The SUR file on Internet and Democracy

Democracy and the algorithmic turn

Anita Gurumurthy and Deepti Bharthur

Issues, challenges and the way forward

Franco Rabazzo



In the current moment of democratic upheaval, the role of technology has been gaining increasing space in the democratic debate due to its role both in facilitating political debates, as well as how users' data is gathered and used. This article aims to discuss the relationship between democracy and the "algorithmic turn" - which the authors define as the "central and strategic role of data processing and automated reasoning in electoral processes, governance and decision making." In doing so the authors help us understand how this phenomenon is influencing society - both positively and negatively - and what are the practical implications we see as a result.

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Democracy is at a turning point. On the one side, refreshing experiments in decentralisation and the horizontalisation of political processes are reinventing the boundaries of democracy, whether it be the rise of youth in formal politics in India and Mexico,11. Radhika Ramaseshan, “After Gujarat 2017: Can BJP’s Communalism Make Up for its Agrarian Neglect?” Economic and Political Weekly 52, no. 51 (2017), accessed June 14, 2018,; PaulinaVillegas, “Wave of Independent Politicians Seek to ‘Open Cracks’ in Mexico’s Status Quo.” The New York Times, March 11, 2018, accessed June 14, 2018, the reclamation of community self-governance in urban spaces such as in the case of the networked Spanish municipalities,22. Ismael Peña-López, “Voice or Chatter Case Studies:, Spain.” IT for Change, 2017, accessed June 14, 2018, or the rise of a new DIY (Do it Yourself) citizen ethos.33. Albert J. Meijer, “The Do It Yourself State,” Information Polity 17, nos. 3, 4 (2012): 303-314. On the other, a range of developments – unanticipated electoral mandates that have stunned the pundits such as the US presidential election of 2016; an expanding trust deficit between state and citizen in many parts of the world44. Cristian Berrío-Zapata, and Darío Sebastian Berrío-Gil, “Voice or Chatter Case Studies: Urna de Cristal, Colombia.” IT for Change, 2017, accessed June 14, 2018, and reduced faith in institutions of democracy;55. Roberto Foa and Yascha Mounk, “Across the Globe, a Growing Disillusionment With Democracy.” The New York Times, September 15, 2015, accessed June 14, 2018, the quest for extra-institutional possibilities of leadership outside traditional venues of action such as government, unions, political parties etc;66. Peña-López, “Voice or Chatter Case Studies,” 2017. the polarisation of the public sphere, and a disconcerting collusion between the techno-capitalist class and the technocratic informational state – point to new challenges for democracy.77. Anita Gurumurthy, Deepti Bharthur, and Nandini Chami, “Voice or Chatter? Making ICTs Work for Transformative Engagement.” Making All Voices Count Research Report, September 14, 2017, accessed June 14, 2018,

With the invisible hand of technology increasingly revealing itself, citizenship itself is at a crossroads. Manipulated masterfully by data-driven tactics, citizens find themselves increasingly slotted into the respective sides of an ever growing and unforgiving ideology divide. However, with the ability to mobilise 140 characters and a handy hashtag, they have also managed to appropriate the digital landscape as a decisive frontier for all shades of civic engagement. From the #FeesMustFall movement student uprisings in South Africa88. Shepherd Mpofu, “Disruption as a Communicative Strategy: The case of # FeesMustFall and #RhodesMustFall Students’ Protests in South Africa,” Journal of African Media Studies 9, no. 2 (2017): 351-373; Thierry Luescher, Lacea Loader, and Taabo Mugume, “# FeesMustFall: An Internet-age Student Movement in South Africa and the case of the University of the Free State,” Politikon 44, no. 2 (2017): 231-245. to the protests against sexual violence against women and girls in India99. Krupa Shandilya, “Nirbhaya’s Body: The Politics of Protest in the Aftermath of the 2012 Delhi Gang Rape,” Gender & History 27, no. 2 (2015): 465-486; Saifuddin Ahmed, Kokil Jaidka, and Jaeho Cho, “Tweeting India’s Nirbhaya Protest: A Study of Emotional Dynamics in an Online Social Movement,” Social Movement Studies 16, no. 4 (2017): 447-465. the online world seems to have secured its place as the stage for civic-public action.

This essay explores the role of the algorithmic turn – what we define here as the central and strategic role data processing and automated reasoning – basically, deployment of digital intelligence tactics – in electoral processes, governance and decision making – in relation to the democratic transition underway. We first discuss the ways in which digital intelligence is influencing and dictating voter behaviors and outcomes. Second, we look at the increasing role of data and algorithms in governance and policy decision processes and the implications for citizen rights. Lastly, we bring to fore some questions on the governance of such technological integration in democratic processes.1010. This essay, in addition to being informed by recent global political events and discourses, also draws from key learnings from a research project we undertook in 2016-17 titled, ‘Voice or chatter? Using a structuration framework towards a theory of ICT-mediated citizen engagement’ (Gurumurthy et al., “Voice or Chatter?”, 2017). Through case studies in eight countries in Asia, Africa and Europe, the study examined the complex and dynamic relationship between the structures of technology and the structures of democracy and the implications for citizen engagement and voice.


Your vote, their tech! How Big Data and big tech are making and unmaking elections

From the somewhat simplistic studies of the early days of mass media technologies such as the role of radio, film and newspapers in war time1111. Harold D. Lasswell, Propaganda Technique in the World War (Gloucester: Peter Smith, 1927). to more recent work that has looked at the role of cell phones and Big Data1212. Big Data are extremely large data sets that may be analysed computationally to reveal patterns, trends, and associations, especially relating to human behavior and interactions. in elections,1313. Robin Jeffrey and Assa Doron, “Mobile-izing: Democracy, Organization and India’s First ‘Mass Mobile Phone’ Elections,” The Journal of Asian Studies 71, no. 1 (2012): 63-80; Sasha Issenberg, “How President Obama’s Campaign Used Big Data to Rally Individual Voters,” Technology Review 116, no. 1 (2012): 38-49, accessed June 14, 2018, technology’s ability to diffuse key messages and propaganda by vested interests has been long acknowledged.

However, the tools and tactics of public sphere manipulation we are witnessing today are unprecedented. The unethical use of Big Data and machine learning1414. The use of statistical techniques that allow computers to iteratively improve upon a given task through data inputs. to “game” the public sphere in pernicious ways marks a new point of departure. For example, through the intense level of surveillance of voters afforded through digital tools, Artificial Intelligence (AI) allows political influence to move from public campaigns to private sentiment,1515. Vyacheslav Polonski, “The Good, the Bad and the Ugly Uses of Machine Learning in Election Campaigns.” Centre for Public Impact, August 30, 2017, accessed June 14, 2018, a shift that repositions electoral politics from a spectacle that is overt to a script that is covert.

Also, as the Internet has grown, so has misinformation. It is often claimed that we live in times of “post-truth”. What this means is that as the virality, speed and reach of digital information increases, a mind-boggling multiplicity of narratives emerge that displace singular and authoritative grand narratives. . The fact that we can choose which communities we want to be connected to means that the received wisdom of societies – the common knowledge and norms shared across communities – break down.1616. Michael Barthel, Amy Mitchell, and Jesse Holcomb, “Many Americans Believe Fake News is Sowing Confusion.” Pew Research Center, December 15, 2016, accessed June 14, 2018, In this flux, social and political sentiment of individuals and communities becomes vulnerable to manipulation and gaming.

In March 2018, as this piece was being written, the Guardian published the explosive news about how Cambridge Analytica, a once obscure data analytics firm, had – through harvesting Facebook users’ data – engineered victories for the Brexit Leave campaign in the UK and the Donald Trump campaign in the United States’ presidential elections.1717. “The Cambridge Analytica Files,” The Guardian, 2018, accessed June 14, 2018, The exposé reveals not merely the large scale of manipulation of users that the techno-paradigm makes possible, but the real implications of behavioural and psychographic profiling and targeting of voters on actual electoral outcomes. The firm’s unscrupulous tactics included scraping (a form of automated data collection) and exploiting user data from Facebook without informed consent and offering monetary incentives for participating in quizzes that were cleverly disguised psychological probes.1818. Ibid. Further, this data was used to engage in polarized messaging and fake news dissemination.

Twitter assumed centre stage in the Mexican political theater in 2012. The failure of mainstream media to report on drug violence owing to threats from cartels had meant that Mexican citizens were already dependent on Twitter for news and updates. Campaigners for the parties in the general election, capatalised on this, spamming the network with thousands of bots1919. Referring here to automated Twitter accounts that pick up and amplify messages and flood the Internet space. that worked round the clock to promote particular new topics and make the trending topics list aligned with the interests of the campaigners, flooding the space with pointless “flame wars”2020. A lengthy exchange of angry or abusive messages between users of an online forum. that left no scope for deep engagement.2121. Mike Orcutt, “Twitter Mischief Plagues Mexico’s Election.” MIT Technology Review, June 21, 2012, accessed June 14, 2018, What we see is that the technological structures of the day built into the media platforms widely used and abused in everyday politics directly have a bearing on how political processes and outcomes are shaped.

The 2017 French presidential elections showed just how extensive the use of bots can be. In May 2017, the Oxford Internet Institute conducted an analysis of the #MacronLeaks hashtag, which involved a data dump of the then presidential candidate’s email correspondence. It found that 50 per cent of the Twitter content consisting of leaked documents and falsified reports was generated by only three percent of the total number of Twitter accounts. These bot accounts were pushing out 1,500 unique tweets per hour garnering an average of 9,500 retweets. The study concluded that over 22.8 million Twitter users were exposed to this information every hour on election day in France.2222. Vyacheslav Polonski, “#MacronLeaks Changed Political Campaigning. Why Macron Succeeded Where Clinton Failed.” World Economic Forum, May 12, 2017, accessed June 14, 2018,; Emilio Ferrara, “Disinformation and Social Bot Operations in the Run Up to the 2017 French Presidential Election,” First Monday 22, no. 8 (2017).

Older practices such as gerrymandering – the manipulation of the boundaries of an electoral constituency so as to bring political advantage for a particular party2323. Nicholas O. Stephanopoulos and Eric M. McGee, “Partisan Gerrymandering and the Efficiency Gap,” The University of Chicago Law Review 82, no. 2 (2015): 831-900. – have found new impetus in the predictive power of Big Data. Gerrymandering has been shown to contribute to increased political polarisation,2424. Ben Wofford, “The Great Gerrymandering Debate.” Brown Political Review, July 15, 2014, accessed June 14, 2018, with disproportionate impacts on the poor. Elected leaders in such polarised constituencies typically tend to avoid taking up issues about economic inequality.2525. Nolan McCarty, Keith T. Poole, and Howard Rosenthal. “Does gerrymandering cause polarization?.“ American Journal of Political Science 53, no. 3 (2009): 666-680. What may be inferred from the above discussion is that while data based electioneering can potentially bring new efficiencies and effectiveness to organising and campaigning, the fact that the technological platforms that define the public sphere today are controlled by the elite does not bear well for the system of electoral democracy as a whole. In theory, the digital intelligence extracted from data cuts down on human resource intensive work, allows for grassroots organisers to optimise their canvassing and can mitigate the distortions of big capital in elections by allowing candidates to reach their constituencies over social media, at literally no cost. However, if the Cambridge Analytica or the MacronLeaks episode shows us anything, it is that we are headed for a vastly different future, one in which voter behaviour is being manipulated towards particular outcomes that may reflect neither a democratic mandate nor informed choice.

These developments pose a crisis for the public sphere. Borrowing from Dewey, “publics” in a democracy are created through “indirect, extensive, enduring and serious consequences of conjoint and interacting behavior”.2626. Tauel Harper, “The Big Data Public and its Problems: Big Data and the Structural Transformation of the Public Sphere,” New Media & Society 19, no. 9 (2016): 1424-1439. Gamed by capital and technology, the very formation of publics is at risk today, with citizen interaction driven into information echo chambers that reinforce and amplify deep bias, resulting in a banality that prevents deliberation and posing particular risks, especially to already marginalised populations.


Algorithm see, algorithm do

While elections are flashpoints – newsworthy by their very nature – the everyday practices of democracy, routine and largely unremarkable, rarely grab the same kind of media attention. However, it is often the structures and practices of everyday citizen-state interaction that become critical in furthering the kind of institutional change that can ultimately contribute to make democracy transformative.

Undoubtedly, there are advantages and efficiencies that digitally mediated governance can afford, such as easier access to information and entitlements for the citizen, and greater transparency and responsiveness for state institutions. E-government arrangements can also help achieve the objectives of participatory governance. The rise of an online network of municipalities in Spain is an excellent example that demonstrates this.2727. Gurumurthy et al., “Voice or Chatter?”, 2017. However, when state-citizen engagement goes online into digital modalities and governance architectures become digitalised, they do pose administrative and legislative challenges, with significant implications for citizen rights.2828. Ibid.

Today, around the world technologies of calculation and regulation are being deployed to enact and regulate their subjects – citizens, migrants, consumers, students, colleagues and many more.2929. Lucas D. Introna, “Algorithms, Governance, and Governmentality: On Governing Academic Writing,” Science, Technology, & Human Values 41, no. 1 (2016): 17-49. Algorithms define the information to be acted upon, engage in “social sorting”3030. David Lyon, “Surveillance in Cyberspace: The Internet, Personal data, and Social Control,” Queen’s Quarterly 109, no. 3 (2002): 345-356. and create autonomous repertoires of action and reaction. “Algorithms ‘govern’ because they have the power to structure possibilities,” notes Ananny.3131. Mike Ananny, “Toward An Ethics of Algorithms: Convening, Observation, Probability, and Timeliness,” Science Technology, & Human Values 41, no. 1 (2016): 97. Napoli even argues that algorithms have come to take the place of institutions “because of their power to structure behavior, influence preferences, guide consumption, produce content, signal quality, and sway commodification.”3232. Philip M. Napoli, “Automated Media: An Institutional Theory Perspective on Algorithmic Media Production and Consumption,” Communication Theory 24, no. 3 (2014): 340-360.

The state itself can be read as an algorithmic assemblage, a complex web of technical actors, autonomous technologies and layers of data coming together to prevail over the ostensible fallibility and inefficiency of human intent. Data in this equation is not merely a source of knowledge, it becomes knowledge itself.3333. Rob Kitchin, “Big Data, New Epistemologies and Paradigm Shifts,” Big Data & Society 1, no. 1 (2014): 1-12.

Consider, for example, Singapore. First developed to detect bird flu outbreaks, the Risk Assessment and Horizon Scanning (RAHS) system in Singapore — which pools data from an exhaustive set of private and public databases – has become the primary decision making tool of the state – from immigration policy, economic forecasts, school curriculum to gauging the nation’s “mood” using Facebook.3434. Shane Harris, “The Social Laboratory.” Foreign Policy, July 29, 2014, accessed June 14, 2018, This highly centralised, all encompassing system of surveillance does not find a comprehensive counter in citizen privacy frameworks.3535. “The Right to Privacy in Singapore,” Privacy International, June 2015, accessed June 15, 2018, Chinese social media giant Baidu has partnered with the military on the China Brain project, to create a system of social credit and ranking for citizens based on their social media engagement3636. Dirk Helbing et al., “Will Democracy Survive Big Data and Artificial Intelligence.” Scientific American, February 25, 2017, accessed June 14, 2018, which will mean that the social media activity of citizens can be monitored and surveilled through state sanction and have a direct impact upon their freedoms.

Notably, welfare decisions are increasingly turned over to data-driven decision making in India, Australia and the US, creating large-scale exclusions in a matter of a single click with punishing consequences for the poor and the marginalised.3737. Gurumurthy et al., “Voice or Chatter?”, 2017; Tal Zarsky, “The Trouble With Algorithmic Decisions: An Analytic Road Map to Examine Efficiency and Fairness in Automated and Opaque Decision Making,” Science, Technology, & Human Values 41, no. 1 (2016): 118-132; Virginia Eubanks, Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor (New York: St.Martin’s Press, 2018). As Ananny notes, algorithms are “embedded within the sociotechnical structures; they are shaped by communities of practice, embodied in standards, and most visible when they fail.”3838. Mike Ananny, “Toward an ethics of algorithms: Convening, observation, probability, and timeliness.“ Science, Technology, & Human Values 41, no. 1 (2016): 93-117, 98.

Global data regimes, whether state led databases such as the RAHS, or privately held by platform corporations are the latest in a line of systems that citizens do not get to vote for, but which end up shaping the significant policies that affect their lives. Global data partnerships have thus seen the large-scale infiltration of data capitalists into hitherto public systems. As a result of this, public infrastructure becomes reconfigured into privately held data enclaves. This poses serious concerns for public good and citizen accountability.3939. Laura Mann, “Left to Other Peoples’ Devices? A Political Economy Perspective on the Big Data Revolution in Development,” Development and Change 49, no. 1 (2017): 3-36. Critical sectors such as education have metamorphosed into covert sites of data mining by programmes. Examples include Google Apps for Education (GAFE)4040. Maria Lindh and Jan Nolin, “Information We Collect: Surveillance and Privacy in the Implementation of Google Apps for Education,” European Educational Research Journal 15, no. 6 (2016): 644-663. and Pearson’s Learning Curve for large-scale modelling and predictive analytics,4141. Ben Williamson, “Digital Education Governance: Data Visualization, Predictive Analytics, and ‘Real-time’ Policy Instruments,” Journal of Education Policy 31, no. 2 (2016): 123-141. both of which pose new ethical challenges to institutional practices. This shift is also visible in health care, with ambitious “smart medicine” projects such as IBM’s Watson.4242. David H. Freedman, “A Reality Check for IBM’s AI Ambitions.” MIT Technology Review, June 27, 2017, accessed June 14, 2018,

As data enabled decision making becomes normalised within public services and governance systems, it promotes a centralisation of authority and power. Facts are selectively mobilised to position political intent as techno-managerial objectivity, while local discretion and flexibility to deal with contextual claims of marginal citizens is eliminated.4343. Gurumurthy et al., “Voice or Chatter?”, 2017. In India, for instance, machine-based decision making on entitlements on the basis of data sets that were incorrect, resulted in the large exclusions of people from welfare benefits. While hiccups in any system are to be anticipated, what made the issue untenable in this case was the fact that no recourse to technological failure or glitches were factored in, leaving citizens, many of them critically dependent on the schemes, disenfranchised on the basis of a completely automated decision, working on flawed data. Algorithmic welfare management, referring here to the practice of deploying technological and data based solutions to process and approve entitlements, uses the myth of the sanctity of data – positing it as a necessary and unfailing means to plug leakages and redeem democracy from undeserving citizens free riding on public resources.4444. Deepti Bharthur, “Voice or Chatter Case Studies: Rajasthan Sampark, India.” IT for Change, 2017, accessed June 14, 2018,

So far as the evidence goes, the algorithmic turn in democracy, the manifestations of which have been discussed in earlier sections, is embedded in the rise of global to local structures of authoritarian capitalism, geared to preserve a neo-liberal consensus even if local interests are at peril.4545. Peter Bloom, Authoritarian Capitalism in the Age of Globalization (Cheltenham: Edward Elgar Publishing, 2016). Fragmenting societies insidiously, disenfranchising marginal citizens systematically, and generating political distractions relentlessly, the technological assemblages based on data and digital intelligence present immense and urgent challenges for the future of human societies.

The legitimacy of the algorithmic turn has been aided by a meta narrative of techno-modernity that all nations must embrace. Cast as neutral tools of economic progress and social advancement, digital technologies have acquired an aura of ungovernability. Big tech corporations often present AI tools that learn and adapt rapidly as an autonomous force far too complex to be understood completely. However, in a rapidly unfolding datafied world, the integration of digital intelligence needs to be rooted in frameworks of accountability, where social intent guides the appropriation of technology.


Watching the watchmen – need for new frameworks

In light of recent events and developments emanating from the Frankenstein Internet of today, digital corporations have come out with public statements about better standards and industry norms for privacy. Google has revealed a set of AI principles – that will ostensibly “take into account a broad range of social and economic factors, and…proceed where (Google) believe(s) that the overall likely benefits substantially exceed the foreseeable risks and downsides.”4646. Sundar Pichai, “AI at Google: Our Principles.” Google, June 7, 2018, accessed June 14, 2018, The principles, coming as they are in response to public pressure and discontent of employees, may seem like a good first step, but whether the company is upholding its ethical commitment or not will be based on Google’s own assessment.4747. Eric Newcomer, “What Google’s AI Principles Left Out.” Bloomberg, June 8, 2018, accessed June 14, 2018, Platform companies such as Facebook4848. Mark Zuckerberg, 2018, “I want to share an update on the Cambridge Analytica situation…”. Facebook, March 21, 2018, accessed June 14, 2018, have also committed to developing ethical standards and AI and design based solutions for countering the above discussed problems of runaway technology. Bodies such as the Institute of Electrical and Electronics Engineers (IEEE) are actively working to develop standards and guidelines for ethical AI.4949. See “The IEEE Global Initiative on Ethics of Autonomous and Intelligent Systems,” IEEE Standards Association, 2017, accessed June 14, 2018, While this is a welcome move, the democratic project in this moment of flux needs an overhaul of institutional norms and cultures. Deliberating and debating the ethics that are adequate to the twenty first century techno-paradigm needs to be followed by non-negotiable and preeminent steps to translate ethical reflections into clear norms and institutional frameworks and oversight.

For one, the public sphere today is in immediate need of fortification against the disruptions of big capital and technology if we are to correct the derailment of democratic processes. Policies that can effectively govern misinformation and social engineering are needed to ensure that the spirit of deliberation and political engagement is preserved. Some countries such as Malaysia,5050. Nazura Ngah, “FAQs: What You Need to Know About the Anti-Fake News Bill 2018.” New Straits Times, March 26, 2018, accessed June 14, 2018, Ireland5151. Kevin Doyle, “Five Years in Jail for Spreading ’Fake News’ Under FF Proposal.” The Independent, December 4, 2017, accessed June 14, 2018, and Germany5252. “Germany Approves Plans to Fine Social Media Firms up to 50m,” The Guardian, June 30, 2017, accessed June 14, 2018, have responded to this crisis with legislation that can counter the spread of fake news and platform misuse through punitive measures. Others such as the US are pushing for greater transparency on online political advertisements with proposed legislation such as The Honest Ads Act.5353. See “S.1989 - Honest Ads Act,”, 2017, accessed June 14, 2018, The wave of proposed regulation and legislation is a welcome sign that countries have woken up to see the writing on the wall. However, the fine line where platform vigilance can easily turn into institutional censorship will be the slippery slope one needs to watch out for.

There is thus, a slow but growing consensus that solutions are needed, in ways that enrich citizens’ social capital rather than infringe on their rights. Critical thinking and discerning consumption of meaningful content, in a technoscape full of falsehoods remains an important challenge and policies that advocate critical media and digital literacy in schools and institutions in this context will be a positive move.5454. “Fighting Fake News – Workshop Report,” Information Society Project, 2018, accessed June 14, 2018,

Policymaking must move from being reactive to actively future-proofing democracy against the autocratic tendencies and function creep of datafication and algorithmic governance. In the absence of clearly articulated norms and policies, algorithmic assemblages, being integrated rapidly into governance frameworks today, risk becoming stand-ins for policy.

Algorithms are limited when it comes to exhibiting nuance, negotiating trade-offs, or exercising the necessary discretion when needed.5555. Barry Devlin, “Algorithms or Democracy – Your Choice.” Upside, September 8, 2017, accessed June 14, 2018, This lack of flexibility completely evacuates citizen rights to meaningful representation and participation. As an important building block of democracy in the digital age, digital intelligence needs to be imagined, calibrated, tested and recalibrated recursively through the prism of citizen rights within institutional frameworks of transparency and accountability.

We therefore need sound and well developed “technological due process”5656. Danielle Keats Citron, “Technological Due Process,” Wash. UL Rev. 85 no. 1249 (2007); Danielle Keats Citron and Frank A. Pasquale, “The Scored Society: Due Process for Automated Predictions,” Wash. L. Rev. 89, no. 1 (2014). that can ensure fairness and preserve the domain of participatory rule making. The right to peer into the algorithmic black box, demand explanations and challenge automated decision making are critical to realise the right to be heard in the context of digitalised governance. The Right to Explanation in the EU General Data Protection & Regulation5757. GDPR, 2018, and the City of New York’s decision to put in place a task force to examine “automated decision systems” in public administration are some positive moves in this direction.5858. Julia Powles, “New York City’s Bold, Flawed Attempt to Make Algorithms Accountable.” The New Yorker, December 20, 2017, accessed June 14, 2018, Furthermore, algorithmic accountability needs to be complemented with strong data protection frameworks that protect citizen rights, allow them control over their data and prevent unethical and unscrupulous data driven techniques and profiteering. Policies must strike the right balance between the concern for individual privacy-personal data and considerations of data as a collective good-having public value. This means some dimensions of data and digital intelligence are treated like public resources and subject to appropriate public oversight. This is non-negotiable if data driven governance is to truly reflect democratic intent, foster inclusive development and guarantee citizen rights.

Ultimately, it is human intent that determines the democratic design or lack thereof in any given technology.5959. Gurumurthy et al., “Voice or Chatter?”, 2017. Digital intelligence and algorithmic assemblages can surveil, disenfranchise or discriminate, not because of objective metrics, but because they have not been subject to the necessary institutional oversight that underpins the realisation of socio-cultural ideals in contemporary democracies. The innovations of the future can foster equity and social justice only if the policies of today shape a mandate for digital systems that centres citizen agency and democratic accountability.

Anita Gurumurthy - India

Anita Gurumurthy is a founding member and executive director of IT for Change, where she leads research collaborations and projects in relation to the network society, with a focus on governance, democracy and gender justice. Her work reflects a keen interest in southern frameworks and the political economy of Internet governance and data and surveillance. Anita engages actively with policy makers, practitioners, social movements activists and the academic community to expand and deepen conversations on the public policy imperatives of the intertwining of the digital in all spheres of life.

Received in April 2018.

Original in English.

Deepti Bharthur - India

Deepti Bharthur is a Research Associate at IT for Change. She contributes to academic, action, and policy research in the areas of e-governance and digital citizenship, data economy, platforms and digital exclusions. She has also coordinated and co-developed design based digital interventions for gender training and leads fund-raising and grant development activities at the organisation.

Received in April 2018.

Original in English.