalities as observed in Rajasthan after the introduction of biometric Point of Service (POS) machines at ration shops was found to be 45% of the population availing PDS services. This number also includes those who were excluded from the database by being included in the wrong dataset. There is no information present to tell us how many actual duplicates and how many genuine ration card holders were weeded out/excluded by POS.</p>
<div style="text-align: justify;" dir="ltr"> </div>
<p style="text-align: justify;" dir="ltr">It was also mentioned that any attempt to question Aadhaar is considered to be an attempt to go back to the manual system and this binary thinking needs to change. Big Data has the potential to benefit people, as has been evidenced by the scholarship and pension portals. However, Big Data’s problems arise in systems like PDS, where there is centralised exclusion at the level of the cloud. Moreover, the quantity problem present in the PDS and MNREGA systems persists. There is still the possibility of getting lesser grains and salary even with analysis of biometrics, hence proving that there are better technologies to tackle these problems. Presently, the accountability mechanisms are being weakened as the poor don’t know where to go to for redressal. Moreover, the mechanisms to check whether the people excluded are duplicates or not is not there. At the time of UID enrollment, out of 90 crores, 9 crore were rejected. There was no feedback or follow-up mechanism to figure out why are people being rejected. It was just assumed that they might have been duplicates.</p>
<div style="text-align: justify;" dir="ltr"> </div>
<p style="text-align: justify;" dir="ltr">Another problem is the rolling out of software without checking for inefficiencies or problems at a beta testing phase. The control of developers over this software, is so massive that it can be changed so easily without any accountability.. The decision making components of the software are all proprietary like in the the de-duplication algorithm being used by the UIDAI. Thus, this leads to a loss of accountability because the system itself is in flux, none of it is present in public domain and there are no means to analyse it in a transparent fashion..</p>
<div style="text-align: justify;" dir="ltr"> </div>
<p style="text-align: justify;" dir="ltr">These schemes are also being pushed through due to database politics. On a field study of NPR of citizens, another Big Data scheme, it was found that you are assumed to be an alien if you did not have the documents to prove that you are a citizen. Hence, unless you fulfill certain conditions of a database, you are excluded and are not eligible for the benefits that being on the database afford you.</p>
<div style="text-align: justify;" dir="ltr"> </div>
<p style="text-align: justify;" dir="ltr">Why is the private sector pushing for UIDAI and the surrounding ecosystem?</p>
<p style="text-align: justify;" dir="ltr">Financial institutions stand to gain from encouraging the UID as it encourages the credit culture and reduces transaction costs.. Another advantage for the private sector is perhaps the more obvious one, that is allows for efficient marketing of products and services..</p>
<div style="text-align: justify;" dir="ltr"> </div>
<p style="text-align: justify;" dir="ltr">The above mentioned fears and challenges were actually observed on the ground and the same was shown through the medium of a case study in West Bengal on the smart meters being installed there by the state electricity utility. While the data coming in from these smart meters is being used to ensure that a more efficient system is developed,it is also being used as a surrogate for income mapping on the basis of electricity bills being paid. This helps companies profile neighbourhoods. The technical officer who first receives that data has complete control over it and he can easily misuse the data. This case study again shows that instruments like Aadhaar and India Stack are limited in their application and aren’t the panacea that they are portrayed to be.</p>
<div style="text-align: justify;" dir="ltr"> </div>
<p style="text-align: justify;" dir="ltr">A participant pointed out that in the light of the above discussions, the aim appears to be to get all kinds of data, through any source, and once you have gotten the UID, you link all of this data to the UID number, and then use it in all the corporate schemes that are being started. Most of the problems associated with Big Data are being described as teething problems. The India Stack and FinTech scheme is coming in when we already know about the problems being faced by UID. The same problems will be faced by India Stack as well.</p>
<div style="text-align: justify;" dir="ltr"> </div>
<p style="text-align: justify;" dir="ltr">Can you opt out of the Aadhaar system and the surrounding ecosystem?</p>
<div style="text-align: justify;" dir="ltr"> </div>
<p style="text-align: justify;" dir="ltr">The discussion then turned towards whether there can be voluntary opting out from Aadhaar. It was pointed out that the government has stated that you cannot opt out of Aadhaar. Further, the privacy principles in the UIDAI bill are ambiguously worded where individuals only have recourse for basic things like correction of your personal information. The enforcement mechanism present in the UIDAI Act is also severely deficient. There is no notification procedure if a data breach occurs. . The appellate body ‘Cyber Appellate Tribunal’ has not been set up in three years.</p>
<div style="text-align: justify;" dir="ltr"> </div>
<p style="text-align: justify;" dir="ltr">CCTNS: Big Data and its Predictive Uses</p>
<div style="text-align: justify;" dir="ltr"> </div>
<p style="text-align: justify;" dir="ltr">What is Predictive Policing?</p>
<p style="text-align: justify;" dir="ltr">The next big Big Data case study was on the Crime and Criminal Tracking Network & Systems (CCTNS). Originally it was supposed to be a digitisation and interconnection scheme where police records would be digitised and police stations across the length and breadth of the country would be interconnected. But, in the last few years some police departments of states like Chandigarh, Delhi and Jharkhand have mooted the idea of moving on to predictive policing techniques. It envisages the use of existing statistical and actuarial techniques along with many other tropes of data to do so. It works in four ways: 1. By predicting the place and time where crimes might occur; 2. To predict potential future offenders; 3. To create profiles of past crimes in order to predict future crimes; 4. Predicting groups of individuals who are likely to be victims of future crimes.</p>
<div style="text-align: justify;" dir="ltr"> </div>
<p style="text-align: justify;" dir="ltr">How is Predictive Policing done?</p>
<p style="text-align: justify;" dir="ltr">To achieve this, the following process is followed: 1. Data collection from various sources which includes structured data like FIRs and unstructured data like call detail records, neighbourhood data, crime seasonal patterns etc. 2. Analysis by using theories like the near repeat theory, regression models on the basis of risk factors etc. 3. Intervention</p>
<div style="text-align: justify;" dir="ltr"> </div>
<div style="text-align: justify;" dir="ltr"> </div>
<p style="text-align: justify;" dir="ltr">Flaws in Predictive Policing and questions of bias</p>
<p style="text-align: justify;" dir="ltr">An obvious weak point in the system is that if the initial data going into the system is wrong or biased, the analysis will also be wrong. Efforts are being made to detect such biases. An important way to do so will be by building data collection practices into the system that protect its accuracy. The historical data being entered into the system is carrying on the prejudices inherited from the British Raj and biases based on religion, caste, socio-economic background etc.</p>
<div style="text-align: justify;" dir="ltr"> </div>
<p style="text-align: justify;" dir="ltr">One participant brought about the issue of data digitization in police stations, and the impact of this haphazard, unreliable data on a Big Data system. This coupled with paucity of data is bound to lead to arbitrary results. An effective example was that of black neighbourhoods in the USA. These are considered problematic and thus they are policed more, leading to a higher crime rate as they are arrested for doing things that white people in an affluent neighbourhood get away with. This in turn further perpetuates the crime rate and it becomes a self-fulfilling prophecy. In India, such a phenomenon might easily develop in the case of migrants, de-notified tribes, Muslims etc. A counter-view on bias and discrimination was offered here. One participant pointed out that problems with haphazard or poor quality of data is not a colossal issue as private companies are willing to fill this void and are actually doing so in exchange for access to this raw data. It was also pointed out how bias by itself is being used as an all encompassing term. There are multiplicities of biases and while analysing the data, care should be taken to keep it in mind that one person’s bias and analysis might and usually does differ from another. Even after a computer has analysed the data, the data still falls into human hands for implementation.</p>
<p style="text-align: justify;" dir="ltr">The issue of such databases being used to target particular communities on the basis of religion, race, caste, ethnicity among other parameters was raised. Questions about control and analysis of data were also discussed, i.e. whether it will be top-down with data analysis being done in state capitals or will this analysis be done at village and thana levels as well too. It was discussed as topointed out how this could play a major role in the success and possible persecutory treatment of citizens, as the policemen at both these levels will have different perceptions of what the data is saying. . It was further pointed out, that at the moment, there’s no clarity on the mode of implementation of Big Data policing systems. Police in the USA have been seen to rely on Big Data so much that they have been seen to become ‘data myopic’. For those who are on the bad side of Big Data, in the Indian context, laws like preventive detention can be heavily misused.There’s a very high chance that predictive policing due to the inherent biases in the system and the prejudices and inefficiency of the legal system will further suppress the already targeted sections of the society. A counterpoint was raised and it was suggested that contrary to our fears, CCTNS might lead to changes in our understanding and help us to overcome longstanding biases.</p>
<p style="text-align: justify;" dir="ltr">Open Knowledge Architecture as a solution to Big Data biases?</p>
<p style="text-align: justify;" dir="ltr">The conference then mulled over the use of ‘Open Knowledge’ architecture to see whether it can provide the solution to rid Big Data of its biases and inaccuracies if enough eyes are there. It was pointed out that Open Knowledge itself can’t provide foolproof protection against these biases as the people who make up the eyes themselves are predominantly male belonging to the affluent sections of the society and they themselves suffer from these biases.</p>
<p style="text-align: justify;" dir="ltr">Who exactly is Big Data supposed to serve?</p>
<p style="text-align: justify;" dir="ltr">The discussion also looked at questions such as who is this data for? Janata Information System (JIS), is a concept developed by MKSS where the data collected and generated by the government is taken to be for the common citizens. For e.g. MNREGA data should be used to serve the purposes of the labourers. The raw data as is available at the moment, usually cannot be used by the common man as it is so vast and full of information that is not useful for them at all. It was pointed out that while using Big Data for policy planning purposes, the actual string of information that turned out to be needed was very little but the task of unravelling this data for civil society purposes is humongous. By presenting the data in the right manner, the individual can be empowered. The importance of data presentation was also flagged. It was agreed upon that the content of the data should be for the labourer and not a MNC, as the MNC has the capability to utilise the raw data on it’s own regardless.</p>
<p style="text-align: justify;" dir="ltr">Concerns about Big Data usage</p>
<ol><li style="list-style-type: decimal;" dir="ltr">
<p style="text-align: justify;" dir="ltr">Participants pointed out that privacy concerns are usually brushed under the table due to a belief that the law is sufficient or that the privacy battle has already been lost. </p>
</li><li style="list-style-type: decimal;" dir="ltr">
<p style="text-align: justify;" dir="ltr">In the absence of knowledge of domain and context, Big Data analysis is quite limited. Big Data’s accuracy and potential to solve problems needs to be factually backed.</p>
</li><li style="list-style-type: decimal;" dir="ltr">
<p style="text-align: justify;" dir="ltr">The narrative of Big Data often rests on the assumption that descriptive statistics take over inferential statistics, thus eliminating the need for domain specific knowledge. It is claimed that the data is so big that it will describe everything that we need to know.</p>
</li><li style="list-style-type: decimal;" dir="ltr">
<p style="text-align: justify;" dir="ltr">Big Data is creating a shift from a deductive model of scientific rigour to an inductive one. In response to this, a participant offered the idea that troves of good data allow us to make informed questions on the basis of which the deductive model will be formed. A hybrid approach combining both deductive and inductive might serve us best.</p>
</li><li style="list-style-type: decimal;" dir="ltr">
<p style="text-align: justify;" dir="ltr">The need to collect the right data in the correct format, in the right place was also expressed.</p>
</li></ol>
<div style="text-align: justify;" dir="ltr"> </div>
<p style="text-align: justify;" dir="ltr">Potential Research Questions & Participants’ Areas of Research</p>
<p style="text-align: justify;" dir="ltr">Following this discussion, participants brainstormed to come up with potential areas of research and research questions. They have been captured below:</p>
<div style="text-align: justify;" dir="ltr"> </div>
<p style="text-align: justify;" dir="ltr">Big Data, Aadhaar and India Stack:</p>
<div style="text-align: justify;" dir="ltr"> </div>
<ol><li style="list-style-type: decimal;" dir="ltr">
<p style="text-align: justify;" dir="ltr">Has Aadhaar been able to tackle illegal ways of claiming services or are local negotiations and other methods still prevalent?</p>
</li><li style="list-style-type: decimal;" dir="ltr">
<p style="text-align: justify;" dir="ltr">Is the consent layer of India Stack being developed in a way that provides an opportunity to the UID user to give informed consent? The OpenPDS and its counterpart in the EU i.e. the My Data Structure were designed for countries with strong privacy laws. Importantly, they were meant for information shared on social media and not for an individual’s health or credit history. India is using it in a completely different sphere without strong data protection laws. What were the granular consent layer structures present in the West designed for and what were they supposed to protect?</p>
</li><li style="list-style-type: decimal;" dir="ltr">
<p style="text-align: justify;" dir="ltr">The question of ownership of data needs to be studied especially in context of a globalised world where MNCs are collecting copious amounts of data of Indian citizens. What is the interaction of private parties in this regard?</p>
</li></ol>
<div style="text-align: justify;" dir="ltr"> </div>
<p style="text-align: justify;" dir="ltr">Big Data and Predictive Policing:</p>
<div style="text-align: justify;" dir="ltr"> </div>
<ol><li style="list-style-type: decimal;" dir="ltr">
<p style="text-align: justify;" dir="ltr">How are inequalities being created through the Big Data systems? Lessons should be taken from the Western experience with the advent of predictive policing and other big data techniques - they tend to lead to perpetuation of the current biases which are already ingrained in the system.</p>
</li><li style="list-style-type: decimal;" dir="ltr">
<p style="text-align: justify;" dir="ltr">It was also pointed out how while studying these topics and anything related to technology generally, we become aware of a divide that is present between the computational sciences and social sciences. This divide needs to be erased if Big Data or any kind of data is to be used efficiently. There should be a cross-pollination between different groups of academics. An example of this can be seen to be the ‘computational social sciences departments’ that have been coming up in the last 3-4 years.</p>
</li><li style="list-style-type: decimal;" dir="ltr">
<p style="text-align: justify;" dir="ltr">Why are so many interim promises made by Big Data failing? A study of this phenomenon needs to be done from a social science perspective. This will allow one to look at it from a different angle.</p>
</li></ol>
<div style="text-align: justify;" dir="ltr"> </div>
<p style="text-align: justify;" dir="ltr">Studying Big Data:</p>
<div style="text-align: justify;" dir="ltr"> </div>
<ol><li style="list-style-type: decimal;" dir="ltr">
<p style="text-align: justify;" dir="ltr">What is the historical context of the terms of reference being used for Big Data? The current Big Data debate in India is based on parameters set by the West. For better understanding of Big Data, it was suggested that P.C. Mahalanobis’ experience while conducting the Indian census, (which was the Big Data of that time) can be looked at to get a historical perspective on Big Data. This comparison might allow us to discover questions that are important in the Indian context. It was also suggested that rather than using ‘Big Data’ as a catchphrase to describe these new technological innovations, we need to be more discerning.</p>
</li><li style="list-style-type: decimal;" dir="ltr">
<p style="text-align: justify;" dir="ltr">What are the ideological aspects that must be considered while studying Big Data? What does the dialectical promise of technology mean? It was contended that every time there is a shift in technology, the zeitgeist of that period is extremely excited and there are claims that it will solve everything. There’s a need to study this dialectical promise and the social promise surrounding it.</p>
</li><li style="list-style-type: decimal;" dir="ltr">
<p style="text-align: justify;" dir="ltr">Apart from the legitimate fears that Big Data might lead to exclusion, what are the possibilities in which it improve inclusion too?</p>
</li><li style="list-style-type: decimal;" dir="ltr">
<p style="text-align: justify;" dir="ltr">The diminishing barrier between the public and private self, which is a tangent to the larger public-private debate was mentioned.</p>
</li><li style="list-style-type: decimal;" dir="ltr">
<p style="text-align: justify;" dir="ltr">How does one distinguish between technology failure and process failure while studying Big Data? </p>
</li></ol>
<div style="text-align: justify;" dir="ltr"> </div>
<div style="text-align: justify;" dir="ltr"> </div>
<div style="text-align: justify;" dir="ltr"> </div>
<p style="text-align: justify;" dir="ltr">Big Data: A Friend?</p>
<p style="text-align: justify;" dir="ltr">In the concluding session, the fact that the Big Data moment cannot be wished away was acknowledged. The use of analytics and predictive modelling by the private sector is now commonplace and India has made a move towards a database state through UID and Digital India. The need for a nuanced debate, that does away with the false equivalence of being either a Big Data enthusiast or a luddite is crucial.</p>
<div style="text-align: justify;" dir="ltr"> </div>
<p style="text-align: justify;" dir="ltr">A participant offered two approaches to solving a Big Data problem. The first was the Big Data due process framework which states that if a decision has been taken that impacts the rights of a citizen, it needs to be cross examined. The efficacy and practicality of such an approach is still not clear. The second, slightly paternalistic in nature, was the approach where Big Data problems would be solved at the data science level itself. This is much like the affirmative algorithmic approach which says that if in a particular dataset, the data for the minority community is not available then it should be artificially introduced in the dataset. It was also suggested that carefully calibrated free market competition can be used to regulate Big Data. For e.g. a private personal wallet company that charges higher, but does not share your data at all can be an example of such competition. </p>
<div style="text-align: justify;" dir="ltr"> </div>
<p style="text-align: justify;" dir="ltr">Another important observation was the need to understand Big Data in a Global South context and account for unique challenges that arise. While the convenience of Big Data is promising, its actual manifestation depends on externalities like connectivity, accurate and adequate data etc that must be studied in the Global South.</p>
<div style="text-align: justify;" dir="ltr"> </div>
<p style="text-align: justify;" dir="ltr">While the promises of Big Data are encouraging, it is also important to examine its impacts and its interaction with people's rights. Regulatory solutions to mitigate the harms of big data while also reaping its benefits need to evolve.</p>
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<p><span id="docs-internal-guid-90fa226f-6157-27d9-30cd-050bdc280875"></span></p>
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For more details visit <a href='http://editors.cis-india.org/internet-governance/big-data-in-india-benefits-harms-and-human-rights-a-report'>http://editors.cis-india.org/internet-governance/big-data-in-india-benefits-harms-and-human-rights-a-report</a>
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No publisherVidushi Marda, Akash Deep Singh and Geethanjali JujjavarapuHuman RightsUIDBig DataPrivacyArtificial IntelligenceInternet GovernanceMachine LearningFeaturedDigital IndiaAadhaarInformation TechnologyE-Governance2016-11-18T12:58:19ZBlog EntryA.I. Hype Cycles and Artistic Subversions
http://editors.cis-india.org/raw/ai-hype-cycles-and-artistic-subversions
<b>Gene Kogan will give a talk on "A.I. hype cycles and artistic subversions" on Friday, January 22, 2016 at the Centre for Internet and Society office, 6 pm - 8 pm.</b>
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<p><img src="http://www.genekogan.com/images/style-transfer/ml_egypt_crab_maps.jpg" alt="Gene Kogan - Style Transfer - Mona Lisa" width="800" /></p>
<h6>Mona Lisa restyled by Egyptian hieroglyphs, the Crab Nebula, and Google Maps. <a href="http://www.genekogan.com/works/style-transfer.html">Style Transfer</a>. Gene Kogan.</h6>
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<p style="text-align: justify;">Recent years have seen a resurgence of popular interest in machine learning and artificial intelligence, as emerging methods have set new scientific benchmarks and introduced classes of neural networks capable of imitating human behavior, among other impressive feats. More importantly, the study of these algorithms is rapidly crossing over into mainstream culture and industry as AI applications begin to inhabit more of our daily lives. Numerous initiatives have appeared, attempting to demystify and make these previously obscure research tracks more accessible to the public. Open source software like Torch, Theano, and TensorFlow have equipped amateurs with the same software which is achieving state-of-the-art results in industry and academia.</p>
<p style="text-align: justify;">This talk will examine the most recent wave of artistic projects applying these methods in various cultural contexts, producing troves of machine-hallucinated text, images, sounds, and videos, demonstrating a previously unseen capacity for imitating human style and sensibility. These experimental works attempt to show the capacity of these machines for producing aesthetically meaningful media, yet challenging and subverting them to illuminate their most obscure and counterintuitive properties.</p>
<p>A recent article by the speaker about this: <a href="http://bit.ly/1OhFcQr">From Pixels to Paragraphs: How artistic experiments with deep learning guard us from hype</a>.</p>
<p>Relevant projects by the speaker that will be presented include: <a href="http://bit.ly/1RyUH76">Style Transfer</a>, <a href="http://bit.ly/1QDNxOI">A Book from the Sky 天书</a>, <a href="http://bit.ly/1QDNClo">Learning to Generate Text and Audio</a>, and <a href="http://bit.ly/1QDNG4D">Deepdream Prototypes</a>.</p>
<h2>Gene Kogan</h2>
<p style="text-align: justify;">Gene Kogan is an artist and programmer who is interested in generative systems and applications of emerging technology in artistic and expressive contexts. He writes code for live music, performance, and visual art. He contributes to numerous open-source software projects and frequently gives workshops and demonstrations on topics related to code and art.</p>
<p style="text-align: justify;">He is a contributor to openFrameworks, Processing, and p5.js, an adjunct professor at Bennington College and NYU, a former resident at Eyebeam Art & Technology Center, and a former Fulbright scholar in Bangalore, India, 2012-2013.</p>
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For more details visit <a href='http://editors.cis-india.org/raw/ai-hype-cycles-and-artistic-subversions'>http://editors.cis-india.org/raw/ai-hype-cycles-and-artistic-subversions</a>
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No publishersharathGenerative ArtArtPracticeMachine LearningResearchers at WorkEventArtificial Intelligence2016-01-01T07:52:20ZEvent