Identification for Development: Benefits and Challenges

Volume 2    Issue 7    July 2017

Over the past nine months, we have been listening to the experiences of lower income individuals with identity systems in India, together with the International Institute of Information Technology Bangalore (as a research partner), Storythings and the Langtons (as communication experts), and funded by Omidyar Network. We have conducted 150 interviews across rural and urban sites in Karnataka, New Delhi and surrounding Uttar Pradesh, and Assam.  We observed identity-based transactions (such as getting an Aadhaar card, buying a SIM card, being tested for a disability certificate), had a heated radio discussion, and great workshops in Delhi, Bengaluru, Washington DC and Stockholm (at SIF) for input. Our aim was to understand user experiences of identity in a digital world  – what do individuals experience, what are the pain points, how can we move towards more inclusive systems which respect privacy, agency and dignity? All these are particularly relevant in India, where Aadhaar is currently a contentious topic.

Many of our interviewees spoke of the benefit of ID systems – an Aadhaar card which enabled benefits and services; a ration card which allowed subsidized food, kerosene and medicine. On the other hand, at a time when Aadhaar memes are being shared on how it is effectively compulsory, we asked questions on privacy, exclusion, bias and repercussions for groups such as senior citizens dependent on Aadhaar verification for pensions. These concerns are not unique to Aadhaar or the Indian context of course. There have been quite a few reports on identification exclusion in the United States, including immigrants, those homeless and out of prison in Ohio, the story of Alice Faith Pennington in Texas, and the intermediaries who are trying to help those in a catch 22 situation without IDs.

We heard many concerns around all the above.

  • Several women spoke of feeling uncomfortable in “male spaces” and sluggish bureaucracy impacting more on them because of impact on time needed for family care. Men often acted on behalf of women.
  • Non-formal migrants were particularly affected by requirements such as a permanent address, not knowing local networks for help etc.
  • A visually challenged teacher told us about the long process of getting both a blind and disability certificate and that in addition, when he went to get an Aadhaar card, he was pushed about and there was no help.
  • An HIV/AIDS activist laid out his concerns around Aadhaar being necessary to obtain anti-retroviral [ART] drugs: “now what has happened in HIV-positive communities, in all the ART centres, only if we have Aadhaar cards, the ART box is given. They are making it compulsory. Due to this, our identity of HIV positive is being shown. Now that Aadhaar is compulsory, few people don’t even have Aadhaar and even if they do, and because it is linked to everything, their fear has increased. It is already a stigmatised condition. Who have they asked before doing this? Have they asked our opinion?”
  • A transgender activist was highly critical of invasive identification for “screening committees” for transgender certificates.

Identification processes are not new. But the introduction of networked systems has introduced two major challenges: the huge impact if there are any mistakes; and secondly data is more easily accessible to many more people. Again, this is not unique to India, but the burden of proving you are lies heavily on individuals and impacts even more on those who don’t have time or resources to do so.

While we agree with the above World Bank Principles (and we are cautious of generalizing from 150 interviews), we still saw confusion around processes, and what individuals perceived as an opaque state, leading to the rise of intermediaries – some helpful, others exploitative. We need more evidence on “user” needs and concerns; stronger citizen’s rights with regards to identification processes, and more efficient and effective grievance redressal. In the words of the transgender activist: “when there is an identity card, it has to be beneficial for the people of the community. We do not want cards which create problems for the community.”

Big Data for Anti-Poverty Policies

Volume 2    Issue 2    February 2017

The idea of datafication, intended as rendering many non-quantified processes into data, has become ubiquitous in business intelligence. Mayer-Schonberger and Cukier (2013) refer to big data as “a revolution that will transform how we live, work and think”. Given the pervasive nature of datafication, it makes sense to ask whether/how this can affect anti-poverty action and research on a global scale.

Since 2011, I have conducted multiple rounds of fieldwork, to monitor the evolution of the computerisation of anti-poverty programmes from back-end digitisation to biometric recognition of users. My interest in datafication sparked from the observation that data has become, over time, an integral part of the making of the nation’s anti-poverty policy.

Anti-poverty programmes are often devised as safety nets to protect the poor and vulnerable against livelihood risks. These programmes range from food security to employment guarantees, and with the advent of the Internet and mobile technologies, they have already been pervaded by many diverse forms of digitisation. However, datafication of anti-poverty programmes is radically different from digitisation.  Digitisation refers to the adoption of digitality in existing processes, whereas datafication is a process in which data become the basis for administering the programme. For example, this can be used to ascertain and assign entitlements such as food or cash to particular people on the basis of poverty status.

Examples of anti-poverty programme datafication abound worldwide. Cash transfer programmes across Africa are moving to mobile money, assigning entitlements on the basis of user data. Perhaps the most powerful example of this is that of India, where the Unique Identity Project, or Aadhaar (meaning “foundation”), proposes to collect the biometric data of all residents, storing them in a  central database.

India’s Aadhaar project is the biggest biometric project worldwide, and a good example of ICTs and datafication for development. Aadhaar provides a unique 12-digit number to those who enrol, capturing their fingerprints and iris scan. Its purpose is that of semplifying delivery of social services, enabling rapid identification of those entitled. Biometric details are linked to citizens’ data, hence a fingerprint is enough to access subsidised foodgrains or other benefits.  My research on Aadhaar reveals two important points about the datafication of anti-poverty programmes. First is their technical rationale, and second are the political consequences that the new data architecture produces.

The technical rationale lies in fighting exclusion errors, which exclude entitled users from service provision, and inclusion errors, meaning inclusion of the non-entitled. Aadhaar’s datafication discriminates the poor from the non-poor, so that a non-entitled citizen cannot receive social safety benefits. It also gives users an identity, so that poor citizens without documents can have access, though this effect is sometimes blocked by malfunctioning technology (Shagun & Aditi 2016).

The main finding of my research on Aadhaar, though, focuses on its usage in India’s main food security system, and is that the programme has visible effects on the design of anti-poverty policies. Aadhaar has the function of transforming India’s anti-poverty agenda, based on subsidies for the poor, into a system in which cash will be directly transferred to them. This embodies the Central Government’s intention to do away with subsidies, substituing them with a free-market system based on bank accounts. As it has been designed, the move is hence likely to yield strong consequences on the wider development of the nation’s anti-poverty policy.

Big data bring together a set of actors – from development managers to recipients – which needs to be made sense of as development becomes more and more data-based. In particular, datafication can do much more than streamlining existing anti-poverty programmes. Aadhaar in India, for example, is entrenched in social policies that can deeply transform the inner architecture of the social security system. As ICT4D researchers, in the study of such phenomena, it is hence important to ask if datafication is actually expanding poor people’s entitlements, or if it generates ambiguous effects on their access to social safety schemes.