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HomePolicyWhat Does It Take to Identify 1.2 Billion Individuals Uniquely?

What Does It Take to Identify 1.2 Billion Individuals Uniquely?

By Ram Sewak Sharma

Unique Identification Authority of India (UIDAI) had the goal of issuing unique identification numbers to every resident of India. In a country as large as ours, this was a difficult task to achieve. UIDAI has largely accomplished this within a short period of about six years. I believe it was able to do this only because it took many innovative and bold decisions. In a recent paper I examine some of these innovations. The paper also tries to derive lessons from UIDAI that could be applied in other government projects.

The Use of Iris Scans

The UIDAI felt that unless iris images were used in addition to fingerprints, it would not be able to fulfill its mandate of unique identification. However, there were many concerns related to the use of iris images. Was this technology mature enough? Was it too expensive? Were there enough vendors in the market to prevent lock-in?

The UIDAI set up a committee to deliberate on the issue of which biometrics to collect and what standards to use for unique identification. This committee recognized the value of using iris images in improving accuracy. However, it fell short of recommending the inclusion of the iris in the biometric set and left the decision to UIDAI.

After a detailed examination, the UIDAI came to the conclusion that the inclusion of iris to the biometric set was necessary for a number of reasons, such as ensuring uniqueness of identities, and achieving greater inclusion.In retrospect, this turned out to be one of the most important decisions of the UIDAI.

On-Field Trials

The idea of using biometrics to ensure the unique identification and authentication of all residents in India was an untested one.

The practice of conducting on-field trials was an important innovation. When UIDAI began its mission, there were many questions inside and outside the organisation on whether the very idea of unique identification for every resident was feasible at all. The idea of using biometrics to ensure the unique identification and authentication of all residents in India was an untested one. There were many assumptions behind it, and the data required to test the validity of these assumptions was not available. For instance, most of the research done on using biometrics for identification or authentication was done in western countries, and that too, on relatively small numbers of people.


Success in PDS through Aadhar | Photo Courtesy: AadharNews

The knowledge which had been produced by Western researchers was not applicable in the Indian context. Could the fingerprints of rural residents and manual laborers be captured successfully, or would they be excluded from Aadhaar? What about the iris images of old or blind people? Do the devices available in the market serve the purpose? What would be the most efficient and effective way to organise the process of enrollment? These questions needed to be answered if the project was to be successful.

The strategy adopted at UIDAI was to conduct a set of trials (called Proofs of Concept, PoCs) in several states across the country. The areas were selected to be representative of real-life enrollment and authentication. A number of biometric capture devices of different makes were used, and several different enrollment processes were tried out.

The PoCs were carefully designed to answer sharply articulated questions, either to verify UIDAI’s assumptions, or to capture the data required to fill in gaps in the UIDAI’s knowledge.

In essence, the scientific method was applied to create the knowledge that was pertinent to the decisions that had to be made at UIDAI. Resources had to be allocated to this work, and in return for that, major sources of project risk were eliminated.

The results of the PoCs indicated that the major hypothesis of the UIDAI was correct: that it was indeed possible to capture biometric data that was fit for the purpose of de-duplication and verification. The results also showed that iris capture did not present any major challenges. An efficient enrollment process was devised using the data captured during these trials.


A pilot project under UID | Photo Courtesy: Live Mint


To promote such a competitive market, the Authority used a two-pronged strategy of using open standards (creating standards where there were none), and using open APIs (Application Programming Interfaces).

The last innovation considered in the paper relates to competition. Given the scale and importance of the project, the UIDAI felt it was important to increase efficiency and reduce costs by leveraging the competencies available in the private sector. At the same time, it was also essential to avoid a situation where any one private player could exercise significant power over the effective functioning of the Aadhaar system: the Authority wanted to ensure that there was a competitive market for providing services to it. To promote such a competitive market, the Authority used a two-pronged strategy of using open standards (creating standards where there were none), and using open APIs (Application Programming Interfaces).

The Authority used this strategy in procuring vendors for de-duplication. Algorithms for de-duplication had never been tested at the scale required in this project. To reduce the risk of poor quality de-duplication, the UIDAI came up with a novel solution. It decided to engage three biometric service providers (BSPs), instead of just one. These BSPs would interface with the UIDAI systems using open APIs specified by the Authority. This decision helped avoid vendor lock-in, and increased scalability.

The UIDAI selected the three top bidders on the basis of the total cost per de-duplication. Even after these three vendors were selected, the Authority was able to set up a competitive market among them, using an innovative system to distribute de-duplication requests among them. Vendors were paid on the basis of the number of de-duplication operations they were able to carry out, and the Authority allocated operations to them on the basis of how fast and how accurate they were. This led to a situation where the BSPs were constantly competing with each other to improve their speed and accuracy.

Where standards were not present, the UIDAI was willing to create new standards in order to increase competition. At the outset of UIDAI’s work, every biometric device had its own interface, distinct from the interfaces of other biometric devices. If a capture application wanted to support 10 commonly used devices, then the application developer would have to implement 10 different interfaces. This would have made it costly to bring new devices into the project, even if these new devices were cheaper and better. In order to avoid this situation, the UIDAI created an intermediate specification. Vendors could implement support for this specification, and their devices could be certified. This allowed all capture applications to work with all certified devices.


The success of the UIDAI offers many lessons for other government projects.

Perhaps the first lesson that can be drawn from it is that innovation is indeed possible within the government.

Government processes need not prevent it from taking innovative decisions. In fact, processes commonly used within the government, such as expert committees and consensus-based decision-making, can provide methods to examine difficult issues in a credible manner. High-quality procurement and project management skills can help the government outsource many functions that are currently housed within it.

The paper also suggests that scale and complexity need not be deterrents to private sector participation: in fact, the large scale of government projects can make the project more attractive to private parties. Another lesson government agencies could learn from the UIDAI is the need to test major hypotheses through field trials before launching projects at scale. Conducting such field trials provides an opportunity to change the design or the implementation roadmap well in time, thus saving precious public money from being wasted.


The UIDAI could achieve its objective because it adopted a different approach from most government organisations. It took tough decisions, such as the one to use iris images; it expended resources on building pertinent knowledge, by constantly experimenting on the ground and learning from these trials; and it exploited private-sector competition to achieve its task at the lowest cost. It should be noted that this is not an exhaustive list of its innovations, but without these three decisions, it is unlikely the UIDAI would have been able to fulfil its mission.

Well-designed pilots and field-tests can help the government evaluate the effectiveness of large programs, so that it can deploy public resources more usefully.

Even large government projects can be done fast and efficiently. Government processes need not be obstructive. In fact, the mechanisms of bureaucracy, such as committees, adherence to financial regulations, and desire for consensus, can help to resolve difficult issues and take tough decisions. Well-designed pilots and field-tests can help the government evaluate the effectiveness of large programs, so that it can deploy public resources more usefully. High quality procurement and contract-management processes can enable the government to leverage the dynamism of the private sector to provide public goods effectively.

Ram Sewak Sharma is the Secretary, Department of Electronics and Information Technology (under Ministry of Communications and Information Technology, Government of India).

This article titled ‘UIDAI’s Public Policy Innovations’ was originally published on Ajay Shah’s Blog on 8th September 2016.

Featured Image Source: Vanessa Bumbeers via Unsplash

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