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To be Counted When They Count You: Words of Caution for the Gender Data Revolution
https://cis-india.org/raw/to-be-counted-when-they-count-you-words-of-caution-for-the-gender-data-revolution
<b>In 2015, after the announcement of the SDGs or Sustainable Development Goals, a new global developmental framework through the year 2030, the United Nations described data as the “lifeblood of decision-making and the raw material for accountability” for the purpose of realizing these developmental goals. This curious yet key link between these new developmental goals and the use of quantitative data for agenda setting invited a flurry of big data-led initiatives such as but not limited to Data2X, that sought to further strengthen and solidify the relationship between ‘Big Development’ and ‘Big Data.’</b>
<p style="text-align: justify; ">One of those SDG goals (Goal 5) prioritizes gender equality and empowerment of women and girls not only as a standalone goal but also as a crucial factor to realizing the other goals. In response, several academic and non-profit initiatives have begun to interpret and conduct data-led gendered development or the “gender data revolution”. As with other data discourses, the gender-data discourse is also one of ‘speed’, charging ahead using a variety of quantitative and visualization approaches to reveal and eventually solve gendered problems of development.</p>
<p style="text-align: justify; ">These interventions also invite some classical critical questions: who is setting the agenda for the gender data revolution and who are its imagined subjects? How are questions of participation and asymmetries of power in developmental research being addressed? How does the gender data revolution address the situatedness as well as incompleteness of data records in the Global South (where most sites of intervention are)? Speaking specifically to the theme of this special issue (‘cross-cultural feminist technologies’), this paper demonstrates how the welfarist discourse of data-led gender development is, in fact, assembled through the overwhelming enumeration of female-identifying bodies in the Global South.</p>
<p style="text-align: justify; ">The paper offers critical historical insights from the fields of international development, anthropology, and postcolonial history to caution against both, the possible harms of gender disaggregated datafication as well as the consequences of non-participatory datafication of women, the subjects of the gender data revolution.</p>
<p style="text-align: justify; ">Read the full paper <strong><a href="https://cis-india.org/raw/to-be-counted-when-they-count-you.pdf" class="internal-link">here</a></strong>.</p>
<p style="text-align: justify; ">This study was undertaken as part of the Big Data for Development network supported by the International Development Research Centre, Canada, and is shared under Creative Commons Attribution 4.0 International license.</p>
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<p style="text-align: justify; "><span class="discreet">The views and opinions expressed on this page are those of their individual authors. Unless the opposite is explicitly stated, or unless the opposite may be reasonably inferred, CIS does not subscribe to these views and opinions which belong to their individual authors. CIS does not accept any responsibility, legal or otherwise, for the views and opinions of these individual authors. For an official statement from CIS on a particular issue, please contact us directly.</span></p>
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For more details visit <a href='https://cis-india.org/raw/to-be-counted-when-they-count-you-words-of-caution-for-the-gender-data-revolution'>https://cis-india.org/raw/to-be-counted-when-they-count-you-words-of-caution-for-the-gender-data-revolution</a>
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No publishernoopurRAW PublicationsBig DataResearchers at WorkBD4DRAW ResearchBig Data for Development2022-02-01T01:06:08ZBlog EntryIs India's Digital Health System Foolproof?
https://cis-india.org/raw/is-indias-digital-health-system-foolproof
<b>This contribution by Aayush Rathi builds on "Data Infrastructures and Inequities: Why Does Reproductive Health Surveillance in India Need Our Urgent Attention?" (by Aayush Rathi and Ambika Tandon, EPW Engage, Vol. 54, Issue No. 6, 09 Feb, 2019) and seeks to understand the role that state-run reproductive health portals such as the Mother and Child Tracking System (MCTS) and the Reproductive and Child Health will play going forward. The article critically outlines the overall digitised health information ecosystem being envisioned by the Indian state.</b>
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<h4>This article was first published in <a href="https://www.epw.in/engage/article/indias-digital-health-paradigm-foolproof" target="_blank">EPW Engage, Vol. 54, Issue No. 47</a>, on November 30, 2019</h4>
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<p>Introduced in 2013 and subsequently updated in 2016, the Ministry of Health and Family Welfare (MHFW) published a document laying out the standards for electronic health records (EHRs). While there exist varying interpretations of what constitutes as EHRs, some of its characteristics include electronic medical records (EMRs) of individual patients, arrangement of these records in a time series, and inter-operable linkages of the EMRs across various healthcare settings (Häyrinen et al 2008; OECD 2013).</p>
<p>To work effectively, EHRs are required to be highly interoperable so that they can facilitate exchange among health information systems (HIS) across participating hospitals. For this, the Integrated Health Information Platform (IHIP) is being developed so as to assimilate data from various registries across India and provide real-time information on health surveillance (Krishnamurthy 2018).</p>
<h3><strong>EHR Implementation: Unpacking the (Dis)incentive Structure</strong></h3>
<p>As the implementation of EHR standards is voluntary, anecdotal evidence indicates that their uptake in the Indian healthcare sector has been very slow. Here, the opposition of the Indian Medical Association to the Clinical Establishments (Registration and Regulation) Act, 2010, resulting in nationwide protests and subsequent legal challenges to the act, is instructive. To start with, the act prescribes the minimum standards that have to be maintained by clinical establishments which are registered or seeking registration (itself mandatory to run a clinic under the act) <strong>[1]</strong>. Further, Rule 9(ii) of the Clinical Establishments (Registration and Regulation) Rules, 2012, drafted under the act, requires clinical establishments to maintain EMRs or EHRs for every patient. However, with health being a state subject in India, the act has only been enforced in 11 states and all union territories except the National Capital Territory of Delhi (Jyoti 2018). The resistance to the act is largely due to protests by stakeholders from within the medical fraternity regarding its adverse impact on small- and medium-sized hospitals (Jyoti 2018).</p>
<h3><strong>Contextualising Clinicians' Inertia</strong></h3>
<p>Another major impediment to the adoption of EHRs by health service providers is reluctance on the part of individual physicians to transition to an EHR system. This is because compliance with EHR standards requires physicians to input clinical notes themselves.</p>
<p>Comparing the greater patient load faced by doctors in India vis-à-vis the United States (US), the chief medical officer of an EHR vendor in India estimates that the average Indian doctor sees about 40–60 patients a day, whereas in the US it may be around 18–20 patients (Kandhari 2017). This is suggestive of the wide disparity in the number of physicians per 1,000 citizens in both countries (World Bank nd). Given this, doctors in India tend to be more problem-oriented, time-strapped, and pay less attention to clinical notes (Kandhari 2017). Thus, clinicians will consider a system to be efficient only if the system reduces their documentation time, even if the time savings do not translate into better patient care (Allan and Englebright 2000). The inability of EHRs to help reduce documentation time deters clinicians from supporting their implementation (Poon et al 2004). Additionally, research done in the United States indicates that there is no evidence to suggest that an information system helps save time expended by clinicians on documentation (Daly et al 2002). Moreover, the use of an information system is stated to have had no impact on patient care, but doctors have acknowledged its use for research purposes (Holzemer and Henry 1992).</p>
<h3><strong>Prohibitive Costs of Implementation</strong></h3>
<p>While national-level EHRs have been adopted globally, their distribution across countries is telling. In a survey published in 2016 by the World Health Organization, wealthier countries were over-represented, with two-thirds from the upper-middle-income group and roughly half from the high-income countries having introduced EHR systems. On the other hand, only a third of lower-middle-income countries and 15% of low-income countries reported having implemented EHRs (World Health Organization 2016). A major reason for the slow uptake of EHRs in poorer countries is likely to be funding as EHR implementation requires considerable investment, with most projects averaging several million dollars (US) (Kuperman and Gibson 2003). Although various funding models for EHR implementation are being utilised globally, it is unclear what model will be adopted in India to bring in private healthcare service providers within its ambit (Healthcare Information and Management Systems Society 2007). This absence of funding direction for private actors poses to be a significant impediment in the integration of private databases with other public ones.</p>
<p>In general, poorer countries are also more likely to have less developed infrastructure and health Information and Communication Technology (ICT) to support EHR systems. Besides this, they not only lack the capacity and human resources required to develop and maintain such complex systems (Tierney et al 2010; McGinn et al 2011), but training periods have also been found to be long and more costly than expected (Kovener et al 1997).</p>
<h3><strong>Socio-economic Exclusions and Cross-cultural Barriers</strong></h3>
<p>There exists scant research investigating the existing use of EHRs in India, though preliminary work is being undertaken to assess EHR implementation in other developing countries (Tierney et al 2010; Fraser et al 2005). Even in the context of developed countries, where widespread adoption of EHRs has been gaining traction for some time now, very little data exists around implementation and efficacy in underserved regions and communities. This is further problematised as clinical information systems and user populations also vary in their characteristics and, for this reason, individual studies are unable to identify common trends that would predict EHR implementation success.</p>
<p>Underserved settings may lack the infrastructure needed to support EHRs. The risk of exclusion already exists in parts such as difficulties inherent in delivering care to remote locations, barriers related to cross-cultural communication, and the pervasive problem of providing care in the setting of severe resource constraints. Equally important is the fact that health workers who already report significant existing impediments in their delivery of routine care in these settings do not necessarily see EHRs as being useful in catering to the specific needs of their patient population (Bach et al 2004). Moreover, experience with EHRs also reveals that there are cultural barriers to capturing accurate data (Miklin et al 2019). What this could mean is that stigma associated with the diagnosis of conditions such as HIV/AIDS or induced abortions will result in their under-reporting even within EHR systems.</p>
<h3><strong>Stick or Twist?</strong></h3>
<p>Other modalities have been devised to nudge healthcare providers into adopting EHR standards voluntarily. The National Accreditation Board for Hospitals and Healthcare Providers (NABH), India, a constituent board of the Quality Council of India (a public–private initiative), has been reported to have incorporated the EHR standards within its accreditation matrix. NABH accreditation, considered an indicator of high quality patient care, is highly sought–after by hospitals in India in order to attract medical tourists as well as insurance companies: two prominent sources of income for hospitals (Kandhari 2017). Additionally, NABH accreditation is valid for a term of three years, thus requiring hospitals seeking to renew their accreditation to adopt EHR standards as well.</p>
<p>Another commercial use of EHR has been in health insurance. The Federation of Indian Chambers of Commerce and Industry (FICCI) and the Insurance Regulatory and Development Authority (IRDAI) have both voiced their support for expediting the implementation of the EHR standards (EMR Standards Committee 2013). Both, the FICCI and IRDAI have placed emphasis on adopting EHRs, seeing it as a necessary move for formalising the health insurance industry (FICCI 2015). They have also had representation on the committee that sent recommendations to the MHFW on the first version of the EHR standards in 2013 (FICCI 2015). FICCI had additionally played a coordination role in having the recommendations framed for the 2013 EHR standards.</p>
<h3><strong>Fluid Data Objectives</strong></h3>
<p>The push for EHR implementation is emblematic of a larger shift in the healthcare approach of the Indian state, that of an indirect targeting of demand-side financing by plugging data inefficiencies in health insurance.</p>
<p>The draft National Health Policy (NHP), published in 2015, reflected the mandate of the Ministry of Health and Family Welfare to strengthen the public health system by creating a right to healthcare legislation and reaching a public spend of 2.5% of the gross domestic product by 2018. The final version of the NHP, published in 2017, however, codified a shift in healthcare policy by focusing on strategic purchasing of secondary and tertiary care services from the private sector and a publicly funded health insurance model.</p>
<p>In line with the vision of the NHP 2017, in February 2018, the Union Minister for Finance and Corporate Affairs, Arun Jaitley, announced two major initiatives as a part of the government’s Ayushman Bharat programme (Ministry of Finance 2018). Administered under the aegis of the Ministry of Health and Family Welfare, these initiatives are intended to improve access to primary healthcare through the creation of 150,000 health and wellness centres as envisioned under the NHP 2017, and improve access to secondary and tertiary healthcare for over 100 million vulnerable families by providing insurance cover of up to ₹ 500,000 per family per year under the Pradhan Mantri–Rashtriya Swasthya Suraksha Mission/National Health Protection Scheme (PM–RSSM/NHPS) (Ministry of Health and Family Welfare 2018). The NHPS, modelled along the lines of the Affordable Care Act in the US, was later rebranded as the Pradhan Mantri–Jan Arogya Yojana (PM-JAY) at the time of its launch in September 2018. It is claimed to be the world’s largest government-funded healthcare programme and is intentioned to provide health insurance coverage for vulnerable sections in lieu of the Sustainable Development Goal-3 (National Health Authority nd).</p>
<p>To enable the implementation of the Ayushman Bharat programme, the NITI Aayog then proposed the creation of a supply-side digital infrastructure called National Health Stack (NHS) (NITI Aayog 2018). As outlined in the consultation and strategy paper, the NHS is “built for NHPS, but beyond NHPS.” The NHS seeks to leverage the digitisation push through IndiaStack, which seeks to digitalise “any large-scale health insurance program, in particular, any government-funded health care programs.” The synergy is clear, with the NHPS scheme also aiming to be “cashless and paperless at public hospitals and empanelled private hospitals" (National Health Authority nd) <strong>[2]</strong>.</p>
<p>The NHS is also closely aligned with the NHP 2017, which draws attention to leveraging technologies such as big data analytics on data stored in universal registries. The Vision document for the NHS emphasises the fragmented nature of health data as an impediment to reducing inequities in healthcare provision. The NHS, then, also seeks to be the master repository of health data akin to the IHIP. By creating a base layer of registries containing information about various actors involved in the healthcare supply chain (providers such as hospitals, beneficiaries, doctors, insurers and Accredited Social Health Activists), it potentially allows for recording of data from both public and private sector entities, plugging a significant gap in the coverage of the HIS currently implemented in India. With the provision of open, pullable APIs, the NHS also shares the motivations of the IndiaStack to monetise health data.</p>
<p>A key component of the proposed NHS is the Coverage and Claims platform, which the vision document describes as “provid[ing] the building blocks required to implement any large-scale health insurance program, in particular, any government-funded healthcare programs. This platform has the transformative vision of enabling both public and private actors to implement insurance schemes in an automated, data-driven manner through open APIs " (NITI Aayog2018). A post on the iSPIRT website further explains the centrality of this Coverage and Claims platform in enabling a highly personalised medical insurance market in India: “This component will not only bring down the cost of processing a claim but ... increased access to information about an individual’s health and claims history ... will also enable the creation of personalised, sachet-sized insurance policies." These data-driven customised insurance policies are expected to generate “care policies that are not only personalized in nature but that also incentivize good healthcare practices amongst consumers and providers … [and] use of techniques from microeconomics to manage incentives for care providers, and those from behavioural economics to incentivise consumers" (Productnation Network 2019). The Coverage and Claims platform, and especially the Policy (generation) Engine that it will contain, is aimed at intensive financialisation of personal healthcare expenses, and extensive experiments with designing personalised nudges to shape the demand behaviour of consumers.</p>
<p>The imagination of healthcare the NHS demonstrates is one where broadening health insurance coverage is equated to providing equitable healthcare and as a panacea for the public healthcare sector. The first phase of this push towards better healthcare provision is to focus on contextualising the historical socio-economic divide. The next phase is characterised by digitalisation: the introduction of ICT to bridge the socio-economic divide in healthcare provision. In this process, the resulting data divide has been invisibilised in reframing better healthcare as an insurance problem for which data needs to be generated. Each policy innovation is then characterised by further marginalisation of those that were originally identified as underserved. This is a result of increasing repercussions of the data-divide, with access to benefits increasingly being mediated by technology.</p>
<h3><strong>Concluding Remarks</strong></h3>
<blockquote>The idea that any person in India can go to any health service provider/ practitioner, any diagnostic center or any pharmacy and yet be able to access and have fully integrated and always available health records in an electronic format is not only empowering but also the vision for efficient 21st century healthcare delivery.<br />
— Ministry of Health and Family Welfare, Electronic Health Record Standards For India (2013)</blockquote>
<p>The objective of health data collection has evolved over the course of the institution of the HIS in 2011, to the development of the NHPS and National Health Policy in 2017. What began as a solution to measure and address gaps in access and quality in healthcare provisioning through data analysis has morphed into data centralisation and insurance coverage. Shifting goalposts can also be found in the objectives behind introducing digital systems to collect data.</p>
<p>In recent iterations of the healthcare imaginary, such as the IHIP and the NHS, data ownership by the beneficiaries is stressed upon. In the absence of a rights-based framework dictating the use of data, the role of ownership should be interrogated, especially in the context of a prevalent data divide (Tisne 2019). The legitimisation of data capture can be seen in the emergence of opt-in models of consent, data fiduciaries managing consent on the data subject’s behalf, etc. (Zuboff 2019).</p>
<p>This framing forecloses a discussion about the quality and kind of data being used. The push towards datafication needs to be questioned for its re-indexing of categorical meaning away from the complexities of narrative, context and history (Cheney-Lippold 2018). Instead, the proposed solution is one that stores datafied elements within a closed set (reproductive health= [abortion, aids, contraceptive,...vaccination, womb]). While this set may be editable, so new interpretations can be codified, it inherently remains stable, assuming a static relationship between words and meaning. Health is then treated as having an empirically definable meaning, thus losing the dynamism of what the health and wellness discourse could entail.</p>
<p>It has been historically demonstrated in the Indian context that multiple tools and databases for health data management are a barrier to an efficient HIS. However, generating centralised or federated databases without addressing concerns in data flows, quality, uses in existing data structures, and the digital divide across health workers and beneficiaries alike will lead to the amplification of existing exclusions in data and, consequently, service provisioning.</p>
<h3><strong>Acknowledgements</strong></h3>
<p>The author would like to express his gratitude to Sumandro Chattapadhyay and Ambika Tandon for their inputs and editorial work on this contribution. This work was supported by the Big Data for Development Network established by International Development Research Centre (Canada).</p>
<h3><strong>Notes</strong></h3>
<p><strong>[1]</strong> Section 2 (a) of the Clinical Establishments (Registration and Regulation) Act, 2010: A hospital, maternity home, nursing home, dispensary, clinic, sanatorium or institution by whatever name called that offers services, facilities requiring diagnosis, treatment or care for illness, injury, deformity, abnormality or pregnancy in any recognised system of medicine established and administered or maintained by any person or body of persons, whether incorporated or not.</p>
<p><strong>[2]</strong> The National Health Stack, then, is the latest manifestation of the Indian government’s push for a “Digital India.” A key component of Digital India has been e-governance, financial inclusion, and digitisation of transaction services. The nudge towards cashless modes of transaction and delivery, also accelerated by India’s demonetisation drive in November 2016, has led to rapid uptake of digital payment services in particular, and that of the IndiaStack initiative in general. Developed by iSPIRT, IndiaStack (https://indiastack.org/) aspires to transform service delivery by public and private actors alike through its “presence-less, paperless, and cashless” mandate.</p>
<h3><strong>References</strong></h3>
<p>Allan, J and Jane Englebright (2000): “Patient-Centered Documentation,” JONA: The Journal of Nursing Administration, Vol 30, No 2, pp 90–95.</p>
<p>Bach, Peter, Hoangmai Pham, Deborah Schrag, Ramsey Tate and J Lee Hargraves (2004): “Primary Care Physicians Who Treat Blacks and Whites,” New England Journal of Medicine, Vol 351, pp 575–84.</p>
<p>Cheney-Lippold, John (2018): We Are Data: Algorithms and the Making of Our Digital Selves, New Delhi: Sage.</p>
<p>Daly, Jeanette, Buckwalter Kathleen and Meridean Maas (2002): “Written and Computerized Care Plans,” Journal of Gerontological Nursing, Vol 28, No 9, pp 14–23.</p>
<p>EMR Standards Committee (2013): “Recommendations on Electronic Medical Records Standards in India,” Ministry of Health and Family Welfare, Government of India, New Delhi, https://mohfw.gov.in/sites/default/files/24539108839988920051EHR%20Standards-v5%20Apr%202013.pdf.</p>
<p>Federation of Indian Chambers of Commerce and Industry (2015): "A Guiding Framework for OPD and Preventive Health Insurance in India: Supply and Demand Side Analysis," http://ficci.in/spdocument/20678/P&P-helath-insurance.pdf.</p>
<p>Fraser, Hamish, Paul Biondich, Deshendran Moodley, Sharon Choi, Burke Mamlin and Peter Szolovits (2005): “Implementing Electronic Medical Record Systems in Developing Countries,” Journal of Innovation in Health Informatics, Vol 13 No 2, pp 83–95.</p>
<p>Häyrinen, Kristiina, Kaija Saranto and Pirkko Nykänen (2008): “Definition, Structure, Content, Use and Impacts of Electronic Health Records: A Review of the Research Literature,” International Journal of Medical Informatics, Vol 77, No 5, pp 291–304.</p>
<p>Healthcare Information and Management Systems Society (2007): “Electronic Health Records: A Global Perspective,” http://www.providersedge.com/ehdocs/ehr_articles/Electronic_Health_Records-A_Global_Perspective-Exec_Summary.pdf.</p>
<p>Holzemer, William and S B Henry (1992): “Computer-supported Versus Manually-generated Nursing Care Plans: A Comparison of Patient Problems, Nursing Interventions, and AIDS Patient Outcomes,” Computers in Nursing, Vol 10 No 1, pp 19–24.</p>
<p>Jha, Ashish, Catherine DesRoches, Eric Campbell, Karen Donelan, Sowmya Rao, Timothy Ferris, Alexandra Shields, Sarah Rosenbaum and David Blumenthal (2009): "Use of Electronic Health Records in U.S. Hospitals," New England Journal of Medicine, Vol 360 No 16, pp 1628–1638.</p>
<p>Jyoti, Archana (2018): “States Give Clinical Establishment Act Cold Shoulder," Pioneer, https://www.dailypioneer.com/2018/india/states-give-clinical-establishment-act-cold-shoulder.html.</p>
<p>Kandhari, Ruhi (2017): “Why a Backdoor Push Towards eHealth,” Ken, https://the-ken.com/story/why-backdoor-push-towards-ehealth/.</p>
<p>Kovner, Christine, Lynda Schuchman and Catherin Mallard (1997): “The Application of Pen-Based Computer Technology to Home Health Care,” CIN: Computers, Informatics and Nursing, Vol 15, No 5, pp 237–44.</p>
<p>Krishnamurthy, R (2018): “Integrated Health Information Platform for Integrated Disease Surveillance Program,” Training of the Trainer Workshop, World Health Organisation, New Delhi, https://idsp.nic.in/WriteReadData/IHIP/IHIP%20ToT-Overview-Presentation.pdf.</p>
<p>Kuperman, Gilad and Richard Gibson (2003): “Computer Physician Order Entry: Benefits, Costs, and Issues,” Annals of Internal Medicine, Vol 139 No 1, pp 31–9.</p>
<p>Leung, Gabriel, Philip Yu, Irene Wong, Janice Johnston and Keith Tin (2003): “Incentives and Barriers That Influence Clinical Computerization in Hong Kong: A Population-based Physician Survey,” Journal of the American Medical Informatics Association, Vol 10 No 2, pp 201–12.</p>
<p>McGinn Carrie Anna, Sonya Grenier, Julie Duplantie, Nicola Shaw, Claude Sicotte, Luc Mathieu, Yvan Leduc, France Légaré and Marie-Pierre Gagnon (2011): “Comparison of User Groups' Perspectives of Barriers and Facilitators to Implementing Electronic Health Records: A Systematic Review,” BMC Medicine, Vol 9 No 46.</p>
<p>Miklin, Daniel, Sameera Vangara, Alan Delamater and Kenneth Goodman (2019): “Understanding of and Barriers to Electronic Health Record Patient Portal Access in a Culturally Diverse Pediatric Population,” JMIR Medical Informatics, Vol 7, No 2.</p>
<p>Ministry of Finance (2018): “Budget 2018-19: Speech of Arun Jaitley,” New Delhi, https://www.indiabudget.gov.in/ub2018-19/bs/bs.pdf.</p>
<p>Ministry of Health and Family Welfare, Government of India (2008): "4 Years of Transforming India-Healthcare for All," New Delhi. https://mohfw.gov.in/ebook2018/gvtbook.html.</p>
<p>Ministry of Health and Family Welfare, Government of India (2013): “Electronic Health Record Standards For India,” Government of India, New Delhi, https://www.nhp.gov.in/NHPfiles/ehr_2013.pdf.</p>
<p>Ministry of Health and Family Welfare, Government of India (2017): Request for Proposal: Development and Implementation of Integrated Health Information Platform (IHIP), Centre for Health Informatics, National Institute of Health and Family Welfare, New Delhi, https://nhp.gov.in/NHPfiles/IHIP_RFP%20.pdf.</p>
<p>Ministry of Health and Family Welfare, Government of India (2018): “IDSP Segment of Integrated Health Information Platform,” New Delhi, https://idsp.nic.in/index4.php?lang=1&level=0&linkid=454&lid=3977.</p>
<p>National Health Authority (nd): “About Pradhan Mantri Jan Arogya Yojana (PM-JAY) | Ayushmaan Bharat,” https://www.pmjay.gov.in/about-pmjay.</p>
<p>NITI Aayog (2018): “National Health Stack- Strategy and Approach,” NITI Aayog, New Delhi, http://www.niti.gov.in/writereaddata/files/document_publication/NHS-Strategy-and-Approach-Document-for-consultation.pdf.</p>
<p>Organisation for Economic Co-operation and Development (2013): “Strengthening Health Information Infrastructure for Health Care Quality Governance: Good Practices, New Opportunities and Data Privacy Protection Challenges,” OECD Health Policy Studies, Paris, OECD Publishing, https://read.oecd-ilibrary.org/social-issues-migration-health/strengthening-health-information-infrastructure-for-health-care-quality-governance_9789264193505-en.</p>
<p>Poon, Eric, David Blumenthal, Tonushree Jaggi, Melissa Honour, David Bates and Rainu Kaushal (2004): “Overcoming Barriers to Adopting and Implementing Computerized Physician Order Entry Systems in U.S. Hospitals,” Health Affairs, Vol 23 No 4, pp 184–90.</p>
<p>Productnation Network (2019): “India’s Health Leapfrog–Towards A Holistic Healthcare Ecosystem,” iSpirt, https://pn.ispirt.in/towards-a-holistic-healthcare-ecosystem/.</p>
<p>Rathi, Aayush and Ambika Tandon (2019): “Data Infrastructures and Inequities: Why Does Reproductive Health Surveillance in India Need Our Urgent Attention?” EPW Engage, https://www.epw.in/engage/article/data-infrastructures-inequities-why-does-reproductive-health-surveillance-india-need-urgent-attention.</p>
<p>Sequist, Thomas, Theresa Cullen, Howard Hays, Maile Taualii, Steven Simon, and David Bates (2007): “Implementation and Use of an Electronic Health Record Within the Indian Health Service,” Journal of the American Medical Informatics Association, Vol 14, No 2, pp 191–97.</p>
<p>World Bank (nd): Physicians (per 1,000 people) | Data, https://data.worldbank.org/indicator/SH.MED.PHYS.ZS.</p>
<p>Tierney, William et al. (2010): “Experience Implementing Electronic Health Records in Three East African Countries,” Studies in Health Technology and Informatics, Vol 160, No 1, pp 371–75.</p>
<p>Tisne, Martin (2018): “It’s Time for a Bill of Data Rights,” MIT Technology Review, https://www.technologyreview.com/s/612588/its-time-for-a-bill-of-data-rights/.</p>
<p>World Health Organization (2016): “Global Diffusion of eHealth: Making Universal Health Coverage Achievable,” https://apps.who.int/iris/bitstream/handle/10665/252529/9789241511780-eng.pdf;jsessionid=9DD5F8603C67EEF35549799B928F3541?sequence=1.</p>
<p>Zuboff, Soshana (2019): The Age of Surveillance Capitalism, New York: PublicAffairs.</p>
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For more details visit <a href='https://cis-india.org/raw/is-indias-digital-health-system-foolproof'>https://cis-india.org/raw/is-indias-digital-health-system-foolproof</a>
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No publisheraayushEHRBig DataBig Data for DevelopmentResearchBD4DHealthcareResearchers at Work2019-12-30T17:58:00ZBlog EntryThe Mother and Child Tracking System - understanding data trail in the Indian healthcare systems
https://cis-india.org/internet-governance/blog/privacy-international-ambika-tandon-october-17-2019-mother-and-child-tracking-system-understanding-data-trail-indian-healthcare
<b>Reproductive health programmes in India have been digitising extensive data about pregnant women for over a decade, as part of multiple health information systems. These can be seen as precursors to current conceptions of big data systems within health informatics. In this article, published by Privacy International, Ambika Tandon presents some findings from a recently concluded case study of the MCTS as an example of public data-driven initiatives in reproductive health in India. </b>
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<h4>This article was first published by <a href="https://privacyinternational.org/news-analysis/3262/mother-and-child-tracking-system-understanding-data-trail-indian-healthcare" target="_blank">Privacy International</a>, on October 17, 2019</h4>
<h4>Case study of MCTS: <a href="https://cis-india.org/raw/big-data-reproductive-health-india-mcts" target="_blank">Read</a></h4>
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<p>On October 17th 2019, the UN Special Rapporteur (UNSR) on Extreme Poverty and Human Rights, Philip Alston, released his thematic report on digital technology, social protection and human rights. Understanding the impact of technology on the provision of social protection – and, by extent, its impact on people in vulnerable situations – has been part of the work the Centre for Internet and Society (CIS) and Privacy International (PI) have been doing.</p>
<p>Earlier this year, <a href="https://privacyinternational.org/advocacy/2996/privacy-internationals-submission-digital-technology-social-protection-and-human" target="_blank">PI responded</a> to the UNSR's consultation on this topic. We highlighted what we perceived as some of the most pressing issues we had observed around the world when it comes to the use of technology for the delivery of social protection and its impact on the right to privacy and dignity of benefit claimants.</p>
<p>Among them, automation and the increasing reliance on AI is a topic of particular concern - countries including Australia, India, the UK and the US have already started to adopt these technologies in digital welfare programmes. This adoption raises significant concerns about a quickly approaching future, in which computers decide whether or not we get access to the services that allow us to survive. There's an even more pressing problem. More than a few stories have emerged revealing the extent of the bias in many AI systems, biases that create serious issues for people in vulnerable situations, who are already exposed to discrimination, and made worse by increasing reliance on automation.</p>
<p>Beyond the issue of AI, we think it is important to look at welfare and automation with a wider lens. In order for an AI to function it needs to be trained on a dataset, so that it can understand what it is looking for. That requires the collection large quantities of data. That data would then be used to train and AI to recognise what fraudulent use of public benefits would look like. That means we need to think about every data point being collected as one that, in the long run, will likely be used for automation purposes.</p>
<p>These systems incentivise the mass collection of people's data, across a huge range of government services, from welfare to health - where women and gender-diverse people are uniquely impacted. CIS have been looking specifically at reproductive health programmes in India, work which offers a unique insight into the ways in which mass data collection in systems like these can enable abuse.</p>
<p>Reproductive health programmes in India have been digitising extensive data about pregnant women for over a decade, as part of multiple health information systems. These can be seen as precursors to current conceptions of big data systems within health informatics. India’s health programme instituted such an information system in 2009, the Mother and Child Tracking System (MCTS), which is aimed at collecting data on maternal and child health. The Centre for Internet and Society, India, <a href="https://cis-india.org/raw/big-data-reproductive-health-india-mcts" target="_blank">undertook a case study of the MCTS</a> as an example of public data-driven initiatives in reproductive health. The case study was supported by the <a href="http://bd4d.net/" target="_blank">Big Data for Development network</a> supported by the International Development Research Centre, Canada. The objective of the case study was to focus on the data flows and architecture of the system, and identify areas of concern as newer systems of health informatics are introduced on top of existing ones. The case study is also relevant from the perspective of Sustainable Development Goals, which aim to rectify the tendency of global development initiatives to ignore national HIS and create purpose-specific monitoring systems.</p>
<p>After being launched in 2011, 120 million (12 crore) pregnant women and 111 million (11 crore) children have been registered on the MCTS as of 2018. The central database collects data on each visit of the woman from conception to 42 days postpartum, including details of direct benefit transfer of maternity benefit schemes. While data-driven monitoring is a critical exercise to improve health care provision, publicly available documents on the MCTS reflect the complete absence of robust data protection measures. The risk associated with data leaks are amplified due to the stigma associated with abortion, especially for unmarried women or survivors of rape.</p>
<p>The historical landscape of reproductive healthcare provision and family planning in India has been dominated by a target-based approach. Geared at population control, this approach sought to maximise family planning targets without protecting decisional autonomy and bodily privacy for women. At the policy level, this approach was shifted in favour of a rights-based approach to family planning in 1994. However, targets continue to be set for women’s sterilisation on the ground. Surveillance practices in reproductive healthcare are then used to monitor under-performing regions and meet sterilisation targets for women, this continues to be the primary mode of contraception offered by public family planning initiatives.</p>
<p>More recently, this database - among others collecting data about reproductive health - is adding biometric information through linkage with the Aadhaar infrastructure. This data adds to the sensitive information being collected and stored without adhering to any publicly available data protection practices. Biometric linkage is aimed to fulfill multiple functions - primarily authentication of welfare beneficiaries of the national maternal benefits scheme. Making Aadhaar details mandatory could directly contribute to the denial of service to legitimate patients and beneficiaries - as has already been seen in some cases.</p>
<p>The added layer of biometric surveillance also has the potential to enable other forms of abuse of privacy for pregnant women. In 2016, the union minister for Women and Child Development under the previous government suggested the use of strict biometric-based monitoring to discourage gender-biased sex selection. Activists critiqued the policy for its paternalistic approach to reduce the rampant practice of gender-biased sex selection, rather than addressing the root causes of gender inequality in the country.</p>
<p>There is an urgent need to rethink the objectives and practices of data collection in public reproductive health provision in India. Rather than continued focus on meeting high-level targets, monitoring systems should enable local usage and protect the decisional autonomy of patients. In addition, the data protection legislation in India - expected to be tabled in the next session in parliament - should place free and informed consent, and informational privacy at the centre of data-driven practices in reproductive health provision.</p>
<p>This is why the systematic mass collection of data in health services is all the more worrying. When the collection of our data becomes a condition for accessing health services, it is not only a threat to our right to health that should not be conditional on data sharing but also it raises questions as to how this data will be used in the age of automation.</p>
<p>This is why understanding what data is collected and how it is collected in the context of health and social protection programmes is so important.</p>
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For more details visit <a href='https://cis-india.org/internet-governance/blog/privacy-international-ambika-tandon-october-17-2019-mother-and-child-tracking-system-understanding-data-trail-indian-healthcare'>https://cis-india.org/internet-governance/blog/privacy-international-ambika-tandon-october-17-2019-mother-and-child-tracking-system-understanding-data-trail-indian-healthcare</a>
</p>
No publisherambikaBig DataData SystemsPrivacyResearchers at WorkInternet GovernanceResearchBD4DHealthcareBig Data for Development2019-12-30T17:18:05ZBlog EntryBig Data and Reproductive Health in India: A Case Study of the Mother and Child Tracking System
https://cis-india.org/raw/big-data-reproductive-health-india-mcts
<b>In this case study undertaken as part of the Big Data for Development (BD4D) network, Ambika Tandon evaluates the Mother and Child Tracking System (MCTS) as data-driven initiative in reproductive health at the national level in India. The study also assesses the potential of MCTS to contribute towards the big data landscape on reproductive health in the country, as the Indian state’s imagination of health informatics moves towards big data.</b>
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<h4>Case study: <a href="https://github.com/cis-india/website/raw/master/bd4d/CIS_CaseStudy_AT_BigDataReproductiveHealthMCTS.pdf" target="_blank">Download</a> (PDF)</h4>
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<h3>Introduction</h3>
<p>The reproductive health information ecosystem in India comprises of a range of different databases across state and national levels. These collect data through a combination of manual and digital tools. Two national-level databases have been launched by the Ministry of Health and Family Welfare - the Health Management Information System (HMIS) in 2008, and the MCTS in 2009. 4 The MCTS focuses on collecting data on maternal and child health. It was instituted due to reported gaps in the HMIS, which records monthly data across health programmes including reproductive health. There are several other state-level initiatives on reproductive health data that have either been subsumed into, or run in
parallel with, the MCTS.</p>
<p>With this case study, we aim to evaluate the MCTS as data-driven initiative in reproductive health at the national level. It will also assess its potential to contribute towards the big data landscape on reproductive health in the country, as the Indian state’s imagination of health informatics moves towards big data. The methodology for the case study involved a desk-based review of existing literature on the use of health information systems globally, as well as analysis of government reports, journal articles, media coverage, policy documents, and other material on the MCTS.</p>
<p>The first section of this report details the theoretical framing of the case study, drawing on the feminist critique of reproductive data systems. The second section maps the current landscape of reproductive health data produced by the state in India, with a focus on data flows, and barriers to data collection and analysis at the local and national level. The case of abortion data is used to further the argument of flawed data collection systems at the
national level. Section three briefly discusses the state’s imagination of reproductive health policy and the role of data systems through a discussion on the National Health Policy, 2017 and the National Health Stack, 2018. Finally, we make some policy recommendations and identify directions for future research, taking into account the ongoing shift towards big data globally to democratise reproductive healthcare.</p>
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For more details visit <a href='https://cis-india.org/raw/big-data-reproductive-health-india-mcts'>https://cis-india.org/raw/big-data-reproductive-health-india-mcts</a>
</p>
No publisherambikaBig DataData SystemsResearchers at WorkReproductive and Child HealthResearchFeaturedPublicationsBD4DHealthcareBig Data for Development2019-12-06T04:57:55ZBlog EntryUnpacking video-based surveillance in New Delhi
https://cis-india.org/raw/unpacking-video-based-surveillance-in-new-delhi-urban-data-justice
<b>Aayush Rathi and Ambika Tandon presented at an international workshop on 'Urban Data, Inequality and Justice in the Global South', on 14 June 2019, at the University of Manchester. The agenda for the workshop and the slides from the presentation by Aayush and Ambika are available below.</b>
<p> </p>
<h4>Agenda of the workshop: <a href="https://github.com/cis-india/website/raw/master/docs/UDJWorkshop2019_Timetable.docx">Download</a> (DOCX)</h4>
<h4>Slides from the presentation: <a href="https://github.com/cis-india/website/raw/master/docs/CIS_AayushAmbika_UDJWorkshop2019_Slides.pdf">Download</a> (PDF)</h4>
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<p>The aim of the workshop was to present findings from case studies on urban data justice commissioned by the Sustainable Consumption Institute and Centre for Development Informatics at the University of Manchester, on aspects of justice in data systems in cities across the world. Aayush and Ambika presented their study on video-based surveillance in New Delhi, which was conducted across a period of 3 months earlier this year. The study aimed to assess the extent to which CCTV surveillance systems in Delhi support the needs of women in the city, including lower class women and those from informal settlements. The study will be published as a working paper by the University of Manchester in the coming months.</p>
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For more details visit <a href='https://cis-india.org/raw/unpacking-video-based-surveillance-in-new-delhi-urban-data-justice'>https://cis-india.org/raw/unpacking-video-based-surveillance-in-new-delhi-urban-data-justice</a>
</p>
No publisherAayush Rathi and Ambika TandonBig DataData JusticeSurveillanceFeaturedUrban Data JusticeResearchResearchers at Work2019-06-20T05:13:25ZBlog EntryCan data ever know who we really are?
https://cis-india.org/raw/zara-rahman-can-data-ever-know-who-we-really-are
<b>This is an excerpt from an essay by Zara Rahman, written for and published as part of the Bodies of Evidence collection of Deep Dives. The Bodies of Evidence collection, edited by Bishakha Datta and Richa Kaul Padte, is a collaboration between Point of View and the Centre for Internet and Society, undertaken as part of the Big Data for Development Network supported by International Development Research Centre, Canada.</b>
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<h4>Please read the full essay on Deep Dives: <a href="https://deepdives.in/can-data-ever-know-who-we-really-are-a0dbfb5a87a0" target="_blank">Can data ever know who we really are?</a></h4>
<h4>Zara Rahman: <a href="https://www.theengineroom.org/people/zara-rahman/" target="_blank">The Engine Room</a>, <a href="https://zararah.net/" target="_blank">Website</a>, and <a href="https://twitter.com/zararah" target="_blank">Twitter</a></h4>
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<blockquote>If I didn’t define myself for myself, I would be crunched into other people’s fantasies for me and eaten alive.<br /><em>– <a href="https://www.blackpast.org/african-american-history/1982-audre-lorde-learning-60s/" target="_blank">Audre Lorde</a></em></blockquote>
<p>The proliferation of digital data and the technologies that allow us to gather that data can be used in another way too — to allow us to define for ourselves who we are, and what we are.</p>
<p>Amidst a growing political climate of fear, mistrust and competition for resources, activists and advocates working in areas that are stigmatised within their societies often need data to ‘prove’ that what they are working on matters. One way of doing this is by gathering data through crowdsourcing. Crowdsourced data isn’t ‘representative’, as statisticians say, but gathering data through unofficial means can be a valuable asset for advocates. For example, <a href="http://readytoreport.in/" target="_blank">data collating the experiences of women</a> who have reported incidents of sexual violence to the police in India, can then be used to advocate for better police responses, and to inform women of their rights. Deservedly or not, quantifiable data takes precedence over personal histories and lived experience in getting the much-desired currency of attention.</p>
<p>And used right, quantifiable data — whether it’s crowdsourced or not — can also be a powerful tool for advocates. Now, we can use quantifiable data to prove beyond a question of a doubt that disabled people, queer people, people from lower castes, face intersecting discrimination, prejudice, and systemic injustices in their lives. It’s an unnecessary repetition in a way, because anybody from those communities could have told reams upon reams of stories about discrimination — all without any need for counting.</p>
<p>Regardless, to play within this increasingly digitised system, we need to repeat what we’ve been saying in a new, digitally-legible way. And to do that, we need to collect data from people who have often only ever been de-humanised as data subjects.</p>
<p>Artist and educator Mimi Onuoha writes about <a href="https://points.datasociety.net/the-point-of-collection-8ee44ad7c2fa#.y0xtfxi2p" target="_blank">the challenges that arise while collecting such data</a>, from acknowledging the humans behind that collection to understanding that missing data points might tell just as much of a story as the data that has been collected. She outlines how digital data means that we have to (intentionally or not) make certain choices about what we value. And the collection of this data means making human choices solid, and often (though not always) making these choices illegible to others.</p>
<p>We speak of black boxes when it comes to <a href="https://www.propublica.org/article/breaking-the-black-box-what-facebook-knows-about-you" target="_blank">the mystery choices that algorithms make</a>, but the same could be said of the many human decisions that are made in categorising data too, whether that be choosing to limit the gender drop-down field to just ‘male/female’ as with Fitbits, or a variety of apps incorrectly assuming that all people who menstruate <a href="https://medium.com/@maggied/i-tried-tracking-my-period-and-it-was-even-worse-than-i-could-have-imagined-bb46f869f45" target="_blank">also want to know about their ‘fertile window’</a>. In large systems with many humans and machines at work, we have no way of interrogating why a category was merged or not, of understanding why certain anomalies were ignored rather than incorporated, or of questioning why certain assumptions were made.</p>
<p>The only thing we can do is to acknowledge these limitations, and try to use those very systems to our advantage, building our own alternatives or workarounds, collecting our own data, and using the data that is out there to tell the stories that matter to us.</p>
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<p>
For more details visit <a href='https://cis-india.org/raw/zara-rahman-can-data-ever-know-who-we-really-are'>https://cis-india.org/raw/zara-rahman-can-data-ever-know-who-we-really-are</a>
</p>
No publishersumandroBodies of EvidenceBig DataData SystemsResearchers at WorkResearchPublicationsBD4DBig Data for Development2019-12-06T05:02:53ZBlog EntryCurating Genderlog India's Twitter handle
https://cis-india.org/internet-governance/news/curating-genderlog-indias-twitter-handle
<b>Shweta Mohandas has been nominated to curate Genderlog's Twitter handle (@genderlogindia).</b>
<p style="text-align: justify; ">Shweta Mohandas <span>will be tweeting about topics related to gender and data, more specifically around AI, big data, privacy and surveillance. To view the tweets, <a class="external-link" href="https://twitter.com/genderlogindia/status/1127892055231873024">click here</a></span></p>
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For more details visit <a href='https://cis-india.org/internet-governance/news/curating-genderlog-indias-twitter-handle'>https://cis-india.org/internet-governance/news/curating-genderlog-indias-twitter-handle</a>
</p>
No publisherAdminInternet GovernanceBig DataArtificial IntelligencePrivacy2019-05-14T14:40:08ZNews ItemData Infrastructures and Inequities: Why Does Reproductive Health Surveillance in India Need Our Urgent Attention?
https://cis-india.org/internet-governance/blog/data-infrastructures-inequities-reproductive-health-surveillance-india
<b>In order to bring out certain conceptual and procedural problems with health monitoring in the Indian context, this article by Aayush Rathi and Ambika Tandon posits health monitoring as surveillance and not merely as a “data problem.” Casting a critical feminist lens, the historicity of surveillance practices unveils the gendered power differentials wedded into taken-for-granted “benign” monitoring processes. The unpacking of the Mother and Child Tracking System and the National Health Stack reveals the neo-liberal aspirations of the Indian state. </b>
<p> </p>
<p><em>The article was first published by <a href="https://www.epw.in/engage/article/data-infrastructures-inequities-why-does-reproductive-health-surveillance-india-need-urgent-attention" target="_blank">EPW Engage, Vol. 54, Issue No. 6</a>, on 9 February 2019.</em></p>
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<h3><strong>Framing Reproductive Health as a Surveillance Question</strong></h3>
<p>The approach of the postcolonial Indian state to healthcare has been Malthusian, with the prioritisation of family planning and birth control (Hodges 2004). Supported by the notion of socio-economic development arising out of a “modernisation” paradigm, the target-based approach to achieving reduced fertility rates has shaped India’s reproductive and child health (RCH) programme (Simon-Kumar 2006).</p>
<p>This is also the context in which India’s abortion law, the Medical Termination of Pregnancy (MTP) Act, was framed in 1971, placing the decisional privacy of women seeking abortions in the hands of registered medical practitioners. The framing of the MTP act invisibilises females seeking abortions for non-medical reasons within the legal framework. The exclusionary provisions only exacerbated existing gaps in health provisioning, as access to safe and legal abortions had already been curtailed by severe geographic inequalities in funding, infrastructure, and human resources. The state has concomitantly been unable to meet contraceptive needs of married couples or reduce maternal and infant mortality rates in large parts of the country, mediating access along the lines of class, social status, education, and age (Sanneving et al 2013).</p>
<p>While the official narrative around the RCH programme transitioned to focus on universal access to healthcare in the 1990s, the target-based approach continues to shape the reality on the ground. The provision of reproductive healthcare has been deeply unequal and, in some cases, in hospitals. These targets have been known to be met through the practice of forced, and often unsafe, sterilisation, in conditions of absence of adequate provisions or trained professionals, pre-sterilisation counselling, or alternative forms of contraception (Sama and PLD 2018). Further, patients have regularly been provided cash incentives, foreclosing the notion of free consent, especially given that the target population of these camps has been women from marginalised economic classes in rural India.</p>
<p>Placing surveillance studies within a feminist praxis allows us to frame the reproductive health landscape as more than just an ill-conceived, benign monitoring structure. The critical lens becomes useful for highlighting that taken-for-granted structures of monitoring are wedded with power differentials: genetic screening in fertility clinics, identification documents such as birth certificates, and full-body screeners are just some of the manifestations of this (Adrejevic 2015). Emerging conversations around feminist surveillance studies highlight that these data systems are neither benign nor free of gendered implications (Andrejevic 2015). In continual remaking of the social, corporeal body as a data actor in society, such practices render some bodies normative and obfuscate others, based on categorisations put in place by the surveiller.</p>
<p>In fact, the history of surveillance can be traced back to the colonial state where it took the form of systematic sexual and gendered violence enacted upon indigenous populations in order to render them compliant (Rifkin 2011; Morgensen 2011). Surveillance, then, manifests as a “scientific” rationalisation of complex social hieroglyphs (such as reproductive health) into formats enabling administrative interventions by the modern state. Lyon (2001) has also emphasised how the body emerged as the site of surveillance in order for the disciplining of the “irrational, sensual body”—essential to the functioning of the modern nation-state—to effectively happen.</p>
<h3><strong>Questioning the Information and Communications Technology for Development (ICT4D) and Big Data for Development (BD4D) Rhetoric</strong></h3>
<p>Information and Communications Technology (ICT) and data-driven approaches to the development of a robust health information system, and by extension, welfare, have been offered as solutions to these inequities and exclusions in access to maternal and reproductive healthcare in the country.</p>
<p>The move towards data-driven development in the country commenced with the introduction of the Health Management Information System in Andhra Pradesh in 2008, and the Mother and Child Tracking System (MCTS) nationally in 2011. These are reproductive health information systems (HIS) that collect granular data about each pregnancy from the antenatal to the post-natal period, at the level of each sub-centre as well as primary and community health centre. The introduction of HIS comprised cross-sectoral digitisation measures that were a part of the larger national push towards e-governance; along with health, thirty other distinct areas of governance, from land records to banking to employment, were identified for this move towards the digitalised provisioning of services (MeitY 2015).</p>
<p>The HIS have been seen as playing a critical role in the ecosystem of health service provision globally. HIS-based interventions in reproductive health programming have been envisioned as a means of: (i) improving access to services in the context of a healthcare system ridden with inequalities; (ii) improving the quality of services provided, and (iii) producing better quality data to facilitate the objectives of India’s RCH programme, including family planning and population control. Accordingly, starting 2018, the MCTS is being replaced by the RCH portal in a phased manner. The RCH portal, in areas where the ANMOL (ANM Online) application has been introduced, captures data real-time through tablets provided to health workers (MoHFW 2015).</p>
<p>A proposal to mandatorily link the Aadhaar with data on pregnancies and abortions through the MCTS/RCH has been made by the union minister for Women and Child Development as a deterrent to gender-biased sex selection (Tembhekar 2016). The proposal stems from the prohibition of gender-biased sex selection provided under the Pre-Conception and Pre-Natal Diagnostics Techniques (PCPNDT) Act, 1994. The approach taken so far under the PCPNDT Act, 2014 has been to regulate the use of technologies involved in sex determination. However, the steady decline in the national sex ratio since the passage of the PCPNDT Act provides a clear indication that the regulation of such technology has been largely ineffective. A national policy linking Aadhaar with abortions would be aimed at discouraging gender-biased sex selection through state surveillance, in direct violation of a female’s right to decisional privacy with regards to their own body.</p>
<p>Linking Aadhaar would also be used as a mechanism to enable direct benefit transfer (DBT) to the beneficiaries of the national maternal benefits scheme. Linking reproductive health services to the Aadhaar ecosystem has been critiqued because it is exclusionary towards women with legitimate claims towards abortions and other reproductive services and benefits, and it heightens the risk of data breaches in a cultural fabric that already stigmatises abortions. The bodies on which this stigma is disproportionately placed, unmarried or disabled females, for instance, experience the harms of visibility through centralised surveillance mechanisms more acutely than others by being penalised for their deviance from cultural expectations. This is in accordance with the theory of "data extremes,” wherein marginalised communities are seen as living on the extremes of data capture, leading to a data regime that either refuses to recognise them as legitimate entities or subjects them to overpolicing in order to discipline deviance (Arora 2016). In both developed and developing contexts, the broader purpose of identity management has largely been to demarcate legitimate and illegitimate actors within a population, either within the framework of security or welfare.</p>
<h3><strong>Potential Harms of the Data Model of Reproductive Health Provisioning</strong></h3>
<p>Informational privacy and decisional privacy are critically shaped by data flows and security within the MCTS/RCH. No standards for data sharing and storage, or anonymisation and encryption of data have been implemented despite role-based authentication (NHSRC and Taurus Glocal 2011). The risks of this architectural design are further amplified in the context of the RCH/ANMOL where data is captured real-time. In the absence of adequate safeguards against data leaks, real-time data capture risks the publicising of reproductive health choices in an already stigmatised environment. This opens up avenues for further dilution of autonomy in making future reproductive health choices.</p>
<p>Several core principles of informational privacy, such as limitations regarding data collection and usage, or informed consent, also need to be reworked within this context.<sup>[1]</sup> For instance, the centrality of the requirement of “free, informed consent” by an individual would need to be replaced by other models, especially in the context of reproductive health of rape survivors who are vulnerable and therefore unable to exercise full agency. The ability to make a free and informed choice, already dismantled in the context of contemporary data regimes, gets further precluded in such contexts. The constraints on privacy in decisions regarding the body are then replicated in the domain of reproductive data collection.</p>
<p>What is uniform across these digitisation initiatives is their treatment of maternal and reproductive health as solely a medical event, framed as a data scarcity problem. In doing so, they tend to amplify the understanding of reproductive health through measurable indicators that ignore social determinants of health. For instance, several studies conducted in the rural Indian context have shown that the degree of women’s autonomy influences the degree of usage of pregnancy care, and that the uptake of pregnancy care was associated with village-level indicators such as economic development, provisioning of basic infrastructure and social cohesion. These contextual factors get overridden in pervasive surveillance systems that treat reproductive healthcare as comprising only of measurable indicators and behaviours, that are dependent on individual behaviour of practitioners and women themselves, rather than structural gaps within the system.</p>
<p>While traditionally associated with state governance, the contemporary surveillance regime is experienced as distinct from its earlier forms due to its reliance on a nexus between surveillance by the state and private institutions and actors, with both legal frameworks and material apparatuses for data collection and sharing (Shepherd 2017). As with historical forms of surveillance, the harms of contemporary data regimes accrue disproportionately among already marginalised and dissenting communities and individuals. Data-driven surveillance has been critiqued for its excesses in multiple contexts globally, including in the domains of predictive policing, health management, and targeted advertising (Mason 2015). In the attempts to achieve these objectives, surveillance systems have been criticised for their reliance on replicating past patterns, reifying proximity to a hetero-patriarchal norm (Haggerty and Ericson 2000). Under data-driven surveillance systems, this proximity informs the preexisting boxes of identity for which algorithmic representations of the individual are formed. The boxes are defined contingent on the distinct objectives of the particular surveillance project, collating disparate pieces of data flows and resulting in the recasting of the singular offline self into various 'data doubles' (Haggerty and Ericson 2000). Refractive, rather than reflective, the data doubles have implications for the physical, embodied life of individual with an increasing number of service provisioning relying on the data doubles (Lyon 2001). Consider, for instance, apps on menstruation, fertility, and health, and wearables such as fitness trackers and pacers, that support corporate agendas around what a woman’s healthy body should look, be or behave like (Lupton 2014). Once viewed through the lens of power relations, the fetishised, apolitical notion of the data “revolution” gives way to what we may better understand as “dataveillance.”</p>
<h3><strong>Towards a Networked State and a Neo-liberal Citizen</strong></h3>
<p>Following in this tradition of ICT being treated as the solution to problems plaguing India’s public health information system, a larger, all-pervasive healthcare ecosystem is now being proposed by the Indian state (NITI Aayog 2018). Termed the National Health Stack, it seeks to create a centralised electronic repository of health records of Indian citizens with the aim of capturing every instance of healthcare service usage. Among other functions, it also envisions a platform for the provisioning of health and wellness-based services that may be dispensed by public or private actors in an attempt to achieve universal health coverage. By allowing private parties to utilise the data collected through pullable open application program interfaces (APIs), it also fits within the larger framework of the National Health Policy 2017 that envisions the private sector playing a significant role in the provision of healthcare in India. It also then fits within the state–private sector nexus that characterises dataveillance. This, in turn, follows broader trends towards market-driven solutions and private financing of health sector reform measures that have already had profound consequences on the political economy of healthcare worldwide (Joe et al 2018).</p>
<p>These initiatives are, in many ways, emblematic of the growing adoption of network governance reform by the Indian state (Newman 2001). This is a stark shift from its traditional posturing as the hegemonic sovereign nation state. This shift entails the delayering from large, hierarchical and unitary government systems to horizontally arranged, more flexible, relatively dispersed systems.<sup>[2]</sup> The former govern through the power of rules and law, while the latter take the shape of self-regulating networks such as public–private contractual arrangements (Snellen 2005). ICTs have been posited as an effective tool in enabling the transition to network governance by enhancing local governance and interactive policymaking enabling the co-production of knowledge (Ferlie et al 2011). The development of these capabilities is also critical to addressing “wicked problems” such as healthcare (Rittel and Webber 1973).<sup>[3]</sup> The application of the techno-deterministic, data-driven model to reproductive healthcare provision, then, resembles a fetishised approach to technological change. The NHSRC describes this as the collection of data without an objective, leading to a disproportional burden on data collection over use (NHSRC and Taurus Glocal 2011).</p>
<p>The blurring of the functions of state and private actors is reflective of the neo-liberal ethic, which produces new practices of governmentality. Within the neo-liberal framework of reproductive healthcare, the citizen is constructed as an individual actor, with agency over and responsibility for their own health and well-being (Maturo et al 2016).</p>
<h3><strong>“Quantified Self” of the Neo-liberal Citizen</strong></h3>
<p>Nowhere can the manifestation of this neo-liberal citizen can be seen as clearly as in the “quantified self” movement. The quantified self movement refers to the emergence of a whole range of apps that enable the user to track bodily functions and record data to achieve wellness and health goals, including menstruation, fertility, pregnancies, and health indicators in the mother and baby. Lupton (2015) labels this as the emergence of the “digitised reproductive citizen,” who is expected to be attentive to her fertility and sexual behaviour to achieve better reproductive health goals. The practice of collecting data around reproductive health is not new to the individual or the state, as has been demonstrated by the discussion above. What is new in this regime of datafication under the self-tracking movement is the monetisation of reproductive health data by private actors, the labour for which is performed by the user. Focusing on embodiment draws attention to different kinds of exploitation engendered by reproductive health apps. Not only is data about the body collected and sold, the unpaid labour for collection is extracted from the user. The reproductive body can then be understood as a cyborg, or a woman-machine hybrid, systematically digitising its bodily functions for profit-making within the capitalist (re)production machine (Fotoloulou 2016). Accordingly, all major reproductive health tracking apps have a business model that relies on selling information about users for direct marketing of products around reproductive health and well-being (Felizi and Varon nd).</p>
<p>As has been pointed out in the case of big data more broadly, reproductive health applications (apps) facilitate the visibility of the female reproductive body in the public domain. Supplying anonymised data sets to medical researchers and universities fills some of the historical gaps in research around the female body and reproductive health. Reproductive and sexual health tracking apps globally provide their users a platform to engage with biomedical information around sexual and reproductive health. Through group chats on the platform, they are also able to engage with experiential knowledge of sexual and reproductive health. This could also help form transnational networks of solidarity around the body and health (Fotopoulou 2016).</p>
<p style="text-align: justify;">This radical potential of network-building around reproductive and sexual health is, however, tempered to a large extent by the reconfiguration of gendered stereotypes through these apps. In a study on reproductive health apps on Google Play Store, Lupton (2014) finds that products targeted towards female users are marketed through the discourse of risk and vulnerability, while those targeted towards male users are framed within that of virility. Apart from reiterating gendered stereotypes around the male and female body, such a discourse assumes that the entire labour of family planning is performed by females. This same is the case with the MCTS/RCH.</p>
<p>Technological interventions such as reproductive health apps as well as HIS are based on the assumption that females have perfect control over decisions regarding their own bodies and reproductive health, despite this being disproved in India. The Guttmacher Institute (2014) has found that 60% of women in India report not having control over decisions regarding their own healthcare. The failure to account for the husband or the family as stakeholder in decision-making around reproductive health has been a historical failure of the family planning programme in India, and is now being replicated in other modalities. This notion of an autonomous citizen who is able to take responsibility of their own reproductive health and well-being does not hold true in the Indian context. It can even be seen as marginalising females who have already been excluded from the reproductive health system, as they are held responsible for their own inability to access healthcare.</p>
<h3><strong>Concluding Remarks</strong></h3>
<p>The interplay that emerges between reproductive health surveillance and data infrastructures is a complex one. It requires the careful positioning of the political nature of data collection and processing as well as its hetero-patriarchal and colonial legacies, within the need for effective utilisation of data for achieving developmental goals. Assessing this discourse through a feminist lens identifies the web of power relations in data regimes. This problematises narratives of technological solutions for welfare provision.</p>
<p>The reproductive healthcare framework in India then offers up a useful case study to assess these concerns. The growing adoption of ICT-based surveillance tools to equalise access to healthcare needs to be understood in the socio-economic, legal, and cultural context where these tools are being implemented. Increased surveillance has historically been associated with causing the structural gendered violence that it is now being offered as a solution to. This is a function of normative standards being constructed for reproductive behaviour that necessarily leave out broader definitions of reproductive health and welfare when viewed through a feminist lens. Within the larger context of health policymaking in India, moves towards privatisation then demonstrate the peculiarity of dataveillance as it functions through an unaccountable and pervasive overlapping of state and private surveillance practises. It remains to be seen how these trends in ICT-driven health policies affect access to reproductive rights and decisional privacy for millions of females in India and other parts of the global South.</p>
<p> </p>
<p>
For more details visit <a href='https://cis-india.org/internet-governance/blog/data-infrastructures-inequities-reproductive-health-surveillance-india'>https://cis-india.org/internet-governance/blog/data-infrastructures-inequities-reproductive-health-surveillance-india</a>
</p>
No publisherAayush Rathi and Ambika TandonBig DataData SystemsPrivacyResearchers at WorkInternet GovernanceResearchBD4DHealthcareSurveillanceBig Data for Development2019-12-30T16:44:32ZBlog EntryFuture Value of Data
https://cis-india.org/internet-governance/news/future-value-of-data
<b>Carnegie India with support of Facebook organized a workshop in Bengaluru on January 10, 2018. Sunil Abraham participated in the workshop.</b>
<p style="text-align: justify; ">The event focused on the political economy of reform in India, foreign and security policy, and the role of innovation and technology in India's internal transformation and international relations.</p>
<p style="text-align: justify; ">Core aims of the workshop included:</p>
<ul>
<li>Share and debate views on what changes we expect in the value of data over next decade.</li>
<li>Challenge and explore the underlying drivers of change across broad arena.</li>
<li>Debate the regional and global perspectives and highlight unique issues of greatest impact.</li>
<li>Build an informed collective view on the topic for all to use going forward.</li>
</ul>
<p>For more details on Future of Value Data, <a class="external-link" href="https://www.futureagenda.org/news/future-value-of-data">click here</a></p>
<p>
For more details visit <a href='https://cis-india.org/internet-governance/news/future-value-of-data'>https://cis-india.org/internet-governance/news/future-value-of-data</a>
</p>
No publisherAdminInternet GovernanceBig Data2018-01-17T00:32:50ZNews ItemOPINION | Data is New Oil and Human Mind the New Battlefield. India Must Wake Up Now
https://cis-india.org/internet-governance/news/news-18-lt-general-retd-ds-hooda-data-is-new-oil-and-human-mind-the-new-battlefield-india-must-wake-up-now
<b>In information warfare, the battlespace is the human mind. This is where the privacy of an individual intersects with national security. Fighting this battle will require a new paradigm in thought and action.</b>
<p style="text-align: justify; ">The article by Lt. General (Retd.) D. S. Hooda was published by <a class="external-link" href="http://www.news18.com/news/india/opinion-data-is-new-oil-and-human-mind-the-new-battlefield-india-must-wake-up-now-1573747.html">News18.com</a> on November 11, 2017</p>
<hr style="text-align: justify; " />
<p style="text-align: justify; ">A few days ago, the Army Headquarters took out a public advisory warning about a “deliberate misinformation campaign being launched by vested interests some of which is being initiated from countries bordering our nation.” This is an acknowledgment of the use of social media for what is today considered the most dominant form of warfare — ‘information warfare’. It has been extensively used by our adversaries in Jammu and Kashmir to show the government and security forces in poor light.<br /> <br /> Deception, propaganda and misinformation have always been a part of warfare but what is different today is that the tools of information warfare have acquired a new dimension. An integration of massive amounts of data with Artificial Intelligence (AI) has given a significant weapon in the hands of information warriors.</p>
<p style="text-align: justify; ">The cost of saving data has been plummeting, with the cost being halved about every 15 months. Now more and more data about individuals is being saved, both by corporations and governments. In his book, <i>Data and Goliath</i>, Bruce Schneier writes that worldwide, Google has the capacity to store 15 exabytes of data. To put it in context, one exabyte is 500 billion pages of text. Bruce also quotes the case of Max Schrems, an Austrian law student, who in 2011 demanded all his personal data from Facebook. After a two year legal battle, Facebook gave him a CD with 1200 pages of PDF. This is how much Facebook knows about you, and it does not forget because it is all saved.<br /> <br /> All this big data would be useless unless it can be utilised for decision making and this is where advances in AI have provided the breakthrough. Smart machines mine the data and detect trends, patterns, habits, ideology and desires. These personal characteristics of individuals are being used by corporations to send targeted advertisements to influence commercial decisions.<br /> <br /> The same technique is used in information warfare. On November 1, the US House Intelligence Committee released Facebook advertisements bought by Russian operatives to influence the 2016 elections. Washington Post wrote, “The ads made visceral appeals to voters concerned about illegal immigration...African American political activism, rising prominence of Muslims” among other issues. Senator Angus King said, “The strategy is to take a crack in our society and turn it into a chasm.”<br /> <br /> Data is the new oil and that is exactly how it is being traded and sold. In the absence of any legal provisions, companies and ‘data brokers’ are sharing and selling personal data. Can this personal data find its way to a hostile government? Last month, the US Army brought out that their troops in the Baltic had reported instances of cell phone hacking. However, more worrisome was the fact the hackers knew personal details of the soldiers. Direct threats against family members of the military can have a negative psychological impact during conflict.<br /> <br /> India has its share of political, social and ethnic differences, just as in many societies. In recent times these differences have been magnified as nationalism has taken centre stage. It is difficult to imagine why these fault lines will not be exploited by inimical forces as India enters the election mode in 2018. Looking at examples from the US and French elections, Brexit and the cyber battle during the Catalonia referendum, I think we have no option but to be prepared.<br /> <br /> The preparation for this war (and I do not use this word lightly) lies in three spheres — concepts, practices and structures.<br /> <br /> Conceptually, our current shortcoming is that we are viewing this issue through a technical prism rather than the broader spectrum of information warfare. CERT and NTRO can technically protect our critical infrastructure but they do not have an equal understanding of the human dimension, which is more strategic than scientific. The Americans, world leaders in information technology, have not been able to prevent a perceived subversion of their democratic process.<br /> <br /> Our practices need to improve. The security of personal data is a major concern. The Supreme Court has declared privacy as a fundamental right, but there are no privacy laws to back it up. Even data stored in India is not safe as the owners of our data are the giant technology companies, mostly based in the US and not under our legal control. In September 2017, it was reported that Google has quietly stopped challenging most search warrants from US judges in which the data requested is stored on overseas servers.<br /> <br /> A May 2017, report by the Centre for Internet and Society estimated that 135 million Aadhaar numbers could have been leaked from official portals. This was not due to a security breach but due to poor privacy practices.<br /> <br /> Our continued reliance on foreign hardware and software is extremely worrisome. There was clear evidence that Cisco systems had been back-doored by the American National Security Agency but the Indian military continues to procure hardware from Cisco. There is a similar story with Chinese equipment in our telecommunication and power sectors. An attempt to introduce an Indian operating system to replace Windows in the Army has been mired in controversy.<br /> <br /> In case of a targeted cyber attack on India, there is little we can do except issue advisories. The solutions will have to come from foreign manufactures or developers whose equipment we are using. There is an urgent need to give a fillip to developing indigenous solutions for our critical infrastructure.<br /> <br /> And finally, structures. An organisation to execute information warfare would have to be led by the Ministry of Defence, because the threat is mainly from external players. It would be a combination of military planners, specialists from the field of intelligence, government agencies, media and cyber warfare experts. Such an organisation does not currently exist, though the raising of the Cyber Command could fill this gap.<br /> <br /> In information warfare, the battlespace is the human mind. This is where the privacy of an individual intersects with national security. Fighting this battle will require a new paradigm in thought and action.<br /> <br /> <i><b>(The author is former Northern Commander, Indian Army, under whose leadership India carried out surgical strikes against Pakistan in 2016. Views are personal.)</b></i></p>
<p>
For more details visit <a href='https://cis-india.org/internet-governance/news/news-18-lt-general-retd-ds-hooda-data-is-new-oil-and-human-mind-the-new-battlefield-india-must-wake-up-now'>https://cis-india.org/internet-governance/news/news-18-lt-general-retd-ds-hooda-data-is-new-oil-and-human-mind-the-new-battlefield-india-must-wake-up-now</a>
</p>
No publisherAdminInternet GovernanceBig DataPrivacy2017-11-26T03:28:55ZNews ItemGlobal Technology Summit 2017
https://cis-india.org/internet-governance/news/global-technology-summit-2017
<b>The 2017 Global Technology Summit will take place on December 7 and 8, 2017 at the Hotel Leela Palace, Bangalore. Sunil Abraham is a speaker at the event.</b>
<p style="text-align: justify; ">Link to the original published by Carnegie <a class="external-link" href="http://carnegieindia.org/2017/12/08/global-technology-summit-2017-event-5656?mkt_tok=eyJpIjoiTjJKbFlXWTBaakV3TVRVMSIsInQiOiJ1YkRmVHZHd2h2bVFOTzNEQm94YzRBYUtrWjFwNnhXMkJFSWNiSDE0QldRd3RsT3d1cXhyd2xrNGs4MjdUc2NTN3kyMm9wd28zWGgrcWFDVVBMXC90czhYQ0dSTzlPajRseGdzXC80WW4wWE9zMVR1N1pYY0pmdHBqZTRjSGphQWVRIn0%3D">here</a></p>
<hr style="text-align: justify; " />
<p style="text-align: justify; ">The inaugural edition of the <a href="http://carnegieindia.org/2016/12/07/global-technology-summit-2016-event-5407">Global Technology Summit</a> convened leading scholars, experts, and officials from more than ten countries for wide-ranging discussions on policy frameworks for technological innovation.</p>
<p style="text-align: justify; ">Building on its success, leading innovators, researchers, and entrepreneurs in cutting-edge technologies from around the world will engage with regulators, policy experts, and civil society actors this December in Bangalore.</p>
<p style="text-align: justify; ">The Summit will focus on new directions in technology policy, such as tech-diplomacy, data protection, and building an innovation ecosystem, as well as fields like digital finance, e-mobility, robotics, and smart cities, where massive technological transformation is likely in the coming years.</p>
<p><a class="external-link" href="http://cis-india.org/internet-governance/files/global-technology-summit-2017-agenda"><b>Agenda here</b></a></p>
<h3>Panel Description</h3>
<p style="text-align: justify; ">Navigating Big Data Challenges: Access to data, and capabilities to analyze the same, redefine the business moat for corporations and governance opportunities for governments. Data dictates product and policy success. It also raises complex challenges. With ever increasing hacks and vulnerabilities, data security continues to confound us. Data-driven businesses and governments also question core assumptions of privacy and individual reputation. Machine learning and deep learning, facilitated by data crunching algorithms, can either be coded to discriminate or learn from human data sets and imbibe the very same prejudices. This panel will deliberate upon these varied challenges, and explore possible policy frameworks to address them.</p>
<p style="text-align: justify; ">The panelists are:</p>
<ul>
<li>Ann Cavoukian</li>
<li>Rahul Matthan</li>
<li>Vishnu Shankar</li>
<li>Rob Sherman</li>
<li>Sunil Abraham</li>
</ul>
<p style="text-align: justify; ">Chaired by B.N. Srikrishna, former judge, Supreme Court of India</p>
<p>
For more details visit <a href='https://cis-india.org/internet-governance/news/global-technology-summit-2017'>https://cis-india.org/internet-governance/news/global-technology-summit-2017</a>
</p>
No publisherAdminInternet GovernanceBig Data2017-12-05T13:47:57ZNews Item#NAMAprivacy: Data standards for IoT and home automation systems
https://cis-india.org/internet-governance/news/medianama-october-18-2017-namaprivacy-data-standards-for-iot
<b>On 5th October, MediaNama held a #NAMAprivacy conference in Bangalore focused on Privacy in the context of Artificial Intelligence, Internet of Things (IoT) and the issue of consent, supported by Google, Amazon, Mozilla, ISOC, E2E Networks and Info Edge, with community partners HasGeek and Takshashila Institution. Part 1 of the notes from the discussion on IoT:</b>
<p style="text-align: justify; ">Link to the original published by Medianama on October 18 <a class="external-link" href="https://www.medianama.com/2017/10/223-namaprivacy-data-standards-for-iot/">here</a></p>
<hr />
<p style="text-align: justify; ">The second session of the #NAMAprivacy in Bangalore dealt with the data privacy in the Internet of Things (IoT) framework. All three panelists for the session – <b>Kiran Jonnalagadda from HasGeek, Vinayak Hegde, a big data consultant working with ZoomCar and Rohini Lakshane a policy researcher from CIS</b> – said that they were scared about the spread of IoT at the moment. This led to a discussion on the standards which will apply to IoT, still nascent at this stage, and how it could include privacy as well.</p>
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<p style="text-align: justify; "><img class="size-full wp-image-176794 aligncenter" height="501" src="https://i2.wp.com/www.medianama.com/wp-content/uploads/IOT-panel-Namaprivacy-e1508321963437.jpg?resize=750%2C501&ssl=1" width="750" /></p>
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<p style="text-align: justify; ">Hedge, a volunteer with the Internet Engineering Task Force (IETF) which was instrumental in developing internet protocols and standards such as DNS, TCP/IP and HTTP, said that IETF took a political stand recently when it came to privacy. “One of the discussions in the IETF was whether security is really important? For a long time, the pendulum swung the other way and said that it’s important and that it’s not big enough a trade-off until the bomb dropped with the Snowden revelations. <b>The IETF has always avoided taking any political stance. But for the first time, they did take a political position and they published a request for comments which said: “Pervasive monitoring is an attack on the Internet” and that has become a guiding standard for developing the standards,</b>” he explained.</p>
<p style="text-align: justify; ">He added that this led the development of new standards which took privacy into consideration by default.</p>
<blockquote style="text-align: justify; ">
<p>“The repercussions has been pervasive across all the layers of the stack whether it is DNS and the development of DNS Sec. The next version of HTTP, does not actually mandate encryption but if you look at all the implementation on the browser side, all of them without exception have incorporated encryption,” he added.</p>
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<p style="text-align: justify; "><img class="size-full wp-image-176747 aligncenter" height="500" src="https://i2.wp.com/www.medianama.com/wp-content/uploads/NAMA-Data-Protection-Bangalore-93-e1508322824147.jpg?resize=750%2C500&ssl=1" width="750" /></p>
<p style="text-align: justify; ">Rohini added that discussion around the upcoming 5G standard, where large-scale IoT will be deployed, also included increased emphasis on privacy. “It is essentially a lot of devices connected to the Internet and talking to each other and the user. The standards for security and privacy for 5G are being built and some of them are in the process of discussion. Different standard-setting bodies have been working on them and there is a race of sorts for setting them up by stakeholders, technology companies, etc to get their tech into the standard,” she said.</p>
<p style="text-align: justify; ">“<b>The good thing about those is that they will have time to get security and privacy. Here, I would like to mention <a href="https://ict-rerum.eu/">RERUM</a> which is formed from a mix of letters which stands for Reliable, Resilient, and Secure IoT for smart cities being piloted in the EU. </b>It essentially believes that security should include reliability and privacy by design. This pilot project was thought to allow IoT applications to consider security and privacy mechanisms early in the design, so that they could balance reliability. Because once a standard is out or a mechanism is out, and you implement something as large as a smart city, it is very difficult to retrofit these considerations,” she explained.</p>
<p style="text-align: justify; "><img class="size-full wp-image-176796 aligncenter" height="499" src="https://i2.wp.com/www.medianama.com/wp-content/uploads/Rohini-Lakshane-CIS-Namaprivacy-e1508322694320.jpg?resize=750%2C499&ssl=1" width="750" /></p>
<h2 style="text-align: justify; ">Privacy issues in home automation and IoT</h2>
<p style="text-align: justify; ">Rohini pointed out a report which illustrates the staggering amount of data collection which will be generated by home automation. “I was looking for figures, and I found an FTC report published in 2015 where one IoT company revealed in a workshop that it <b>provides home automation to less than 10,000 households but all of them put together account for 150 million data points per day.</b> So that’s one data point for every six seconds per household. So this is IoT for home automation and there is IoT for health and fitness, medical devices, IoT for personal safety, public transport, environment, connected cars, etc.”</p>
<p style="text-align: justify; ">In this sort of situation, the data collected could be used for harms that users did not account for.</p>
<blockquote style="text-align: justify; ">
<p>“I received some data a couple of years back and the data was from a water flowmeter. It was fitted to a villa in Hoskote and the idea was simple where you could measure the water consumption in the villa and track the consumption. So when I received the data, I figured out by just looking at the water consumption, you can see how many people are in the house, when they get up at night, when they go out, when they are out of station. All of this data can be misused. Data is collected specifically for water consumption and find if there are any leakages in the house. But it could be used for other purposes,” <b>Arvind P from Devopedia</b> said.</p>
</blockquote>
<p style="text-align: justify; "><img class="size-full wp-image-176800 aligncenter" height="499" src="https://i1.wp.com/www.medianama.com/wp-content/uploads/Arvind-Devopedia-Namaprivcay-e1508323377344.jpg?resize=750%2C499&ssl=1" width="750" /></p>
<p style="text-align: justify; "><b>Pranesh Prakash, policy director at Centre for Internet and Society (CIS)</b>, also provided an example of a Twitter handle called “should I be robbed now” where it correlates a user’s vacation pictures says that they could be robbed. “What we need to remember is that a lot of correlation analysis is not just about the analysis but it is also about the use and misuse of it. A lot of that use and misuse is non-transparent. Not a single company tells you how they use your data, but do take rights on taking your data,” he added.</p>
<p style="text-align: justify; "><img class="size-full wp-image-176801 aligncenter" height="501" src="https://i1.wp.com/www.medianama.com/wp-content/uploads/Pranesh-Prakash-Namaprivacy-e1508324108535.jpg?resize=750%2C501&ssl=1" width="750" /></p>
<p style="text-align: justify; ">Vinayak Hedge also added that the governments are using similar methods of data tracking to catch bitcoin miners in China and Venezuela from smart meters.</p>
<p style="text-align: justify; ">“In China, there are all these bitcoin miners. I was reading this story in Venezuela, where bitcoin mining is outlawed. <b>The way they’re catching these bitcoin miners is by looking at their electricity consumption. Bitcoin mining uses a huge amount of power and computing capacity.</b> And people have come out with ingenious ways of getting around it. They will draw power from their neighbours or maybe from an industrial setting. This could be a good example for a privacy-infringing activity.”</p>
<h2 style="text-align: justify; "><b>Pseudonymization</b></h2>
<p style="text-align: justify; "><b>Srinivas P, head of security at Infosys</b>, pointed out that a possible solution to provide privacy in home automation systems could be the concept of pseudonymity. <b>Pseudonymization</b> is a procedure by which the most identifying fields within a data record are replaced by one or more artificial identifiers or pseudonyms.</p>
<p style="text-align: justify; ">“There are a number of home automation systems which are similar to NEST, which is extensively used in Silicon Valley homes, that connect to various systems. For example, when you are approaching home, it will know when to switch on your heating system or AC based on the weather. And it also has information on who stays in the house and what room and what time they sleep. And in a the car, it gives a full real-time profile about the situation at home. It can be a threat if it is hacked. This is a very common threat that is being talked about and how to introduce pseudo-anonymity. When we use these identifiers, and when the connectivity happens, how do we do so that the name and user are not there? Pseudonymity can be introduced so that it becomes difficult for the hacker to decipher who this guy is,” Srinivas added.</p>
<h2 style="text-align: justify; "><b>Ambient data collection</b></h2>
<p style="text-align: justify; ">With IoT, it has never been able to capture ambient data. <b>Ambient data</b> <b>is information that lies in areas not generally accessible to the user.</b> An example for this is how users get traffic data from Internet companies. Kiran Jonnalagadda explained how this works:</p>
<blockquote style="text-align: justify; ">
<p>“When you look at traffic data on a street map, where is that data coming from? <b>It’s not coming from the fact that there is an app on the phone constantly transmitting data from the phone. It’s coming from the fact that cell phone towers record who is coming to them and you know if the cell phone tower is facing the road, and it has so many connections on it, you know that traffic is at a certain level in that area</b>. Now as a user of the map, you are talking to a company which produces this map and it is not a telecom company. Someone who is using a phone is only dealing with a telecom company and how does this data transfer happen and how much user data is being passed on to the last mile user who is actually holding the phone.”</p>
</blockquote>
<p style="text-align: justify; "><img class="size-full wp-image-176802 aligncenter" height="501" src="https://i0.wp.com/www.medianama.com/wp-content/uploads/Kiran-Namaprivacy-e1508324684657.jpg?resize=750%2C501&ssl=1" width="750" /></p>
<p style="text-align: justify; ">Jonnalagadda stressed on the need for people to ask who is aggregating this ambient data.</p>
<p style="text-align: justify; ">“Now obviously, when you look at the map, you don’t get to see, who is around you. And that would be a clear privacy violation and you only get to see the fact that traffic is at a certain level of density around the street around you. But at what point is the aggregation of data happening from an individually identifiable phone to just a red line or a green line indicating the traffic in an area. We also need to ask who is doing this aggregation. Is it happening on the telecom level? Is it happening on the map person level and what kind of algorithms are required that a particular phone on a cell phone network represents a moving vehicle or a pedestrian? Can a cell phone company do that or does a map company do that? If you start digging and see at what point is your data being anonymized and who is responsible for anonmyzing it and you think that this is the entity that is supposed to be doing it, we start realizing that it is a lot more complicated and a lot more pervasive than we thought it would be,” he said.</p>
<p style="text-align: justify; "><b>#NAMAprivacy Bangalore:</b></p>
<ul style="text-align: justify; ">
<li>Will artificial Intelligence and Machine Learning kill privacy? [<a href="https://www.medianama.com/2017/10/223-namaprivacy-artificial-intelligence-privacy/">read</a>]</li>
<li>Regulating Artificial Intelligence algorithms [<a href="https://www.medianama.com/2017/10/223-namaprivacy-regulating-artificial-intelligence-algorithms/">read</a>]</li>
<li>Data standards for IoT and home automation systems [<a href="https://www.medianama.com/2017/10/223-namaprivacy-data-standards-for-iot/">read</a>]</li>
<li>The economics and business models of IoT and other issues [<a href="https://www.medianama.com/2017/10/223-namaprivacy-economics-and-business-models-of-iot/">read</a>]</li>
</ul>
<p style="text-align: justify; "><b>#NAMAprivacy Delhi:</b></p>
<ul style="text-align: justify; ">
<li>Blockchains and the role of differential privacy [<a href="https://www.medianama.com/2017/09/223-namaprivacy-blockchains-role-differential-privacy/">read</a>]</li>
<li>Setting up purpose limitation for data collected by companies [<a href="https://www.medianama.com/2017/09/223-namaprivacy-setting-purpose-limitation-data-collected-companies/">read</a>]</li>
<li>The role of app ecosystems and nature of permissions in data collection [<a href="https://www.medianama.com/2017/09/223-namaprivacy-role-app-ecosystems-nature-permissions-data-collection/">read</a>]</li>
<li>Rights-based approach vs rules-based approach to data collection [<a href="https://www.medianama.com/2017/09/223-namaprivacy-rights-based-approach-vs-rules-based-approach-data-collection/">read</a>]</li>
<li>Data colonisation and regulating cross border data flows [<a href="https://www.medianama.com/2017/09/223-namaprivacy-data-colonisation-and-regulating-cross-border-data-flows/">read</a>]</li>
<li>Challenges with consent; the Right to Privacy judgment [<a href="https://www.medianama.com/2017/09/223-consent-challenges-privacy-india-namaprivacy/">read</a>]</li>
<li>Consent and the need for a data protection regulator [<a href="https://www.medianama.com/2017/09/223-privacy-india-consent-data-protection-regulator-namaprivacy/">read</a>]</li>
<li>Making consent work in India [<a href="https://www.medianama.com/2017/09/223-privacy-india-consent-namaprivacy/">read</a>]</li>
</ul>
<p>
For more details visit <a href='https://cis-india.org/internet-governance/news/medianama-october-18-2017-namaprivacy-data-standards-for-iot'>https://cis-india.org/internet-governance/news/medianama-october-18-2017-namaprivacy-data-standards-for-iot</a>
</p>
No publisherAdminInternet GovernanceBig Data2017-11-08T02:15:52ZNews ItemBig Data for governance
https://cis-india.org/internet-governance/news/telangana-today-november-8-2017-alekhya-hanumanthu-big-data-for-governance
<b>Recent times have witnessed an explosion of data as users started leaving a huge data footprint everywhere they go. Interestingly, this period has seen a phenomenal increase in computing power couple by a drop in costs of storage.</b>
<p style="text-align: justify; ">The article by Alekhya Hanumanthu was published in <a class="external-link" href="https://telanganatoday.com/big-data-governance">Telangana Today</a> on November 4, 2017.</p>
<hr style="text-align: justify; " />
<p style="text-align: justify; ">India is now sitting on the data so generated and subjecting it to data analytics for uses in various sectors like insurance, education, healthcare, governance, so on and so forth.</p>
<p style="text-align: justify; ">According to Centre for Internet and Society (CIS), in 2015, the Government of Narendra Modi launched Digital India Programme to ensure availability of government services to citizens electronically by improving online infrastructure and Internet connectivity.</p>
<p style="text-align: justify; ">Amongst other things, e-Governance and e-Kranti intend to reform governance through technology and enable electronic delivery of services. Needless to say, it will involve large scale digitisation, electronic collection of data from residents and processing. The Big data so created will help policy making evolve into a data backed, action oriented initiative with accountability asserted where it is due.</p>
<h3 style="text-align: justify; ">Let’s take a look at some Big Data based initiatives underway according to analyticsindiamag:</h3>
<p style="text-align: justify; "><b>Project insight:</b> Undertaken up by Indian tax agencies, Project Insight is an advanced analytical tool that is a comprehensive platform that encourages compliance of tax while at the same time it prevents non-compliance. Significantly, it will be used to detect fraud, support investigations and provide insights for policy making. For instance, it will detect the social media activity of a person to glean their spending and check if it is commensurate with the tax they have paid during that year. Needless to say, this will also unearth sources of black money.</p>
<p style="text-align: justify; "><b>Economic Development Board in Andhra:</b> CORE-CM Office Realtime Executive Dashboard is an integrated dashboard established to monitor category-wise key performance indicators of various departments/schemes in real time. Users can check key performance indicators of various departments, schemes, initiatives, programmes, etc. With a panoply of services information ranging from Women and Child Welfare to Street lights monitoring, it has become an exemplary role model of governance.</p>
<p style="text-align: justify; "><b>Geo-tagging of assets under Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA):</b> Under the guidance of Narendra Modi, online monitoring of assets to check leakages Ministry of Rural development was started. To achieve this, they were tied up with ISRO and National Informatics Centre to geo tag MGNREGA assets. According to India Today, the assets created range from plantations, rural infrastructure, water harvesting structures, flood control measures such as check dams etc. To do this, a junior engineer takes a photo of an asset and uploads it on the Bhuvan web portal run by ISRO’s National Remote Sensing Centre via a mobile app. Once a photo is uploaded, time and location gets encrypted automatically. Thus, the Government hopes to hold an ironclad control of the resources thus disseminated.</p>
<p style="text-align: justify; "><b>CAG’s centre for Data Management and Analytics:</b> According to Comptroller and Auditor General of India, The CAG’s Centre for Data Management and Analytics (CDMA) is going to play a catalytic role to synthesise and integrate relevant data into auditing process. According to an announcement on National Informatics Centre (NIC), it aims to build up capacity in the Indian Audit and Accounts Department in Big Data Analytics to explore the data rich environment at the Union and State levels. What’s more, this initiative of CAG of India, puts it amongst the pioneers in institutionalising data analytics in government audit in the international community.</p>
<p style="text-align: justify; "><b>Task Force to spruce up Employment Data:</b> The data provided by Labour Bureau is limited and not timely enough for policymakers to assess the need for job creation. To address this gap, the Government has set up a committee tasked to fill the employment data gap and ensure the timely availability of reliable information regarding job creation. Thus the top line of Government has a direct view of where the employment gaps are so that it can facilitate creation of appropriate jobs.</p>
<h3 style="text-align: justify; ">What’s the big picture?</h3>
<p style="text-align: justify; ">Policy making and governance by Indian government have traditionally been rife with red tape, bureaucracy and corruption. Lack of accountability on part of Government workforce not only impacted the quantity and quality of work delivered but also invited corrupt practices and leakages. So, Big data is a welcome change in direction.</p>
<p>
For more details visit <a href='https://cis-india.org/internet-governance/news/telangana-today-november-8-2017-alekhya-hanumanthu-big-data-for-governance'>https://cis-india.org/internet-governance/news/telangana-today-november-8-2017-alekhya-hanumanthu-big-data-for-governance</a>
</p>
No publisherAdminInternet GovernanceBig Data2017-11-08T01:42:18ZNews ItemMediaNama - #NAMAprivacy: The Future of User Data (Delhi, Sep 6)
https://cis-india.org/internet-governance/news/medianama-namaprivacy-the-future-of-user-data-delhi-sep-6
<b>MediaNama is hosting a full day conference on "the future of user data in India", on the 6th of September 2017, which is particularly significant given the recent Supreme Court ruling on the fundamental right to privacy, and two government consultations: one at the TRAI, and another at MEITY. This discussion is supported by Facebook, Google, and Microsoft. Sumandro Chattapadhyay, Research Director, will participate as a speaker in the session titled "regulating storage, sharing and transfer of data."</b>
<p> </p>
<h4>Details</h4>
<p>Time: September 6th 2017, 9 am to 4:30 pm</p>
<p>Venue: Gulmohar Hall, India Habitat Centre, Lodhi Road (please enter from Gate #3)</p>
<p>Agenda: <a href="https://www.medianama.com/2017/08/223-agenda-namaprivacy-future-of-user-data/">https://www.medianama.com/2017/08/223-agenda-namaprivacy-future-of-user-data/</a></p>
<h4>Announced Speakers</h4>
<ul><li>Chinmayi Arun, Centre for Communication Governance at NLU Delhi</li>
<li>Malavika Raghavan, IFMR Finance Foundation</li>
<li>Renuka Sane, NIPFP</li>
<li>Smitha Krishna Prasad, Centre for Communication Governance at NLU Delhi</li>
<li>Ananth Padmanabhan, Carnegie India</li>
<li>Avinash Ramachandra, Amazon</li>
<li>Hitesh Oberoi, Naukri</li>
<li>Jochai Ben-Avie, Mozilla</li>
<li>Mrinal Sinha, Mobikwik</li>
<li>Murari Sreedharan, Bankbazaar</li>
<li>Sumandro Chattapadhyay, Centre for Internet and Society</li></ul>
<h4>Facilitators</h4>
<ul><li>Saikat Datta, Asia Times Online</li>
<li>Shashidar KJ, MediaNama</li>
<li>Nikhil Pahwa, MediaNama</li></ul>
<h4>Attendees</h4>
<p>We have confirmed 140+ attendees from: Adobe, Amber Health, Amazon, APCO Worldwide, Bank Bazaar, Bloomberg-Quint, Blume Ventures, Broadband India Forum, Business Standard, BuzzFeed News, CCOAI, CEIP, Change Alliance, Chase India, CIS, CNN News18, DEF, Deloitte, DNA, DSCI, E2E Networks, British High Commission, Eurus Network Services, FICCI, Firefly Networks, Flipkart, Forrester Research, Fortumo, DoT, MEITY, IAMAI, IBM, ICRIER, IFMR Finance Foundation, IIMC, Indian Law Institute, Indic Project, Info Edge, ISPAI, IT for Change, ITU-APT, Jamia Millia Islamia, Jindal Global Law School, Mimir Technologies, Mozilla, Newslaundry, NIPFP, Nishith Desai Associates, NIXI, NLU-Delhi, ORF, Paytm, PLR Chambers, PRS Legislative Research, Publicis Groupe, Quartz India, Reliance Jio, Reuters, Saikrishna & Associates, Scroll.in, SFLC.in, Spectranet, The Economics Times, The Indian Express, The Times of India, The Wire, Times Internet, Twitter, and more.</p>
<p> </p>
<p>
For more details visit <a href='https://cis-india.org/internet-governance/news/medianama-namaprivacy-the-future-of-user-data-delhi-sep-6'>https://cis-india.org/internet-governance/news/medianama-namaprivacy-the-future-of-user-data-delhi-sep-6</a>
</p>
No publishersumandroBig DataDigital EconomyPrivacyInternet GovernanceData GovernanceData ProtectionDigital Rights2017-09-05T10:22:12ZBlog EntryCISxScholars Delhi - Harsh Gupta - FAT ML for Lawyers and Lawmakers (June 29, 5:30 pm)
https://cis-india.org/raw/cisxscholars-harsh-gupta-machine-learning-for-lawyers-and-lawmakers-20170629
<b>We are proud to announce that Harsh Gupta will discuss "FAT ML (Fairness, Accountability, and Transparency in Machine Learning) for Lawyers and Lawmakers" at the CIS office in Delhi on Thursday, June 29, at 5:30 pm. This will be a two and half hour session: beginning with a 45 minute talk, followed by 15 minute break, another talk for 45 minutes, and then a discussion session. Please RSVP if you are joining us: <raw@cis-india.org>. </b>
<p> </p>
<p><em>CISxScholars are informal events organised by CIS for presentation, discussion, and exchange of academic research and policy analysis.</em></p>
<hr />
<h3><strong>FAT ML (Fairness, Accountability, and Transparency in Machine Learning) for Lawyers and Lawmakers</strong></h3>
<p>From tagging people in photos to determining risk of loan defaults, use of data based tools is affecting more and areas of our lives. In some areas there have been very successful applications of such tools, in others areas they has been found to not only reflect the existing bias and discrimination found in today's society but also exaggerate it.</p>
<h3><strong>Harsh Gupta</strong></h3>
<p>Harsh Gupta is a recent graduate from IIT Kharagpur with B.Sc and M.Sc in Mathematics and Computing and will be joining JP Morgan and Chase as a data scientist. He completed his master's thesis in "Discrimination Aware Machine Learning". He was also an intern at The Center for Internet and Society during summer of 2016.</p>
<p> </p>
<p>
For more details visit <a href='https://cis-india.org/raw/cisxscholars-harsh-gupta-machine-learning-for-lawyers-and-lawmakers-20170629'>https://cis-india.org/raw/cisxscholars-harsh-gupta-machine-learning-for-lawyers-and-lawmakers-20170629</a>
</p>
No publishersumandroFAT MLCISxScholarsBig DataMachine LearningResearchers at WorkEventArtificial Intelligence2017-06-27T09:16:48ZEvent