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The many pitfalls of Aadhaar

Reetika Khera | Updated on March 10, 2019 Published on March 10, 2019

Title: Dissent on Aadhaar: Big Data Meets Big Brother Editor: Reethika Khera Publisher: Orient BlackSwan Price: ₹475

An anthology, Dissent on Aadhaar, sheds light on the hidden dangers of relying on Aadhaar for delivering welfare benefits

The proponents of the UID project claimed that a large number of Indians were denied welfare benefits because people did not have any identity documents.

This assertion, not really supported with evidence, provided the initial justification for the project.

If, as the government claimed, the coverage of existing forms of ID was incomplete, then those could have been expanded to ensure wider coverage. This option was rejected on the grounds that existing databases were seriously flawed.

The Unique Identification Authority of India (UIDAI) was set up to organise enrolment and generation of Aadhaar numbers.

Apart from the National Population Register (NPR), there are two ways of enrolling for an Aadhaar number from the UIDAI directly: one, using a proof of ID and a proof of address from a list (including passports, ration cards, voter IDs, etc.) drawn up by the UIDAI; two, using the ‘introducer’ system. This was set up keeping in mind people who were lacking in pre-existing IDs.

According to a response to a Right to Information (RTI) query in 2015, only 0.03 per cent of Aadhaar numbers were issued through the introducer system. The rest were issued to those who submitted two IDs or through the NPR, raising questions about the basic premise of the Aadhaar project.

Note also that the UIDAI used those very IDs to enrol for Aadhaar that it had rejected as error-ridden or flawed.

This circularity went largely unnoticed. It has serious implications for the reliability of the Aadhaar database. Independent of biometric data (fingerprint, photograph and iris scans), the accuracy of demographic data (for example, name, date of birth, etc.) in the Aadhaar database is especially important now as it is becoming the basis for claiming benefits.

There has been no independent audit of the database, so we do not know to what extent there are errors, but media reports regularly highlight them and their fallout.

The promoters of UID also succeeded in creating the impression that Aadhaar would guarantee access to benefits, end the ‘mai-baap sarkar’ (state as lord and master) culture and enable people to assert their rights vis-a-vis state structures.

Here again, the UIDAI was misinformed. Exclusion is largely the result of a weak ‘targeting’ mechanism (identification of the poor) and the imposition of stringent caps on coverage (arising from budgetary constraints).

For instance, in the PDS, statewise central commitment was fixed at the poverty rate estimated using National Sample Survey (NSS) data from 1993–94 until the passage of the National Food Security Act (NFSA) in 2013. Caps were applied in several schemes (such as pensions and housing). The possession of an additional ID cannot solve the problem of exclusion, unless these caps are relaxed or identification methods improve.

Instead, as discussed below, Aadhaar is slowly becoming a tool of exclusion, the last hurdle after all the prior eligibility hurdles have been crossed.

For some, even enrolling for Aadhaar has not been easy.

Corruption

Another justification for the Aadhaar project was its purported role in reducing corruption in welfare programmes such as NREGA, PDS and pensions. Fraud in these programmes can be broadly categorised as ‘eligibility fraud’, ‘identity fraud’ and ‘quantity fraud’.

Eligibility fraud refers to inclusion of persons who do not meet official eligibility criteria, for example, by presenting fudged supporting documents. Quantity fraud takes the form of eligible persons receiving less than their entitlements, f

or instance by under-selling in the PDS (people are forced to sign off on more than what they actually get); in MDM, it could refer to dilution of prescribed nutrition norms (for example, not following the menu at all, or giving watery dal).

Identity fraud refers to cases where one person’s benefits are claimed fraudulently by another. In the PDS, an official may defraud the system by getting a ration card in the name of a non-existent person or dead person (‘ghosts’), or getting two cards when they are entitled to only one (‘duplicates’).

In the MDM scheme, identity fraud can take the form of inflated attendance (where costs are booked for more children than are actually being served meals). In programmes such as NREGA and SSP, which provide support in cash rather than kind, one big protection against identity fraud comes from using the banking system to transfer funds.

This eliminates, by and large, the possibility of identity fraud so long as banking norms are observed.

Biometric technology, to the extent that it is reliable, can help eliminate identity fraud, but cannot help in reducing quantity fraud or eligibility fraud. There is limited evidence on the magnitude of each type of fraud, but available evidence suggests that quantity fraud is the bigger problem (Khera 2011, 2015 and Muralidharan et al. 2018).

Therefore, contrary to the government’s understanding, Aadhaar can only play a marginal role in reducing corruption.

Aadhaar in welfare

For the PDS, NREGA, SSP and the MDM scheme, three broad themes are examined: recent evidence on corruption, the government’s claims about Aadhaar’s contribution to improved implementation of these schemes, and the emerging evidence on disruption due to Aadhaar-integration.

Aadhaar-integration is planned in two ways. One, ‘Aadhaarseeding’ refers to adding a data field for the Aadhaar number to the software (Management Information System, MIS) that is used to administer these programmes.

This is supposed to be a simple one-off activity, yet it is not quite as simple as it sounds.

For each scheme, each entitled person needs to be informed of what is needed, a range of supporting documents may be required, the number may not be correctly entered, etc.

Further, in many cases, re-enrolment of biometrics has been necessary as fingerprints or iris scans become outdated. In programmes with universal coverage, Aadhaar-seeding can help with eliminating identity fraud by weeding out ‘bogus’ beneficiaries (for example, dead, non-existent persons, etc.).

Once 100 per cent Aadhaarseeding is achieved, beneficiaries in the MIS without Aadhaar numbers are deemed to be bogus and are deleted.

Two, Aadhaar-Based Biometric Authentication (ABBA) refers to the practice of installing a Point of Sale (POS) machine equipped with a fingerprint reader and authenticating a person each time she accesses her entitlements. For instance, at the time of purchase of PDS grain each month, any one person listed on the ration card needs to authenticate themselves; similarly for pensions, elderly persons must go to the point of delivery (for example, post office or Gram Panchayat office) to authenticate themselves.

ABBA performs the role of signatures (in the earlier pre-Aadhaar days). ABBA on POS machines is currently a monthly activity, so each of its associated technologies (correct Aadhaar-seeding, mobile connectivity, electricity, functional POS machines and UIDAI servers and fingerprint recognition) need to work for a person to get her entitlement.

MEET THE AUTHOR

Reetika Khera is Associate Professor (Economics and Public Systems) at the Indian Institute of Management, Ahmedabad. She edited The Battle for Employment Guarantee (OUP, 2011).

(With permission from Orient Blackswan. Edited extracts from the chapter ‘Impact of Aadhaar in Welfare Programmes’ by Reetika Khera)

 

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Published on March 10, 2019
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