The Interim Order issued by the Supreme Court on 13th March come as a grave disappointment, given the large scale exclusion and cases of starvation deaths reported due to ABBA (Aadhaar Based Biometric Authentication), from the poorest districts of the country. The deadline was not relaxed for notifications under Section 7 of the Aadhaar Act, 2016 that practically make it a requirement to link Aadhaar for people to continue to have access to 139 crucial welfare schemes, several of which are citizens’ legal rights.
On 22nd March, UIDAI CEO Ajay Bhushan Pandey made a presentation before the Supreme five-judge bench to convince them that all was well with Aadhaar. On slide 42, an extremely important piece of evidence showing the utter failure of ABBA for welfare was allowed to stand without being brought to notice of the learned judges: the percentage of authentication failures. To wit, a small mathematical jugglery allowed the UIDAI to claim that auth failures measured on interactions with the government (mostly welfare) were as low as 13% from 2016 onwards. In a recent interview, UIDAI CEO was dismissive of the failure rates and called it human error.
However further examination of this innocuous detail reveals the following, much of which researchers, activists and civil society have been pointing out for years:
UIDAI’s sleight of hand in calculating the auth failure percentage
UIDAI considers successful authentication to be one that occurs once even after multiple attempts! Thus multiple failures are clubbed together and hidden when a successful authentication event occurs, which then allows UIDAI to claim “only” 13% auth failures. This statistic is of course ethically quite wrong since it completely ignores the hardship and distress faced by people each time ABBA does not work and citizens are required to make multiple trips.
A study of Kerala dairy farmers pension authentication data showed that by UIDAI’s method of calculation, only 9% of pensioners were denied pension. However a deeper look at the data immediately showed that 45% of pensioners’ authentication had failed failed once or more number of times.
The actual auth failure percentage is revealed
What should concern all of us are the actual biometric authentication failure rates which are as high as 66%! This is borne out by analysis of 4 separate datasets:
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The real impact of authentication failures - Mass distress
A study of the PDS system in Karnataka across 9.6lakh families found that introduction of biometric verification and monthly coupons has made an already cumbersome process unmanageable. People are forced to go multiple times to perform authentication; further they are forced to make visits to higher officials and have to bring a family member along, all of which adds to distress and entails a minimum opportunity cost of Rs 557 / per family / per month. 80% of the beneficiaries face serious issues with the current Public Distribution System.
Govt data shows that 850 – 900 Million people are forced to use ABBA as part of the 139 welfare schemes across India. Extrapolating from the Karnataka PDS study, ABBA is causing distress to nearly 700 million Indians.
The real impact of authentication failures - the truly excluded
Coming back to UIDAI’s data on biometric authentication failure, 13%, is a measure of the people who are truly excluded from the system. These are beneficiaries who can never get benefits, irrespective of how many times they try, what UIDAI euphemistically calls “trials”.
Now imagine the double whammy for the truly excluded: they can’t draw benefits due to ABBA issue, and if the situation persists for a period of months, they are removed from the system being labeled a “ghost”. The government in turn falsely then shows these people cut off from welfare they are legally entitled to as “Savings”. Hence over a period of time, UIDAI claims success by virtue of weeding out ghosts and the authentication success % increases.
 An opportunity cost refers to a benefit that a person could have received, but gave up to take another course of action. For example – The opportunity cost of following the process of collecting ration results in each family losing two days of work (~Rs 400). Money which could have been used to buy 8 kg of good quality rice in the open market!
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