The Centre for Internet and Society
https://cis-india.org
These are the search results for the query, showing results 11 to 25.
Towards Algorithmic Transparency
https://cis-india.org/internet-governance/blog/towards-algorithmic-transparency
<b>This policy brief examines the issue of transparency as a key ethical component in the development, deployment, and use of Artificial Intelligence.</b>
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<p>This brief proposes a framework that seeks to overcome the challenges in preserving transparency when dealing with machine learning algorithms, and suggests solutions such as the incorporation of audits, and ex ante approaches to building interpretable models right from the design stage. Read the full report <a href="https://cis-india.org/internet-governance/algorithmic-transparency-pdf" class="internal-link" title="Algorithmic Transparency PDF">here</a>.</p>
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<p>The Regulatory Practices Lab at CIS aims to produce regulatory policy
suggestions focused on India, but with global application, in an agile
and targeted manner and to promote transparency around practices
affecting digital rights. <br />The Regulatory Practices Lab is supported by Google and Facebook.<br /><br /></p>
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For more details visit <a href='https://cis-india.org/internet-governance/blog/towards-algorithmic-transparency'>https://cis-india.org/internet-governance/blog/towards-algorithmic-transparency</a>
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No publisherRadhika Radhakrishnan, and Amber SinhaRegulatory Practices LabInternet GovernanceFeaturedAlgorithmsinternet governanceTransparencyArtificial Intelligence2020-07-15T13:16:44ZBlog EntryEthics and Human Rights Guidelines for Big Data for Development Research
https://cis-india.org/raw/bd4d-ethics-human-rights-guidelines
<b>This is a four-part review of guideline documents for ethics and human rights in big data for development research. This research was produced as part of the Big Data for Development network supported by International Development Research Centre, Canada</b>
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<h4>Part #1 - Review of Principles of Ethics in Biomedical Science: <a href="https://cis-india.org/raw/bd4d-guideline-documents/biomedicalscience" class="internal-link" title="CIS_BD4D_Guideline01_MS+AS_BiomedicalScience PDF">Download</a> (PDF)</h4>
<h4>Part #2 - Review of Principles of Ethics in Computer Science: <a href="https://cis-india.org/raw/bd4d-guideline-documents/computerscience" class="internal-link" title="CIS_BD4D_Guideline02_RS+AS_ComputerScience PDF">Download</a> (PDF)</h4>
<h4>Part #3 - Summary of Review of Codes of Ethics for Big Data and AI: <a href="https://cis-india.org/raw/bd4d-guideline-documents/AIEthicsReview" class="internal-link" title="CIS_BD4D_Guideline03_AS+PT_BigDataAIEthicsReview_SummaryNotes PDF">Download</a> (PDF)</h4>
<h4>Part #4 - Extended Review of Codes of Ethics for Big Data and AI: <a href="https://cis-india.org/raw/bd4d-guideline-documents/ExtendedNotes" class="internal-link" title="CIS_BD4D_Guideline04_PT+PB_BigDataAIEthicsReview_ExtendedNotes PDF">Download</a> (PDF)</h4>
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<p>The rapid expansion in the volume, velocity, and variety of data available, together with the development of innovative forms of statistical analytics, is generally referred to as “big data”; though there is no single agreed upon definition of the term. Big data promises to provide new insights and solutions across a wide range of sectors. Despite enormous optimism about the scope and variety of big data’s potential applications, many remain concerned about its widespread adoption, with some scholars suggesting it could generate as many harms as benefits. The predecessor disciplines of data science such as computer sciences, applied mathematics, and statistics have traditionally managed to stay out of the scope of ethical frameworks, based on the assumption that they do not involve humans as subject of their research. While critical study into big data is still in its infancy, there is a growing belief that there are significant discontinuities between the rapid growth in big data and the ethical framework that exists to govern its use. In this set of documents, we look at them in detail.</p>
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For more details visit <a href='https://cis-india.org/raw/bd4d-ethics-human-rights-guidelines'>https://cis-india.org/raw/bd4d-ethics-human-rights-guidelines</a>
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No publisherAmber Sinha, Manjri Singh, Rajashri Seal, Pranav Bhaskar Tiwari, Pranav M BidareResearchers at WorkBD4DRAW ResearchBig Data for DevelopmentArtificial Intelligence2020-05-20T07:56:48ZBlog EntryPanelist at launch of Google-UNESCAP AI Report
https://cis-india.org/internet-governance/news/panelist-at-launch-of-google-unescap-ai-report
<b>Arindrajit Basu was a speaker at the panel launching the Google-UNESCAP AI Report at the GovInsider Forum held at the United Nations Convention Centre in Bangkok on October 16, 2019. </b>
<p>Click to <a class="external-link" href="http://cis-india.org/internet-governance/files/launch-the-ai-report">view the agenda</a>.</p>
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For more details visit <a href='https://cis-india.org/internet-governance/news/panelist-at-launch-of-google-unescap-ai-report'>https://cis-india.org/internet-governance/news/panelist-at-launch-of-google-unescap-ai-report</a>
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No publisherAdminInternet GovernanceArtificial Intelligence2019-11-02T06:48:25ZNews ItemFarming the Future: Deployment of Artificial Intelligence in the agricultural sector in India
https://cis-india.org/internet-governance/blog/artificial-intelligence-in-the-delivery-of-public-services-elonnai-hickok-pranav-bidare-arindrajit-basu-siddharth-october-16-2019-farming-the-future
<b>This case study was published as a chapter in the joint UNESCAP-Google publication titled Artificial Intelligence in Public Service Delivery. The chapter in its final form would not have been possible without the efforts and very useful interventions by our colleagues at Digital Asia Hub,Google, and UNESCAP.</b>
<p><img src="https://cis-india.org/home-images/Findings.jpg" alt="Findings" class="image-inline" title="Findings" /></p>
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<p style="text-align: justify; ">Although agriculture is a critical sector for India’s economic development, it continues to face many challenges including a lack of <span>modernization of agricultural methods, fragmented landholdings, erratic rainfalls, overuse of groundwater and a lack of access to </span><span>information on weather, markets and pricing. As state governments create policies and frameworks to mitigate these challenges, the </span><span>role of technology has often come up as a potential driver of positive change.</span></p>
<p style="text-align: justify; "><span>Farmers in the southern Indian states of Karnataka and Andhra Pradesh are facing significant challenges. For hundreds of years,these farmers have relied on traditional agricultural methods to make sowing and harvesting decisions, but now volatile weather patterns and shifting monsoon seasons are making such ancient wisdom obsolete. Farmers are unable to predict weather patterns or crop yields accurately, making it difficult for them to make informed financial and operational decisions associated with planting and harvesting. Erratic weather patterns particularly affect those farmers who reside in remote areas, cut off from meaningful accessto infrastructure and information. In addition to a lack of vital weather information, farmers may lack information about market conditions and may then sell their crops to intermediaries at below-market prices.</span></p>
<p style="text-align: justify; "><span>Against this backdrop, the state governments and local partners in southern India teamed up with Microsoft to develop predictive AI services to help smallholder farmers to improve their crop yields and give them greater price control. Since 2016 three applications have been developed and applied for use in these communities, two of which are discussed in this case study: the AI-sowing app and the price forecasting model.</span></p>
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<p style="text-align: justify; "><a class="external-link" href="https://www.unescap.org/sites/default/files/publications/AI%20Report.pdf">Click to read</a> the report here.</p>
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For more details visit <a href='https://cis-india.org/internet-governance/blog/artificial-intelligence-in-the-delivery-of-public-services-elonnai-hickok-pranav-bidare-arindrajit-basu-siddharth-october-16-2019-farming-the-future'>https://cis-india.org/internet-governance/blog/artificial-intelligence-in-the-delivery-of-public-services-elonnai-hickok-pranav-bidare-arindrajit-basu-siddharth-october-16-2019-farming-the-future</a>
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No publisherElonnai Hickok, Arindrajit Basu, Siddharth Sonkar and Pranav M BInternet GovernanceArtificial Intelligence2019-10-16T13:41:02ZBlog EntryAI Opera- AI as a total work of art
https://cis-india.org/internet-governance/news/ai-opera-ai-as-a-total-work-of-art
<b>On October 11, 2019, Shweta Mohandas and Mira were invited as panelists for the 'AI Opera- AI as a total work of art' event organized by Goethe as part of the India Week Hamburg 2019 held in Bangalore. CIS was an event partner. </b>
<p style="text-align: justify; ">The panel had to present different perspectives and possibilities of Artificial Intelligence (AI). The discussion was facilitated by German artist, performer and filmmaker Christoph Faulhaber. For more info, <a class="external-link" href="https://www.goethe.de/ins/in/en/sta/ban/ver.cfm?fuseaction=events.detail&event_id=21670394">click here</a>.</p>
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For more details visit <a href='https://cis-india.org/internet-governance/news/ai-opera-ai-as-a-total-work-of-art'>https://cis-india.org/internet-governance/news/ai-opera-ai-as-a-total-work-of-art</a>
</p>
No publisherAdminInternet GovernanceArtificial Intelligence2019-10-14T14:30:56ZNews ItemWe need a better AI vision
https://cis-india.org/internet-governance/blog/fountain-ink-october-12-2019-arindrajit-basu-we-need-a-better-ai-vision
<b>Artificial intelligence conjures up a wondrous world of autonomous processes but dystopia is inevitable unless rights and privacy are protected.</b>
<p style="text-align: justify; ">The blog post by Arindrajit Basu was published by<a class="external-link" href="https://fountainink.in/essay/we-need-a-better-ai-vision-"> Fountainink</a> on October 12, 2019.</p>
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<p style="text-align: justify; ">he dawn of Artificial Intelligence (AI) has policy-makers across the globe excited. In India, it is seen as a tool to overleap structural hurdles and better understand a range of organisational and management processes while improving the implementation of several government tasks. Notwithstanding the apparent enthusiasm in the government and private sectors, an adequate technological, infrastructural, and financial capacity to develop these models at scale is still in the works.</p>
<p style="text-align: justify; ">A number of policy documents with direct or indirect references to India’s AI future—to be powered by vast troves of data—have been released in the past year and a half. These include the National Strategy for Artificial Intelligence (which I will refer to as National Strategy) authored by NITI Aayog, the AI Taskforce Report, Chapter 4 of the Economic Survey, the Draft e-Commerce Bill and the Srikrishna Committee Report.</p>
<p style="text-align: justify; ">While they extol the virtues of data-driven analytics, references to the preservation or augmentation of India’s constitutional ethos through AI has been limited though it is crucial for safeguarding the rights and liberties of citizens while paving the way for the alleviation of societal oppression.</p>
<p style="text-align: justify; ">In this essay, I outline the variety of AI use cases that are in the works. I then highlight India’s AI vision by culling the relevant aspects of policy instruments that impact the AI ecosystem and identify lacunae that can be rectified. Finally, I attempt to “constitutionalise AI policy” by grounding it in a framework of constitutional rights that guarantee protection to the most vulnerable sections of society.</p>
<blockquote class="synopsis" style="text-align: justify; ">In the manufacturing industry, AI adoption is not uniform across all sectors. But there has been a notable transformation in electronics, heavy electricals and automobiles.</blockquote>
<p style="text-align: justify; ">It is crucial to note that these cases, still emerging in India, have been implemented at scale in other countries such as the United Kingdom, United States and China. Projects were rolled out to the detriment of ethical and legal considerations. Hindsight should make the Indian policy ecosystem much wiser. By closely studying the research produced in these diverse contexts, Indian policy-makers should try to find ways around the ethical and legal challenges that cropped up elsewhere and devise policy solutions that mitigate the concerns raised.</p>
<p style="text-align: justify; ">***</p>
<p style="text-align: justify; ">B<span>efore anything else we need to define AI—an endeavour fraught with multiple contestations. My colleagues and I at the Centre for Internet & Society ducked this hurdle when conducting our research by adopting a function-based approach. An AI system (as opposed to one that automates routine, cognitive or non-cognitive tasks) is a dynamic learning system that allows for the delegation of some level of human decision-making to the system. This definition allows us to capture some of the unique challenges and prospects that stem from the use of AI.</span></p>
<p style="text-align: justify; ">The research I contributed to at CIS identified key trends in the use of AI across India. In healthcare, it is used for descriptive and predictive purposes.</p>
<p style="text-align: justify; ">For example, the Manipal Group of Hospitals tied up with IBM’s Watson for Oncology to aid doctors in the diagnosis and treatment of seven types of cancer. It is also being used for analytical or diagnostic services. Niramai Health Analytix uses AI to detect early stage breast cancer and Adveniot Tecnosys detects tuberculosis through chest X-rays and acute infections using ultrasound images. In the manufacturing industry, AI adoption is not uniform across all sectors. But there has been a notable transformation in the electronics, heavy electricals and automobiles sector gradually adopting and integrating AI solutions into their products and processes.</p>
<p style="text-align: justify; ">It is also used in the burgeoning online lending segment in order to source credit score data. As many Indians have no credit scores, AI is used to aggregate data and generate scores for more than 80 per cent of the population who have no credit scores. This includes Credit Vidya, a Hyderabad-based data underwriting start-up that provides a credit score to first time loan-seekers and feeds this information to big players such as ICICI Bank and HDFC Bank, among others. It is also used by players such as Mastercard for fraud detection and risk management. In the finance world, companies such as Trade Rays are being used to provide user-friendly algorithmic trading services.</p>
<blockquote class="synopsis" style="text-align: justify; ">AI is also being increasingly used in the education sector for providing services to students such as decision-making assistance and also for student-progress monitoring.</blockquote>
<p style="text-align: justify; ">The next big development is in law enforcement. Predictive policing is making great strides in various states, including Delhi, Punjab, Uttar Pradesh and Maharashtra. A brainchild of the Los Angeles Police Department, predictive policing is the use of analytical techniques such as Machine Learning to identify probable targets for intervention to prevent crime or to solve past crime through statistical predictions.</p>
<p style="text-align: justify; ">Conventional approaches to predictive policing start with the mapping of locations where crimes are concentrated (hot spots) by using algorithms to analyse aggregated data sets. Police in Uttar Pradesh and Delhi have partnered with the Indian Space Research Organisation (ISRO) in a Memorandum of Understanding to allow ISRO’s Advanced Data Processing Research Institute to map, visualise and compile reports about crime-related incidents.</p>
<p style="text-align: justify; ">There are aggressive developments also on the facial recognition front. Punjab Police, in association with Gurugram-based start-up Staqu has started implementing the Punjab Artificial Intelligence System (PAIS) which uses digitised criminal records and automated facial recognition to retrieve information on the suspected criminal. At the national level, on June 28, the National Crime Records Bureau (NCRB) called for tenders to implement a centralised Automated Facial Recognition System (AFRS), defining the scope of work in broad terms as the “supply, installation and commissioning of hardware and software at NCRB.”</p>
<p style="text-align: justify; ">AI is also being increasingly used in the education sector for providing services to students such as decision-making assistance and also for student-progress monitoring. The Andhra Pradesh government had started collecting information from a range of databases and processes the information through Microsoft’s Machine Learning Platform to monitor children and devote student focussed attention on identifying and curbing school drop-outs.</p>
<p style="text-align: justify; ">In Andhra Pradesh, Microsoft collaborated with the International Crop Institute for Semi-Arid Tropics (ICRISAT) to develop an AI Sowing App powered by Microsoft’s Cortana Intelligence Suite. It aggregated data using Machine Learning and sent advisories to farmers regarding optimal dates to sow. This was done via text messages on feature phones after ground research revealed that not many farmers owned or were able to use smart phones. The NITI Aayog AI Strategy specifically cited this use case and reported that this resulted in a 10-30 per cent increase in crop yield. The government of Karnataka has entered into a similar arrangement with Microsoft.</p>
<p style="text-align: justify; ">Finally, in the defence sector, our research found enthusiasm for AI in intelligence, surveillance and reconnaissance (ISR) functions, cyber defence, robot soldiers, risk terrain analysis and moving towards autonomous weapons systems. These projects are being developed by the Defence Research and Development Organisation but the level of trust and support in AI-driven processes reposed by the wings of the armed forces is yet to be publicly clarified. India also had the privilege of leading the global debate on Lethal Autonomous Weapons Systems (LAWS) with Amandeep Singh Gill chairing the United Nations Group of Governmental Experts (UN-GGE) on the issue. However, ‘lethal’ autonomous weapons systems at this stage appear to be a speck in the distant horizon.</p>
<p style="text-align: justify; ">***</p>
<p style="text-align: justify; ">A<span>long with the range of use cases described above, a patchwork of policy imperatives is emerging to support this ecosystem. The umbrella document is the National Strategy for Artificial Intelligence published by the NITI Aayog in June 2018. Despite certain lacunae in its scope, the existence of a cohesive and robust document that lends a semblance of certainty and predictability to a rapidly emerging sphere is in itself a boon. The document focuses on how India can leverage AI for both economic growth and social inclusion. The contents of the document can be divided into a few themes, many of which have also found their way into multiple other instruments.</span></p>
<p style="text-align: justify; ">NITI Aayog provides over 30 policy recommendations on investment in scientific research, reskilling, training and enabling the speedy adoption of AI across value chains. The flagship research initiative is a two-tiered endeavour to boost AI research in India. First, new centres of research excellence (COREs) will develop fundamental research. The COREs will act as feeders for international centres for transformational AI which will focus on creating AI-based applications across sectors.</p>
<p style="text-align: justify; "><img src="https://cis-india.org/home-images/AIinCountries.jpg/@@images/16b4af34-cb6d-423c-be35-e45a60d501cf.jpeg" alt="AI in Countries" class="image-inline" title="AI in Countries" /></p>
<p style="text-align: justify; ">This is an impressive theoretical objective but questions surrounding implementation and structures of operation remain to be answered. China has not only conceptualised an ecosystem but through the Three Year Action Plan to Promote the Development of New Generation Artificial Intelligence Industry, it has also taken a whole-of-government approach to propelling the private sector to an e-leadership position. It has partnered with national tech companies and set clear goals for funding, such as the $2.1 billion technology park for AI research in Beijing.</p>
<p style="text-align: justify; ">The contents of the NITI document can be divided into a few themes, many of which have also found their way into multiple other instruments. First, it proposes an “AI+X” approach that captures the long-term vision for AI in India. Instead of replacing the processes in their entirety, AI is understood as an enabler of efficiency in processes that already exist. NITI Aayog therefore looks at the process of deploying AI-driven technologies as taking an existing process (X) and adding AI to them (AI+X). This is a crucial recommendation all AI projects should heed. Instead of waving AI as an all-encompassing magic wand across sectors, it is necessary to identify specific gaps AI can seek to remedy and then devise the process underpinning this implementation.</p>
<blockquote class="synopsis" style="text-align: justify; ">A cacophony of policy instruments by multiple government departments seeks to reconceptualise data to construct a theoretical framework that allows for its exploitation for AI-driven analytics.</blockquote>
<p style="text-align: justify; ">The AI-driven intervention to develop sowing apps for farmers in Karnataka and Andhra Pradesh are examples of effective implementation of this approach. Instead of other knee-jerk reactions to agrarian woes such as a hasty raising of Minimum Support Price, effective research was done in this use-case to identify a lack of predictability in weather patterns as a key factor in productive crop yields. They realised that aggregation of data through AI could provide farmers with better information on weather patterns. As internet penetration was relatively low in rural Karnataka, text messages to feature phones that had a far wider presence was indispensable to the end game.</p>
<p style="text-align: justify; ">***</p>
<p style="text-align: justify; ">T<span>his is in contrast to the ill-conceived path adopted by the Union ministry of electronics and information technology in guidelines for regulating social media platforms that host content (“intermediaries”). Rule 3(9) of the Draft of the Information Technology [Intermediary Guidelines (Amendment) Rules] 2018 mandates intermediaries to use “automated tools or appropriate mechanisms, with appropriate controls, for proactively identifying and removing or disabling public access to unlawful information or content”.</span></p>
<p style="text-align: justify; ">Proposed in light of the fake news menace and the unbridled spread of “extremist” content online, the use of the phrase “automated tools or appropriate mechanisms” is reflective of an attitude that fails to consider ground realities that confront companies and users alike. They ignore, for instance, the cost of automated tools: whether automated content moderation techniques developed in the West can be applied to Indic languages or grievance redress mechanisms users can avail of if their online speech is unduly restricted. This is thus a clear case of the “AI” mantra being drawn out of a hat without studying the “X” it is supposed to remedy.</p>
<p style="text-align: justify; ">The second focus of the National Strategy that has since morphed into a technology policy mainstay across instruments is on data governance, access and utilisation. The document says the major hurdle to the large scale adoption of AI in India is the difficulty in accessing structured data. It recommends developing big annotated data sets to “democratise data and multi-stakeholder marketplaces across the AI value chain”. It argues that at present only one per cent of data can be analysed as it exists in various unconnected silos. Through the creation of a formal market for data, aggregators such as diagnostic centres in the healthcare sector would curate datasets and place them in the market, with appropriate permissions and safeguards. AI firms could use available datasets rather than wasting effort sourcing and curating the sets themselves.</p>
<p style="text-align: justify; ">A cacophony of policy instruments by multiple government departments seeks to reconceptualise data to construct a theoretical framework that allows for its exploitation for AI-driven analytics.The first is “community data” and appears both in the Srikrishna Report that accompanied the draft Data Protection Bill in 2018 and the draft e-commerce policy.</p>
<p style="text-align: justify; ">But there appears to be some conflict between its usage in the two. Srikrishna endorses a collective protection of privacy by protecting an identifiable community that has contributed to community data. This requires the fulfilment of three key conditions: <i>first,</i> the data belong to an identifiable community; <i>second, </i>individuals in the community consent to being a part of it, and <i>third</i>, the community as a whole consents to its data being treated as community data. On the other hand, the Department of Promotion of Industry and Internal Trade’s (DPIIT) draft e-commerce policy looks at community data as “societal commons” or a “national resource” that gives the community the right to access it but government has ultimate and overriding control of the data. This configuration of community data brings into question the consent framework in the Srikrishna Bill.</p>
<blockquote class="synopsis" style="text-align: justify; ">The government’s attempt to harness data as a national resource for the development of AI-based solutions may be well-intentioned but is fraught with core problems in implementation.</blockquote>
<p style="text-align: justify; ">The matter is further confused by treating “data as a public good”. This is projected in Chapter 4 of the 2019 Economic Survey published by the Ministry of Finance. It explicitly states that any configuration needs to be deferential to privacy norms and the upcoming privacy law. The “personal data” of an individual in the custody of a government is also a “public good” once the datasets are anonymised. At the same time, it pushes for the creation of a government database that links several individual databases, which leads to the “triangulation” problem, where matching different datasets together allows for individuals to be identified despite their anonymisation in seemingly disparate databases.</p>
<p style="text-align: justify; ">“Building an AI ecosystem” was also one of the ostensible reasons for data localisation—the government’s gambit to mandate that foreign companies store the data of Indian citizens within national borders. In addition to a few other policy instruments with similar mandates, Section 40 of the Draft Personal Data Protection Bill mandates that all “critical data” (this is to be notified by the government) be stored exclusively in India. All other data should have a live, serving copy stored in India even if transfer abroad is allowed. This was an attempt to ensure foreign data processors are not the sole beneficiaries of AI-driven insights.</p>
<p style="text-align: justify; ">The government’s attempt to harness data as a national resource for the development of AI-based solutions may be well intentioned but is fraught with core problems in implementation. First, the notion of data as a national resource or as a public good walks a tightrope with constitutionally guaranteed protections around privacy, which will be codified in the upcoming Personal Data Protection Bill. My concerns are not quite so grave in the case of genuine “public data” like traffic signal data or pollution data. However, the Economic Survey manages to crudely amalgamate personal data into the mix.</p>
<p style="text-align: justify; ">It also states that personal data in the custody of a government is a public good once the datasets are anonymised. This includes transactions data in the User Payments Interface (UPI), administrative data including birth and death records, and institutional data including data in public hospitals or schools on pupils or patients. At the same time, it pushes for a government database that will lead to the triangulation problem outlined above. The chapter also suggests that said data may be sold to private firms (unclear if this includes foreign or domestic firms). This not only contradicts the notion of public good but is also a serious threat to the confidentiality and security of personal data.</p>
<p style="text-align: justify; ">***</p>
<p style="text-align: justify; ">T<span>herefore, along with the concerted endeavour to create data marketplaces, it is crucial for policy-makers to differentiate between public data and personal data individuals may consent to be made public. The parameters for clearly defining free and informed consent, as codified in the Draft Personal Data Protection Bill need to be strictly followed as there is a risk of de-anonymisation of data once it finds its way into the marketplace. Second, it is crucial for policy-makers to define clearly a community and parameters for what constitutes individual consent to be part of a community. Finally, along with technical work on setting up a national data marketplace, there must be protracted efforts to guarantee greater security and standards of anonymisation.</span></p>
<blockquote class="synopsis" style="text-align: justify; ">The National Strategy mentions that India should position itself as a “garage” for AI in emerging economies. This could mean Indian citizens are used as guinea pigs for AI-driven solutions at the cost of their rights.</blockquote>
<p style="text-align: justify; ">Assuming that a constitutionally valid paradigm may be created, the excessive focus on data access by tech players dodges the question of the capabilities of analytic firms to process this data and derive meaningful insights from the information. Scholars on China, arguably the poster-child of data-driven economic growth, have sent mixed messages. Ding argues that despite having half the technical capabilities of the US, easy access to data gives China a competitive edge in global AI competition. On the contrary, Andrew Ng has argued that operationalising a sufficient number of relevant datasets still remains a challenge. Ng’s views are backed up by insiders at Chinese tech giant Tencent who say the company still finds it difficult to integrate data streams due to technical hurdles. NITI Aayog’s idea of a multi-stream data marketplace may theoretically be a solution to these potential hurdles but requires sustained funding and research innovation to be converted into reality.</p>
<p style="text-align: justify; ">The National Strategy suggests that government should create a multi-disciplinary committee to set up this marketplace and explore levers for its implementation. This is certainly the need of the hour. It also rightly highlights the importance of research partnerships between academia and the private sector, and the need to support start-ups. There is therefore an urgent need for innovative allied policy instruments that support the burgeoning start-up sector. Proposals such as data localisation may hurt smaller players as they will have to bear the increased fixed costs of setting up or renting data centres.</p>
<p style="text-align: justify; ">The National Strategy also incongruously mentions that India should position itself as a “garage” for the use of AI in emerging economies. This could mean Indian citizens are used as guinea pigs for AI-driven solutions at the cost of their fundamental rights. It could also imply that India should occupy a leadership position and work with other emerging economies to frame the global rights based discourse to seek equitable solutions for the application of AI that works to improve the plight of the most vulnerable in society.</p>
<p style="text-align: justify; ">***</p>
<p style="text-align: justify; ">O<span>ur constitutional ethos places us in a unique position to develop a framework that enables the actualisation of this equitable vision—a goal the policy instruments put out thus far appear to have missed. While the National Strategy includes a section on privacy, security and ethical implications of AI, it stops short of rooting it in fundamental rights and constitutional principles. As a centralised policy instrument, the National Strategy deserves praise for identifying key levers in the future of India’s AI ecosystem and, with the exception of the concerns I outlined above, it is at par with the policy-making thought process in any other nation.</span></p>
<p style="text-align: justify; ">When we start the process of using constitutional principles for AI governance, we must remember that as per Article 12, an individual can file a writ against the state for violation of a fundamental right if the action is taken under the aegis of a “public function”. To combat discrimination by private actors, the state can enact legislation compelling private actors to comply with constitutional mandates. In July, Rajeev Chandrashekhar, a Rajya Sabha MP, suggested a law to combat algorithmic discrimination along the lines of the Algorithmic Accountability Bill proposed in the US Senate. There are three core constitutional questions along the lines of the “golden triangle” of the Indian Constitution any such legislation will need to answer—those of accountability and transparency, algorithmic discrimination and the guarantee of freedom of expression and individual privacy.</p>
<p style="text-align: justify; ">Algorithms are developed by human beings who have their own cognitive biases. This means ostensibly neutral algorithms can have an unintentional disparate impact on certain, often traditionally disenfranchised groups.</p>
<p style="text-align: justify; ">In the <i>MIT Technology Review</i>, Karen Hao explains three stages at which bias might creep in. The first stage is the framing of the problem itself. As soon as computer scientists create a deep-learning model, they decide what they want the model to finally achieve. However, frequently desired outcomes such as “profitability”, “creditworthiness” or “recruitability” are subjective and imprecise concepts subject to human cognitive bias. This makes it difficult to devise screening algorithms that fairly portray society and the complex medley of identities, attributes and structures of power that define it.</p>
<p style="text-align: justify; ">The second stage Hao mentions is the data collection phase. Training data could lead to bias if it is unrepresentative of reality or represents entrenched prejudice or structural inequality. For example, most Natural Language Processing systems used for Parts of Speech (POS) tagging in the US are trained on the readily available data sets from the <i>Wall Street Journal</i>. Accuracy would naturally decrease when the algorithm is applied to individuals—largely ethnic minorities—who do not mimic the speech of the <i>Journal</i>.</p>
<p style="text-align: justify; ">According to Hao, the final stage for algorithmic bias is data preparation, which involves selecting parameters the developer wants the algorithm to consider. For example, when determining the “risk-profile” of car owners seeking insurance premiums, geographical location could be one parameter. This could be justified by the ostensibly neutral argument that those residing in inner-city areas with narrower roads are more likely to have scratches on their vehicles. But as inner cities in the US have a disproportionately high number of ethnic minorities or other vulnerable socio-economic groups, “pin code” becomes a facially neutral proxy for race or class-based discrimination.</p>
<p style="text-align: justify; ">***</p>
<p style="text-align: justify; ">T<span>he right to equality has been carved into multiple international human rights instruments and into the Equality Code in Articles 14-18 of the Indian Constitution. The dominant approach to interpreting the right to equality by the Supreme Court has been to focus on “grounds” of discrimination under Article 15(1), thus resulting in a lack of recognition of unintentional discrimination and disparate impact.</span></p>
<p style="text-align: justify; ">A notable exception, as constitutional scholar Gautam Bhatia points out, is the case of <i>N.M. Thomas </i>which pertained to reservation in promotions. Justice Mathew argued that the test for inequality in Article 16(4) is an effects-oriented test independent of the formal motivation underlying a specific act. Justice Krishna Iyer and Mathew also articulated a grander vision wherein they saw the Equality Code as transcending the embedded individual disabilities in class driven social hierarchies. This understanding is crucial for governing data driven decision-making that impacts vulnerable communities. Any law or policy on AI-related discrimination must also include disparate impact within its definition of “discrimination” to ensure that developers think about the adverse consequences even of well-intentioned decisions.</p>
<p style="text-align: justify; ">AI driven assessments have been challenged on grounds of constitutional violations in other jurisdictions. In 2016, the Wisconsin Supreme Court considered the legality of using risk assessment tools such as COMPAS for sentencing criminals. It affirmed the trial court’s findings and held that using COMPAS did not violate constitutional due process standards. Eric Loomis had argued that using COMPAS infringed both his right to an individualised sentence and to accurate information as COMPAS provided data for specific groups and kept the methodology used to prepare the report a trade secret. He additionally argued that the court used unconstitutional gendered assessments as the tool used gender as one of the parameters.</p>
<p style="text-align: justify; ">The Wisconsin Supreme Court disagreed with Loomis arguing that COMPAS only used publicly available data and data provided by the defendant, which apparently meant Loomis could have verified any information contained in the report. On the question of individualisation, the court argued that COMPAS provided only aggregate data for groups similarly placed to the offender. However, it went on to argue as the report was not the sole basis for a decision by the judge, a COMPAS assessment would be sufficiently individualised as courts retained the discretion and information necessary to disagree.</p>
<p style="text-align: justify; ">By assuming that Loomis could have genuinely verified all the data collected about similarly placed groups and that judges would exercise discretion to prevent the entrenchment of inequalities through COMPAS’s decision-making patterns, the judges ignored social realities. Algorithmic decision-making systems are an extension of unequal decision-making that re-entrenches prevailing societal perceptions around identity and behaviour. An instance of discrimination cannot be looked at as a single instance but as one in a menagerie of production systems that define, modulate and regulate social existence.</p>
<p style="text-align: justify; ">The policy-making ecosystem needs, therefore, to galvanise the “transformative” vision of India’s democratic fibre and study existing systems and power structures AI could re-entrench or mitigate. For example, in the matter of bank loans there is a presumption against the credit-worthiness of those working in the informal sector. The use of aggregated decision-making may lead to more equitable outcomes given that there is concrete thought on the organisational structures making these decisions and the constitutional safeguards provided.</p>
<p style="text-align: justify; ">Most case studies on algorithmic discrimination in Virgina Eubanks’ <i>Automating Inequality </i>or Safiya Noble’s <i>Algorithms of Oppression</i> are based on western contexts. There is an urgent need for publicly available empirical studies on pilot cases in India to understand the contours of discrimination. Primary research questions should explore three related subjects. Are specified ostensibly neutral variables being used to exclude certain communities from accessing opportunities and resources or having a disproportionate impact on their civil liberties? Is there diversity in the identities of the coders themselves? Are the training data sets used representative and diverse and, finally, what role does data driven decision-making play in furthering the battle against embedded structural hierarchies?</p>
<p style="text-align: justify; ">***</p>
<p style="text-align: justify; ">A key feature of AI-driven solutions is the “black box” that processes inputs and generates actionable outputs behind a veil of opacity to the human operator. Essentially, the black box denotes that aspect of the human neural decision-making function that has been delegated to the machine. A lack of transparency or understanding could lead to what Frank Pasquale terms a “Black Box Society” where algorithms define the trajectories of daily existence unless “the values and prerogatives of the encoded rules hidden within black boxes” are challenged.</p>
<p style="text-align: justify; ">Ex-<i>post facto</i> assessment is often insufficient for arriving at genuine accountability. For example, the success of predictive policing in the US was drawn from the fact that police have indeed found more crimes in areas deemed “high risk”. But this assessment does not account for the fact that this is a product of a vicious cycle through which more crime is detected in an area simply because more policemen are deployed. Here, the National Strategy rightly identifies that simply opening up code may not deconstruct the black box as not all stakeholders impacted by AI solutions may understand the code. The constant aim should be explicability which means the human developer should be able to explain how certain factors may be used to arrive at a certain cluster of outcomes in a given set of situations.</p>
<p style="text-align: justify; ">The requirement of accountability stems from the Right to Life provision under Article 21. As stated in the seven-judge bench in <i>Maneka Gandhi vs. Union of India</i>, any procedure established by law must be seen to be “fair, just and reasonable” and not “fanciful, oppressive or arbitrary.”</p>
<p style="text-align: justify; ">The Right to Privacy was recognised as a fundamental right by the nine-judge bench in <i>K.S. Puttaswamy (Retd.) vs. Union of India</i>. Mass surveillance can lead to the alteration of behavioural patterns which may in turn be used for the suppression of dissent by the State. Pulling vast tracts of data on all suspected criminals—as in facial recognition systems like PAIS—create a “presumption of criminality” that can have a chilling effect on democratic values.</p>
<p style="text-align: justify; ">Therefore, any use, particularly by law enforcement would need to satisfy the requirements for infringing on the right to privacy: the existence of a law, necessity—a clearly defined state objective—and proportionality between the state object and the means used restricting fundamental rights the least. Along with centralised policy instruments such as the National Strategy, all initiatives taken in pursuance of India’s AI agenda must pay heed to the democratic virtues of privacy and free speech and their interlinkages.</p>
<p style="text-align: justify; ">India needs a law to regulate the impact of Artificial Intelligence and enable its development without restricting fundamental rights. However, regulation should not adopt a “one-size-fits-all” approach that views all uses with the same level of rigidity. Regulatory intervention should be based on questions around power asymmetries and the likelihood of the use case adversely affronting human dignity captured by India’s constitutional ethos.</p>
<blockquote class="synopsis" style="text-align: justify; ">As an aspiring leader in global discourse, India can lay the rules of the road for other emerging economies not only by incubating, innovating and implementing AI powered technologies but by grounding it in a lattice of rich constitutional jurisprudence that empowers the individual.</blockquote>
<p style="text-align: justify; ">The High Level Task Force on Artificial Intelligence (AI HLEG) set up by the European Commission in June 2018 published a report on “Ethical Guidelines for Trustworthy AI” earlier this year. They feature seven core requirements which include human agency and oversight; technical robustness and safety; privacy and data governance; transparency; diversity, non-discrimination and fairness; societal and environmental well-being; and accountability. While the principles are comprehensive, this document stops short of referencing any domestic or international constitutional law that helps cement these values. The Indian Constitution can help define and concretise each of these principles and could be used as a vehicle to foster genuine social inclusion and mitigation of structural injustice through AI.</p>
<p style="text-align: justify; ">At the centre of the vision must be the inherent rights of the individual. The constitutional moment for data driven decision-making emerges therefore when we conceptualise a way through which AI can be utilised to preserve and improve the enforcement of rights while also ensuring that data does not become a further avenue for exploitation.</p>
<p style="text-align: justify; ">National vision transcends the boundaries of policy and to misuse Peter Drucker, “eats strategy for breakfast”. As an aspiring leader in global discourse, India can lay the rules of the road for other emerging economies not only by incubating, innovating and implementing AI powered technologies but by grounding it in a lattice of rich constitutional jurisprudence that empowers the individual, particularly the vulnerable in society. While the multiple policy instruments and the National Strategy are important cogs in the wheel, the long-term vision can only be framed by how the plethora of actors, interest groups and stakeholders engage with the notion of an AI-powered Indian society.</p>
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<p>
For more details visit <a href='https://cis-india.org/internet-governance/blog/fountain-ink-october-12-2019-arindrajit-basu-we-need-a-better-ai-vision'>https://cis-india.org/internet-governance/blog/fountain-ink-october-12-2019-arindrajit-basu-we-need-a-better-ai-vision</a>
</p>
No publisherbasuInternet GovernanceArtificial Intelligence2019-10-14T13:55:59ZBlog EntryAI for Good
https://cis-india.org/internet-governance/blog/ai-for-good-event-report-on-workshop-conducted-at-unbox-festival
<b>CIS organised a workshop titled ‘AI for Good’ at the Unbox Festival in Bangalore from 15th to 17th February, 2019. The workshop was led by Shweta Mohandas and Saumyaa Naidu. In the hour long workshop, the participants were asked to imagine an AI based product to bring forward the idea of ‘AI for social good’.</b>
<p>The report was edited by Elonnai Hickok.</p>
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<p style="text-align: justify; ">The workshop was aimed at examining the current narratives around AI and imagining how these may transform with time. It raised questions about how we can build an AI for the future, and traced the implications relating to social impact, policy, gender, design, and privacy.</p>
<h3>Methodology</h3>
<p class="Normal1" style="text-align: justify; ">The rationale for conducting this workshop in a design festival was to ensure a diverse mix of participants. The participants in the workshop came from varied educational and professional backgrounds who had different levels of understanding of technology. The workshop began with a discussion on the existing applications of artificial intelligence, and how people interact and engage with it on a daily basis. This was followed by an activity where the participants were provided with a form and were asked to conceptualise their own AI application which could be used for social good. The participants were asked to think about a problem that they wanted the AI application to address and think of ways in which it would solve the problem. They were also asked to mention who will use the application. It prompted participants to provide details of the AI application in terms of the form, colour, gender, visual design, and medium of interaction (voice/ text). This was intended to nudge the participants into thinking about the characteristics of the application, and how it will lend to the overall purpose. The form was structured and designed to enable participants to both describe and draw their ideas. The next section of the form gave them multiple pairs of principles. They were asked to choose one principle from each pair. These were conflicting options such as ‘Openness’ or ‘Proprietary’, and ‘Free Speech’ or ‘Moderated Speech’. The objective of this section was to illustrate how a perceived ideal AI that satisfies all stakeholders can be difficult to achieve, and that the AI developers at times may be faced with a decision between profitability and user rights.</p>
<p class="Normal1" style="text-align: justify; ">Participants were asked to keep their responses anonymous. These responses were then collected and discussed with the group. The activity led to the participants engaging in a discussion on the principles mentioned in the form. Questions around where the input data to train the AI would come from, or what type of data the application will collect were discussed. The responses were used to derive implications on gender, privacy, design, and accessibility.</p>
<p class="Normal1" style="text-align: justify; "><img src="https://cis-india.org/home-images/ConceptualiseAI.jpg" alt="Conceptualise AI" class="image-inline" title="Conceptualise AI" /></p>
<h3 class="Normal1" style="text-align: justify; ">Responses</h3>
<p class="Normal1" style="text-align: justify; "><img src="https://cis-india.org/home-images/Responses.jpg" alt="" class="image-inline" title="" /></p>
<h3 class="Normal1" style="text-align: justify; ">Analysis</h3>
<p>Even as the responses were varied, they had a few key similarities and observations.</p>
<h3>Participants’ Familiarity with AI</h3>
<p style="text-align: justify; ">The participants’ understanding of AI was based on what they read and heard from various sources. While discussing the examples of AI, the participants were familiar with not just the physical manifestation of AI such as robots, but also AI software. However when asked to define an AI the most common explanations were, bots, software, and the use of algorithms to make decisions using large amounts of data. The participants were optimistic of the way AI could be used for social good. However, some of them showed concern about the implications on privacy.</p>
<h3 style="text-align: justify; ">Perception of AI Among Participants</h3>
<p class="Normal1">With the workshop, our aim was to have the participants reflect on their perception of AI based on their exposure to the narratives around AI by companies and the government.</p>
<p class="Normal1" style="text-align: justify; ">The participants were given the brief to imagine an AI that could solve a problem or be used for social good. Most participants considered AI to be a positive tool for social impact. It was seen as a problem solver. The ideas conceptualised by the participants varied from countering fake news, wildlife conservation, resource distribution, and mental health. This brought to focus the range of areas that were seen as pertinent for an AI intervention. Most of the responses dealt with concerns that affect humans directly, the one aimed at wildlife conservation being the only exception.</p>
<p class="Normal1" style="text-align: justify; "><span>On being asked, who will use the AI application, it was interesting to note that all the responses considered different stakeholders such as individuals, non profits, governments and private companies to be the end user. However, it was interesting that through the discussion the harms that might be caused by the use of AI by these stakeholders were not brought up. For example, the use of AI for resource distribution did not take into consideration the fact that the government could provide unequal distribution based on the existing biased datasets.</span> <a name="fr1"></a> <span>Several of the AI applications were conceptualised to work without any human intervention. For example, one of the ideas proposed was to use AI as a mental health counsellor which was conceptualised as a chatbot that would learn more about human psychology with each interaction. It was assumed that such a service would be better than a human psychologist who can be emotionally biased. Similarly, while discussing the idea behind the use of AI for preventing the spread of fake news, the participant believed that the indication coming from an AI would have greater impact than one coming from a human. They believed that the AI could provide the correct information and prevent the spread of fake news. </span><span>By discussing these cases we were able to highlight that the complete reliance on technology could have severe consequences.</span><a name="fr2"></a></p>
<h3 class="Normal1" style="text-align: justify; ">Form and Visual Design of the AI Concepts</h3>
<p style="text-align: justify; ">In most cases, the participants decided the form and visual design of their AI concepts keeping in mind its purpose. For instance, the therapy providing AI mentioned earlier, was envisioned as a textual platform, while a ‘clippy type’ add on AI tool was thought of for detecting fake news. Most participants imagined the AI application to have a software form, while the legal aid AI application was conceptualised to have a human form. This revealed that the participants perceived AI to be both a software and a physical device such as a robot.</p>
<h3 style="text-align: justify; ">Accessibility of the Interfaces</h3>
<p style="text-align: justify; ">The purpose of including the type of interface (voice or text) while conceptualising the AI application was to push the participants towards thinking about accessibility features. We aimed to have the participants think about the default use of the interface, both in terms of language and accessibility. The participants though cognizant of the need to have a large number of users, preferred to have only textual input into the interface, not anticipating the accessibility concerns.</p>
<p style="text-align: justify; ">The choices between access vs cost, and accessibility vs scalability were also questioned by the participants during the workshop. They enquired about the meaning of the terms as well as discussed the difficulty in having an all inclusive interface. Some of the responses consisted only of text inputs, especially for sensitive issues involving interactions, such as for therapy or helplines. This exercise made the participants think about the end user as well as the ‘AI for all’ narrative. We decided to add these questions that made the participants think about how the default ability, language, and technological capability of the user is taken for granted, and how simple features could help more people interact with the application. This discussion led to the inference that there is a need to think about accessibility by design during the creation of the application and not as an afterthought.<a name="fr3"></a></p>
<h3 style="text-align: justify; ">Biases Based on Gender</h3>
<p style="text-align: justify; ">We intended for the participants to think about the inherent biases that creep into creating an AI concept. These biases were evident from deciding identifiably male names, to deciding a male voice when the application needed to be assertive, or a female voice and name for when it was dealing with school children. Most of the other participants either did not mention the gender or they said that the AI could be gender neutral or changeable.</p>
<p style="text-align: justify; ">These observations are also revealing of the existing narrative around AI. The popular AI interfaces have been noted to exemplify existing gender stereotypes. For example, the virtual assistants were given female identifiable names and default female voices such as Siri, Alexa, and Cortana. The more advanced AI were given male identifiable names and default male voices such as Watson, Holmes etc.<a name="fr4"></a> <span>Although these concerns have been pointed out by several researchers, there needs to be a visible shift towards moving away from existing gender biases.</span></p>
<h3 style="text-align: justify; ">Concerns around Privacy</h3>
<p style="text-align: justify; ">Though the participants were aware of the privacy implications of data driven technologies, they were unsure of how their own AI concept could deal with questions of privacy. The participants voiced concerns about how they would procure the data to train the AI but were uncertain about their data processing practices. This included how they would store the data, anonymise the data, or prevent third parties from accessing it. For example, during the activity, it was pointed out to the participants that there would be sensitive data collected in applications such as therapy provision, legal aid for victims of abuse, and assistance for people with social anxiety. In these cases, the participants stated that they would ensure that the data was shared responsibly, but did not consider the potential uses or misuses of this shared data.</p>
<h3 style="text-align: justify; ">Choices between Principles</h3>
<p class="Normal1" style="text-align: justify; ">This part of the exercise was intended to familiarise the participants with certain ethical and policy questions about AI, as well as to look at the possible choices that AI developers have to make. Along with discussing the broader questions around the form and interface of AI, we wanted the participants to also look at making decisions about the way the AI would function. The intent behind this component of the exercise was to encourage the participants to question the practices of AI companies, as well as understand the implications of choices while creating an AI. As the language in this section was based on law and policy, we spent some time describing the terms to the participants. Even as some of the options presented by us were not exhaustive or absolute extremes, we placed this section to demonstrate the complexity in creating an AI that is beneficial for all. We intended for the participants to understand that an AI that is profitable to the company, free for people, accessible, privacy respecting, and open source, though desirable may be in competition with other interests such as profitability and scalability.</p>
<p class="Normal1" style="text-align: justify; ">The participants were urged to think about how decisions regarding who can use the service, how much transparency and privacy the company will provide, are also part of building an AI. Taking an example from the responses, we talked about how having a closed proprietary software in case of AI applications such as providing legal aid to victims of abuse would deter the creation of similar applications. However, after the terms were explained, the participants mostly chose openness over proprietary software, and access over paid services.</p>
<h3 class="Normal1" style="text-align: justify; ">Conclusion</h3>
<p class="Normal1" style="text-align: justify; ">The aim of this exercise was to understand the popular perception of AI. The participants had varied understanding of AI, but were familiar with the term. They also knew of the popular products that claim to use AI. Since the exercise was designed for people as an introduction to AI policy, we intended to keep questions around data practices out of the concept form. Eventually, with this exercise, we, along with the participants, were able to look at how popular media sells AI as an effective and cheaper solution to social issues. The exercise also allowed the participants to understand certain biases with gender, language, and ability. It also shed light on how questions of access and user rights should be placed before the creation of a technological solution. New technologies such as AI are being featured as problem solvers by companies, the media and governments. However, there is a need to also think about how these technologies can be exclusionary, misused, or how they amplify existing socio economic inequities.</p>
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<p class="Normal1" style="text-align: justify; "><span>[1]. </span><a class="external-link" href="https://www.bizjournals.com/sanfrancisco/news/2019/08/26/maximizing-the-potential-of-ai-starts-with-trust.html">https://www.bizjournals.com/sanfrancisco/news/2019/08/26/maximizing-the-potential-of-ai-starts-with-trust.html</a></p>
<p>[2]. <a class="external-link" href="https://qz.com/1023448/if-youre-not-a-white-male-artificial-intelligences-use-in-healthcare-could-be-dangerous/">https://qz.com/1023448/if-youre-not-a-white-male-artificial-intelligences-use-in-healthcare-could-be-dangerous/</a></p>
<p>[3]. <a class="external-link" href="https://www.vox.com/the-goods/2018/11/29/18118469/instagram-accessibility-automatic-alt-text-object-recognition">https://www.vox.com/the-goods/2018/11/29/18118469/instagram-accessibility-automatic-alt-text-object-recognition</a></p>
<p>[4]. <a class="external-link" href="https://www.theguardian.com/pwc-partner-zone/2019/mar/26/why-are-virtual-assistants-always-female-gender-bias-in-ai-must-be-remedied">https://www.theguardian.com/pwc-partner-zone/2019/mar/26/why-are-virtual-assistants-always-female-gender-bias-in-ai-must-be-remedied</a></p>
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For more details visit <a href='https://cis-india.org/internet-governance/blog/ai-for-good-event-report-on-workshop-conducted-at-unbox-festival'>https://cis-india.org/internet-governance/blog/ai-for-good-event-report-on-workshop-conducted-at-unbox-festival</a>
</p>
No publisherShweta Mohandas and Saumyaa NaiduInternet GovernanceArtificial Intelligence2019-10-13T05:32:28ZBlog EntryArtificial Intelligence: a Full-Spectrum Regulatory Challenge [Working Draft]
https://cis-india.org/internet-governance/artificial-intelligence-a-full-spectrum-regulatory-challenge-working-draft
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<p>Today, there are certain misconceptions regarding the regulation of AI. Some corporations would like us to believe that AI is being developed and used in a regulatory vacuum. Others in civil society organisations believe that AI is a regulatory circumvention strategy deployed by corporations. As a result, these organisations call for onerous regulations targeting corporations. However, some uses of AI by corporations can be completely benign and some uses AI by the state can result in the most egregious human rights violations. Therefore policy makers need to throw every regulatory tool from their arsenal to unlock the benefits of AI and mitigate its harms.</p>
<p>This policy brief proposes a granular, full spectrum approach to the regulation of AI depending on who is using AI, who is impacted by that use and what human rights are impacted. Everything from deregulation, to forbearance, to updated regulations, to absolute and blanket prohibitions needs to be considered depending on the specifics. This approach stands in contrast to approaches of ethics, omnibus law, homogeneous principles, and human rights, which will result in inappropriate under-regulation or over-regulation of the sector.</p>
<p>Find a copy of the working draft <a href="https://cis-india.org/internet-governance/artificial-intelligence-a-full-spectrum-regulatory-challenge-working-draft-pdf" class="internal-link" title="Artificial Intelligence: A Full-Spectrum Regulatory Challenge (Working Draft) PDF">here</a>.</p>
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For more details visit <a href='https://cis-india.org/internet-governance/artificial-intelligence-a-full-spectrum-regulatory-challenge-working-draft'>https://cis-india.org/internet-governance/artificial-intelligence-a-full-spectrum-regulatory-challenge-working-draft</a>
</p>
No publishersunilRegulatory Practices LabInternet GovernanceArtificial Intelligence2020-08-04T06:10:13ZBlog EntryResponsible AI Workshop
https://cis-india.org/internet-governance/news/responsible-ai-workshop
<b>Sunil Abraham participated in this meeting organized by Facebook on September 17, 2019 in New Delhi. </b>
<p><a class="external-link" href="http://cis-india.org/internet-governance/files/responsible-ai">Click to view the agenda</a></p>
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For more details visit <a href='https://cis-india.org/internet-governance/news/responsible-ai-workshop'>https://cis-india.org/internet-governance/news/responsible-ai-workshop</a>
</p>
No publisherAdminInternet GovernanceArtificial Intelligence2019-09-20T14:50:47ZNews ItemTalks at National University of Juridical Sciences Today
https://cis-india.org/internet-governance/news/talks-at-national-university-of-juridical-sciences-today
<b>Arindrajit Basu delivered two lectures at the National University of Juridical Sciences on September 18, 2019. </b>
<p style="text-align: justify; ">The first one was part of a symposium being conducted by the soon to be set up Intellectual Property and Technology Law Centre. I spoke on "Conceptualising India's Digital Policy Vision" The other speaker today was Mr. Supratim Chakraborty (Partner, Khaitan&Co.) Tomorrow's speakers are Prof. Mahendra Kumar Bhandan and Nikhil Narendran (Partner, Trilegal)</p>
<p style="text-align: justify; "><b>Abstract</b></p>
<p style="text-align: justify; ">The past year has seen vigorous activity on the domestic data governance policy front in India. Across key issues including intermediary liability, data localisation and e-commerce, the government has rolled out a patchwork of regulatory policies that has resulted in battle lines being drawn by governments, industry and civil society actors both in India and across the globe. The Data Protection Bill is set to be tabled in the next session of Parliament amidst supposed disagreement among policy-makers on key provisions, including data localization. The draft e-commerce policy and Chapter 4 of the Economic Survey refer to the concepts of ‘community data’ and ‘data as public good’ respectively. Artifiicial Intelligence is also the new buzz word among policy-making circles and industry players alike.<br /><br />The implementation of each of these concepts have important implications for individual privacy, the monetisation of data by (foreign tech companies) and the harnessing of-as the e-commerce policy puts it-India’s data for India’s development. Meanwhile, at international forums such as the G20, India has partnered up with its BRICS allies to emphasize the notion of ‘data sovereignty’ or the right of each country to govern data within its jurisdiction without external interference.<br />In his talk, Basu unpacked each of these policies and followed up with a discussion on what these developments meant for Indian citizens and for India’s role in the multilateral global order.</p>
<p style="text-align: justify; ">The second one was on 'Constitutionalizing Artificial Intelligence' conducted by the Constitutional Law Society. Here, I drew from some preliminary findings from a paper I am working on with Elonnai and Amber.</p>
<p style="text-align: justify; "><b>Abstract</b></p>
<p style="text-align: justify; ">The use of big data and algorithmic decision-making has been touted world over as a means of augmenting human capacities, removing bureaucratic fetters and benefiting society. Yet, with concerns arising around bias, fairness and a lack of algorithmic accountability, an entirely new domain of discourse on data justice has emerged - underscoring the idea that algorithms not only have the potential to exacerbate entrenched structural inequality but could also create and modulate new forms of injustice for the vulnerable sections of society.</p>
<p style="text-align: justify; "><span>There is a need for a reflexive turn in the debate on data justice that adequately considers the broader narrative and entrenched inequality in the ecosystem. </span><span>Transformative constitutionalism is a new brand of scholarship in comparative constitutional law which celebrates the crucial role of the state and the judiciary in bringing about emancipatory change and rooting out structural inequality.</span></p>
<p style="text-align: justify; ">Originally conceptualized as a Global South concept designed as a counter-model to the individual rights-driven model of Northern Constitutions, scholars have now identified emancipatory provisions in several western constitutions such as Germany. India’s constitution is one such example. The origins of constitutional order in India were designed to “bring the alien and powerful machine like that of the state under the control of human will” and to eliminate the inequality of “status, facilities and opportunities.” <br /><br />What is the relevance of India's constitutional ethos in the regulation of modern day data driven decision-making? How can policy-makers use constitutional tenets to mitigate structural injustice and transform the bearings of 21st century Indian society?</p>
<p>
For more details visit <a href='https://cis-india.org/internet-governance/news/talks-at-national-university-of-juridical-sciences-today'>https://cis-india.org/internet-governance/news/talks-at-national-university-of-juridical-sciences-today</a>
</p>
No publisherAdminIndustry 4.0Internet GovernanceArtificial Intelligence2019-09-20T14:45:35ZNews ItemAI in Healthcare
https://cis-india.org/internet-governance/news/ai-in-healthcare
<b>The Center for Information Technology and Public Policy (CITAPP) and the International Institute of Information Technology Bangalore (IIITB) invited Radhika Radhakrishnan for a talk at IIIT-Bangalore on September 13, 2019. </b>
<p style="text-align: justify; ">In her talk, she critically questioned the dominant narrative of “AI for social good” that has been widely adopted by various stakeholders in India (including the private sector, non-profits, and the Indian State) from a feminist standpoint. Specific to healthcare in India, such a narrative has been employed towards solving development challenges (such as a shortage of medical practitioners in remote regions of the country) through the introduction of AI applications targeted towards the sick-poor. Through her research and fieldwork, she analysed the layers of expropriation and experimentation that come into play when AI technologies become a method of using 'diverse' bodies and medical records of the sick-poor as ‘data’ to train proprietary AI algorithms at a low cost in the absence of effective State regulatory mechanisms. She argued that structural challenges (such as lack of incentives for medical practitioners to join public healthcare) get reframed into opportunities to substitute labour (people) by capital (technology) through innovation of “spectacular technologies” such as AI. Throughout the talk, she also highlighted the methodologies she used to conduct this research.</p>
<p>
For more details visit <a href='https://cis-india.org/internet-governance/news/ai-in-healthcare'>https://cis-india.org/internet-governance/news/ai-in-healthcare</a>
</p>
No publisherAdminIndustry 4.0Internet GovernanceArtificial Intelligence2019-09-19T16:15:24ZNews ItemPolicies for the Platform Economy
https://cis-india.org/internet-governance/news/policies-for-the-platform-economy
<b>Anubha Sinha and Amber Sinha will be panelists in this event being organized by IT for Change at India Habitat Centre in New Delhi on August 30, 2019. </b>
<p>The agenda for the event <a class="external-link" href="http://cis-india.org/internet-governance/files/agenda-for-policies-for-the-platform-economy">is here</a>.</p>
<p>
For more details visit <a href='https://cis-india.org/internet-governance/news/policies-for-the-platform-economy'>https://cis-india.org/internet-governance/news/policies-for-the-platform-economy</a>
</p>
No publisherAdminInternet GovernanceArtificial Intelligence2019-08-27T00:19:26ZNews ItemImpact of Industrial Revolution 4.0 - IT and Automotive Sector in India by the Dialogue and FES
https://cis-india.org/internet-governance/news/impact-of-industrial-revolution-4-0-it-and-automotive-sector-in-india-by-the-dialogue-and-fes
<b>On August 21, 2019, Aayush Rathi, attended a report launch event and focus group discussion on the "Impact of Industrial Revolution 4.0 - IT and Automotive Sector in India". Research conducted by the Dialogue in collaboration with the Friedrich-Ebert-Stiftung (FES) were being presented. </b>
<p class="moz-quote-pre" style="text-align: justify; ">At CIS, we have previously produced research on the future of work in these sectors. Aayush attended the event to understand how other researchers are approaching the subject of the future of work in terms of the methodological approach and the questions being asked and policy responses being proposed. In what may be treated as validation of our research design, FES and the Dialogue have addressed similar questions and adopted an empirical+desk based approach to do so as well.</p>
<p>
For more details visit <a href='https://cis-india.org/internet-governance/news/impact-of-industrial-revolution-4-0-it-and-automotive-sector-in-india-by-the-dialogue-and-fes'>https://cis-india.org/internet-governance/news/impact-of-industrial-revolution-4-0-it-and-automotive-sector-in-india-by-the-dialogue-and-fes</a>
</p>
No publisherAdminIndustry 4.0Internet GovernanceInformation TechnologyArtificial Intelligence2019-08-27T00:13:32ZNews ItemEmergence of Chinese Technology:Rising stakes for innovation, competition and governance
https://cis-india.org/internet-governance/news/emergence-of-chinese-technology-rising-stakes-for-innovation-competition-and-governance
<b>Omidyar Network in partnership with the Esya Centre organized a private discussion on the theme “Emergence of Chinese technology - rising stakes for innovation, competition and governance” on Monday, 12 August 2019 in New Delhi. Arindrajit Basu attended the event. </b>
<p style="text-align: justify; ">China Ascendant: Soft Power report by ON focuses on three prongs of power-digital power, fore power and sharp power. Standards have been a major avenue for proliferation of Chinese competition.This is combined with knowledge transfer as 2.8 million Chinese students in the US have largely returned to tech companies in China. Core strength is still not in basic research so by 2020, aiming for 15 per cent of PhD.s to be in basic research. China uses nudges in shaping global governance outcomes by targeting the right stakeholders as opposed to altering the ground rules entirely, Universities in China have focused on how cultural connections can be linked upto negotiating prowess at multilateral fora.</p>
<ul>
<li>China takes a whole of government approach to technology innovation. Continues to be consumer focused.</li>
<li>China does not look at India as a R+D partner,more as a market.Stability and unpredictability has been an issue.None of India's tech policies were drafted with China in mind.</li>
</ul>
<p>
For more details visit <a href='https://cis-india.org/internet-governance/news/emergence-of-chinese-technology-rising-stakes-for-innovation-competition-and-governance'>https://cis-india.org/internet-governance/news/emergence-of-chinese-technology-rising-stakes-for-innovation-competition-and-governance</a>
</p>
No publisherAdminInternet GovernanceArtificial Intelligence2019-08-19T14:03:21ZNews ItemRethinking the intermediary liability regime in India
https://cis-india.org/internet-governance/blog/cyber-brics-august-12-2019-torsha-sarkar-rethinking-the-intermediary-liability-regime-in-india
<b>The article consolidates some of our broad thematic concerns with the draft amendments to the intermediary liability rules, published by MeitY last December.
</b>
<p>The blog post by Torsha Sarkar was <a class="external-link" href="https://cyberbrics.info/rethinking-the-intermediary-liability-regime-in-india/">published by CyberBRICS</a> on August 12, 2019.</p>
<hr />
<h3 style="text-align: justify; ">Introduction</h3>
<p style="text-align: justify; ">In December 2018, the Ministry of Electronics and Information Technology (“MeitY”) released the Intermediary Liability Guidelines (Amendment) Rules (“the Guidelines”), which would be significantly altering the intermediary liability regime in the country. While the Guidelines has drawn a considerable amount of attention and criticism, from the perspective of the government, the change has been overdue.</p>
<p style="text-align: justify; ">The Indian government has been determined to overhaul the pre-existing safe harbour regime since last year. The draft<a href="https://www.medianama.com/wp-content/uploads/Draft-National-E-commerce-Policy.pdf">version</a> of the e-commerce policy, which were leaked last year, also hinted at similar plans. As effects of mass dissemination of disinformation, propaganda and hate speech around the world spill over to offline harms, governments have been increasingly looking to enact interventionist laws that leverage more responsibility on the intermediaries. India has not been an exception.</p>
<p style="text-align: justify; ">A major source of these harmful and illegal content in India come through the popular communications app WhatsApp, despite the company’s enactment of several anti-spam measures over the past few years. Last year, rumours circulated on WhatsApp prompted a series of lynchings. In May, Reuters <a href="https://in.reuters.com/article/india-election-socialmedia-whatsapp/in-india-election-a-14-software-tool-helps-overcome-whatsapp-controls-idINKCN1SL0PZ" rel="noreferrer noopener" target="_blank">reported</a> that clones and software tools were available at minimal cost in the market, for politicians and other interested parties to bypass these measures, and continue the trend of bulk messaging.</p>
<p style="text-align: justify; ">These series of incidents have made it clear that disinformation is a very real problem, and the current regulatory framework is not enough to address it. The government’s response to this has been accordingly, to introduce the Guidelines. This rationale also finds a place in its preliminary<a href="https://www.meity.gov.in/comments-invited-draft-intermediary-rules" rel="noreferrer noopener" target="_blank">statement of reasons</a>.</p>
<p style="text-align: justify; ">While enactment of such interventionist laws has triggered fresh rounds of debate on free speech and censorship, it would be wrong to say that such laws were completely one-sided, or uncalled for.</p>
<p style="text-align: justify; ">On one hand, automated amplification and online mass circulation of purposeful disinformation, propaganda, of terrorist attack videos, or of plain graphic content, are all problems that the government would concern itself with. On the other hand, several online companies (including <a href="https://www.blog.google/outreach-initiatives/public-policy/oversight-frameworks-content-sharing-platforms/" rel="noreferrer noopener" target="_blank">Google</a>) also seem to be in an uneasy agreement that simple self-regulation of content would not cut it. For better oversight, more engagement with both government and civil society members is needed.</p>
<p style="text-align: justify; ">In March this year, Mark Zuckerberg wrote an<a href="https://www.washingtonpost.com/opinions/mark-zuckerberg-the-internet-needs-new-rules-lets-start-in-these-four-areas/2019/03/29/9e6f0504-521a-11e9-a3f7-78b7525a8d5f_story.html?utm_term=.4d177c66782f" rel="noreferrer noopener" target="_blank">op-ed</a> for the Washington Post, calling for more government involvement in the process of content regulation on its platform. While it would be interesting to consider how Zuckerberg’s view aligns with those similarly placed, it would nevertheless be correct to say that online intermediaries are under more pressure than ever to keep their platforms clean of content that is ‘illegal, harmful, obscene’. And this list only grows.</p>
<p style="text-align: justify; ">That being said, the criticism from several stakeholders is sharp and clear in instances of such law being enacted – be it the ambitious <a href="https://www.ivir.nl/publicaties/download/NetzDG_Tworek_Leerssen_April_2019.pdf" rel="noreferrer noopener" target="_blank">NetzDG</a> aimed at combating Nazi propaganda, hate speech and fake news, or the controversial new European Copyright Directive which has been welcomed by journalists but has been severely critiqued by online content creators and platforms as detrimental against user-generated content.</p>
<p style="text-align: justify; ">In the backdrop of such conflicting interests on online content moderation, it would be useful to examine the Guidelines released by MeitY. In the first portion we would be looking at certain specific concerns existing within the rules, while in the second portion, we would be pushing the narrative further to see what an alternative regulatory framework may look like.</p>
<p style="text-align: justify; ">Before we jump to the crux of this discussion, one important disclosure must be made about the underlying ideology of this piece. It would be unrealistic to claim that the internet should be absolutely free from regulation. Swathes of content on child sexual abuse, or terrorist propaganda, or even the hordes of death and rape threats faced by women online are and should be concerns of a civil society. While that is certainly a strong driving force for regulation, this concern should not override the basic considerations for human rights (including freedom of expression). These ideas would be expanded a bit more in the upcoming sections.</p>
<h3 style="text-align: justify; ">Broad, thematic concerns with the Rules</h3>
<h3 style="text-align: justify; ">A uniform mechanism of compliance</h3>
<h3 style="text-align: justify; ">Timelines</h3>
<p style="text-align: justify; ">Rule 3(8) of the Guidelines mandates intermediaries, prompted by <em>a</em> <em>court order or a government notification</em>, to take down content relating to unlawful acts within 24 hours of such notification. In case they fail to do so, the safe harbour applicable to them under section 79 of the Information Technology Act (“the Act”) would cease to apply, and they would be liable. Prior to the amendment, this timeframe was 36 hours.</p>
<p style="text-align: justify; ">There is a visible lack of research which could rationalize that a 24-hour timeline for compliance is the optimal framework, for <em>all</em> intermediaries, irrespective of the kind of services they provide, or the sizes or resources available to them. As Mozilla Foundation has <a href="https://blog.mozilla.org/netpolicy/2018/07/11/sustainable-policy-solutions-for-illegal-content/" rel="noreferrer noopener" target="_blank">commented</a>, regulation of illegal content online simply cannot be done in an one-size-fits-all approach, nor can <a href="https://blog.mozilla.org/netpolicy/2019/04/10/uk_online-harms/" rel="noreferrer noopener" target="_blank">regulation be made</a> with only the tech incumbents in mind. While platforms like YouTube can comfortably <a href="https://www.bmjv.de/SharedDocs/Pressemitteilungen/DE/2017/03142017_Monitoring_SozialeNetzwerke.html" rel="noreferrer noopener" target="_blank">remove</a> criminal prohibited content within a span of 24 hours, this still can place a large burden on smaller companies, who may not have the necessary resources to comply within this timeframe. There are a few unintended consequences that would arise out of this situation.</p>
<p style="text-align: justify; ">One, sanctions under the Act, which would include both organisational ramifications like website blocking (under section 69A of the Act) as well as individual liability, would affect the smaller intermediaries more than it would affect the bigger ones. A bigger intermediary like Facebook may be able to withstand a large fine in lieu of its failure to control, say, hate speech on its platform. That may not be true for a smaller online marketplace, or even a smaller online social media site, targeted towards a very specific community. This compliance mechanism, accordingly, may just go on to strengthen the larger companies, and eliminating the competition from the smaller companies.</p>
<p style="text-align: justify; ">Two, intermediaries, in fear of heavy criminal sanctions would err on the side of law. This would mean that the decisions involved in determining whether a piece of content is illegal or not would be shorter, less nuanced. This would also mean that legitimate speech would also be under risk from censorship, and intermediaries would pay <a href="https://cis-india.org/internet-governance/intermediary-liability-in-india.pdf" rel="noreferrer noopener" target="_blank">less heed</a> to the technical requirements or the correct legal procedures required for content takedown.</p>
<h3 style="text-align: justify; ">Utilization of ‘automated technology’</h3>
<p style="text-align: justify; ">Another place where the Guidelines assume that all intermediaries operating in India are on the same footing is Rule 3(9). This mandates these entities to proactively monitor for ‘unlawful content’ on their platforms. Aside the unconstitutionality of this provision, this also assumes that all intermediaries would have the requisite resource to actually set up this tool and operate it successfully. YouTube’s ContentID, which began in 2007, has already seen a whopping <a href="https://www.blog.google/outreach-initiatives/public-policy/protecting-what-we-love-about-internet-our-efforts-stop-online-piracy/" rel="noreferrer noopener" target="_blank">100 million dollars investment by 2018</a>.</p>
<p style="text-align: justify; ">Funnily enough, ContentID is a tool exclusively dedicated to finding copyright violation of rights-holder, and even then, it has been proven to be not <a href="https://www.plagiarismtoday.com/2019/01/10/youtubes-copyright-insanity/" rel="noreferrer noopener" target="_blank">infallible</a>. The Guidelines’ sweeping net of ‘unlawful’ content include far many more categories than mere violations of IP rights, and the framework assumes that intermediaries would be able to set up and run an automated tool that would filter through <em>all</em> these categories of ‘unlawful content’ at one go.</p>
<h3 style="text-align: justify; ">The problems of AI</h3>
<p style="text-align: justify; ">Aside the implementation-related concerns, there are also technical challenges related with Rule 3(9). Supervised learning systems (like the one envisaged under the Guidelines) use training data sets for pro-active filtering. This means if the system is taught that for ten instances of A being the input, the output would be B, then for the eleventh time, it sees A, it would give the output B. In the lingo of content filtering, the system would be taught, for example, that nudity is bad. The next time the system encounters nudity in a picture, it would automatically flag it as ‘bad’ and violating the community standards.</p>
<p style="text-align: justify; "><a href="https://www.theguardian.com/technology/2016/sep/08/facebook-mark-zuckerberg-napalm-girl-photo-vietnam-war" rel="noreferrer noopener" target="_blank">Except, that is not how it should work</a>. For every post that is under the scrutiny of the platform operators, numerous nuances and contextual cues act as mitigating factors, none of which, at this point, would be<a href="https://scholarship.law.nd.edu/cgi/viewcontent.cgi?referer=https://www.google.co.in/&httpsredir=1&article=1704&context=ndlr" rel="noreferrer noopener" target="_blank">understandable</a> by a machine.</p>
<p style="text-align: justify; ">Additionally, the training data used to feed the system <a href="https://www.cmu.edu/dietrich/philosophy/docs/london/IJCAI17-AlgorithmicBias-Distrib.pdf" rel="noreferrer noopener" target="_blank">can be biased</a>. A self-driving car who is fed training data from only one region of the country would learn the customs and driving norms of that particular region, and not the patterns that apply across the intended purpose of driving throughout the country.</p>
<p style="text-align: justify; ">Lastly, it is not disputed that bias would be completely eliminated in case the content moderation was undertaken by a human. However, the difference between a human moderator and an automated one, would be that there would be a measure of accountability in the first one. The decision of the human moderator can be disputed, and the moderator would have a chance to explain his reasons for the removal. Artificial intelligence (“AI”) is identified by the algorithmic ‘<a href="http://raley.english.ucsb.edu/wp-content/Engl800/Pasquale-blackbox.pdf" rel="noreferrer noopener" target="_blank">black box</a>’ that processes inputs, and generates usable outputs. Implementing workable accountability standards for this system, including figuring out appeal and grievance redressal mechanisms in cases of dispute, are all problems that the regulator must concern itself with.</p>
<p style="text-align: justify; ">In the absence of any clarity or revision, it seems unlikely that the provision would actually ever see full implementation. Neither would the intermediaries know what kind of ‘automated technology’ they are supposed to use for filtering ‘unlawful content’, nor would there be any incentives for them to actually deploy this system effectively for their platforms.</p>
<h3 style="text-align: justify; ">What can be done?</h3>
<p style="text-align: justify; ">First, more research is needed to understand the effect of compliance timeframes on the accuracy of content takedown. Several jurisdictions are operating now on different timeframes of compliance, and it would be a far more holistic regulation should the government consider the dialogue around each of them and see what it means for India.</p>
<p style="text-align: justify; ">Second, it might be useful to consider the concept of an independent regulator as an alternative and as a compromise between pure governmental regulation (which is more or less what the system is) or self-regulation (which the Guidelines, albeit problematically, also espouse through Rule 3(9)).</p>
<p style="text-align: justify; ">The <a href="https://www.gov.uk/government/consultations/online-harms-white-paper" rel="noreferrer noopener" target="_blank">UK White Paper on Harms</a>, a piece of important document in the system of liability overhaul, proposes an arms-length regulator who would be responsible for drafting codes of conduct for online companies and responsible for their enforcement. While the exact merits of the system is still up for debate, the concept of having a separate body to oversee, formulate and also possibly<a href="https://medium.com/adventures-in-consumer-technology/regulating-social-media-a-policy-proposal-a2a25627c210" rel="noreferrer noopener" target="_blank">arbitrate</a> disputes regarding content removal, is finding traction in several parallel developments.</p>
<p style="text-align: justify; ">One of the Transatlantic Working Group Sessions seem to discuss this idea in terms of having an ‘<a href="https://medium.com/whither-news/proposals-for-reasonable-technology-regulation-and-an-internet-court-58ac99bec420" rel="noreferrer noopener" target="_blank">internet court</a>’ for illegal content regulation. This would have the noted advantage of a) formulating norms of online content in a transparent, public fashion, something previously done behind closed doors of either the government or the tech incumbents and b) having specially trained professionals who would be able to dispose of matters in an expeditious manner.</p>
<p style="text-align: justify; ">India is not unfamiliar to the idea of specialized tribunals, or quasi-judicial bodies for dealing with specific challenges. In 2015, for example, the Government of India passed the Commercial Courts Act, by which specific courts were tasked to deal with matters of very large value. This is neither an isolated instance of the government choosing to create new bodies for dealing with a specific problem, nor would it be inimitable in the future.</p>
<p style="text-align: justify; ">There is no<a href="https://www.thehindubusinessline.com/opinion/resurrecting-the-marketplace-of-ideas/article26313605.ece" rel="noreferrer noopener" target="_blank"> silver bullet</a> when it comes to moderation of content on the web. However, in light of these parallel convergence of ideas, the appeal of an independent regulatory system as a sane compromise between complete government control and <em>laissez-faire</em>autonomy, is worth considering.</p>
<p>
For more details visit <a href='https://cis-india.org/internet-governance/blog/cyber-brics-august-12-2019-torsha-sarkar-rethinking-the-intermediary-liability-regime-in-india'>https://cis-india.org/internet-governance/blog/cyber-brics-august-12-2019-torsha-sarkar-rethinking-the-intermediary-liability-regime-in-india</a>
</p>
No publishertorshaInternet GovernanceIntermediary LiabilityArtificial Intelligence2019-08-16T01:49:47ZBlog Entry