Silvia Masiero: Big data for anti-poverty programmes
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”, since data have transitioned from the role of optional asset to that of programmatic lens to see the world and frame it. Given the pervasive nature of datafication, it makes sense to examine its social and developmental implications, asking whether and how it can affect the ways in which anti-poverty action is conducted on a world scale.
I began collecting data on the computerisation of anti-poverty schemes, in particular food security measures, in south India in 2011, and wrote my PhD thesis on this. Since then I have conducted multiple rounds of fieldwork, to monitor the evolution of the Indian anti-poverty system from back-end digitisation to biometric recognition of users. My interest in datafication emerged from the observation that data became, over time, an integral part of the making of the nation’s anti-poverty policy.
Digitisation vs. Datafication
One important question is on the effect of big data on the social safety nets designed for the world’s poor. These nets, known as anti-poverty programmes, are devised to protect the poor and vulnerable against livelihood risks. These programmes range from food security to employment guarantees, health insurance, and anything that constitutes a primary need for below-poverty-line citizens, and are widely diffused across developing nations. With the advent of the Internet and mobile money, such programmes have already been pervaded by diverse forms of digitisation.
However, datafication of anti-poverty programmes is radically different from digitisation at large. If digitisation refers widely to the adoption of digitality in existing processes, datafication is a process in which data of beneficiaries become the basis for administering the programme. It involves systematisation of citizens’ data into databases that collects all relevant information. This allows to recognise entitled citizens, telling for example those below the poverty line from those who are not, and assign entitlements accordingly, such as food or cash transfers.
Aadhaar: Datafying India’s Anti-Poverty System
Examples of anti-poverty programme datafication abound worldwide. For example, 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. The Aadhaar project is the biggest biometric project worldwide, and provides a unique 12-digit number to all those who enrol, capturing their 10 fingerprints, iris and photograph.
The purpose of this form of datafication is that of simplifying delivery of social services, enabling rapid identification of those entitled. With Aadhaar, biometric details are linked to citizens’ data, hence a fingerprint is enough to access subsidised foodgrains or other benefits. This is hailed worldwide as an example of best practice in information and communication technology (ICT) for development, and one that can turn citizens’ data into means for more effective anti-poverty action. But as it emerged from my research, the reality may be more complex than that.
More specifically, my research on Aadhaar reveals two points on the datafication of anti-poverty programmes. First is their technical rationale, aimed at producing more effective and accountable food security systems. Second are the political consequences that the new data architecture produces.
A Politically Embedded View
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. Nevertheless, this effect is sometimes blocked by malfunctioning ICTs, resulting in below-poverty-line citizens being prevented from accessing their entitlements, resulting in technology-induced disempowerment rather than in the desired systemic improvement in service delivery.
But political consequences are visible too. 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, substituting them with a free-market system based on bank accounts. This has the potential to dismantle India’s current social policy, while many poor citizens – unbanked and suspicious of market intervention – report being in strong favour of subsidies instead of cash.
As a result, the main argument made in my research is that datafication does much more than streamlining existing anti-poverty programmes. Entrenched in extant social policies, it can deeply transform their inner architecture, as Aadhaar is doing with India’s system of social security. As big data become increasingly incorporated in anti-poverty systems worldwide, it is hence important to appraise this phenomenon through a politically embedded lens, asking whether and how datafication is actually expanding poor people’s entitlements.
I will give a seminar titled The Affordances of Big Data for Poverty Reduction: Evidence from India at the UNESCO Chair in ICT4D on 2 February 2017, 1pm to 2pm. The seminar will be hosted by Royal Holloway University of London, Queen’s Building, QB136. If this work interests you, it will be my honor and pleasure to hear from you, I am contactable at all times at firstname.lastname@example.org.
This Blog post was written by Dr Silvia Masiero, a Lecturer in International Development at the SBE, a member of the Centre for Service Management (CSM) and an affiliated member of the UNESCO Chair for ICT4D. Silvia can be contacted via S.Masiero@lboro.ac.uk