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Tattered edges always accompany biometrics-based digital ID systems like Aadhaar

Tattered edges always accompany biometrics-based digital ID systems like Aadhaar

Being fractal in nature, data reveals more detail the closer you look at it. That is true with massive citizen databases, like India’s Aadhaar digital ID program, which have practical limits and surprising tradeoffs.

Those limits, according to a recent study, result in so-called high-resolution and low-resolution citizens. The more complete and pristine that an individual’s biometric and demographic profile is in government digital ID systems — the higher their data resolution — the more fully they can participate in citizenship and collect resources shared by the state.

Of course, the opposite is true as well, according to a pair of researchers, Ranjit Singh, from the Data & Society Research Institute, and Steven Jackson, of Cornell University.

Aadhaar is like any nation’s data-based system for knowing citizens (partly through categorization), managing them and serving them. It just happens to be the largest such biometrics-supported program in the world.

Out of 1.4 billion residents of India, 1.25 billion over the past decade have identified themselves with the government by submitting fingerprints, photographs for facial recognition systems and other personal information.

That is a successful effort by anyone’s standards. But looking closer at the numbers reveals that not every Aadhar participant is an equal beneficiary of state services controlled through the 12-digit accounts.

Lower-resolution digital identity profiles typically equate to lesser access to government services, including food subsidies, and force people to exert more effort to participate in voting, for example.

It is incumbent on residents to submit all data required, something that does not always happen.

Thinly seeded Aadhaar profiles — those that are not linked to at least some of the multitude of state databases, hold profile resolution down, too.

Then there are the inescapable facts of categorization, according to the study. The ultimate categorization of all Indians would produce an excellent example of a database’s long tail. At the very end of that tail would be one person who cannot be lumped into any other set.

Obviously, that is an impossible outcome, which means that not everyone is categorized through systems even as ambitious as Aadhaar. That lowers those resident’s resolution in the eyes of the state and creates life friction for them.

The research paper points out that there is a high correlation between income and profile resolution (poorer, less-educated citizens are more likely to get shut out of participation and assistance than the wealthier and higher-educated). But it is not absolute.

That might not be an unwelcome result for some of the more-advantaged residents. High resolution brings with it greater chances of state surveillance and reduced privacy.

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