NASSCOM's Feedback on the Discussion Paper- Responsible AI for All: Adopting the Framework – A use case approach on Facial Recognition Technology | nasscom | The Official Community of Indian IT Industry

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NASSCOM's Feedback on the Discussion Paper- Responsible AI for All: Adopting the Framework – A use case approach on Facial Recognition Technology

Sudipto

@Sudipto

January 2, 2023

Public Policy

390

Background

In November 2022, NITI Aayog released a Discussion Paper (Paper) "Responsible AI for All: Adopting the Framework - A use case appraoch on Facial Recognition Technology" soliciting feedback from the public On December 30, 2022, NASSCOM submitted its feedback on the Discussion Paper.

General Recommendation

At a broader level, our recommendation is that any use of facial recognition technology (FRT) system needs to be evaluated basis the use case. This will help identify the nature of risks and challenges involved and develop the necessary precautionary measures. We have analysed the use-case of FRT system in other jurisdictions (Border control: Global Entry in United States of America; Airports and security clearance: Face Express in Japan; and Forensic identification: INPOL-Z in Germany) as listed in Annex 2 of the Paper. The aim is to identify key takeaways from use cases to inform the NITI Aayog’s thinking on responsible use of FRT.

Summary of recommendations:

Requirements like, appropriateness of explainability, external review and constitution of ethics committee should be based on nature of risk associated (like, whether the use of FRT affects the human rights, etc.) with the FRT.
FRT systems whose output can be used in a manner that affects human rights/freedom/diversity/privacy should be subject to stricter requirements.
Adverse event reporting system may be established to collate adverse incidents, establishing a post-market monitoring mechanism.
Considering the complex nature of the technology being used, full explainability may not always be feasible. In that event, alternatives such as human review, audits, and limiting use cases could be utilised.
Procurement requirements and conditions to be guided by the level of risks or harm and the use case of the FRT system in question.
Clear division of responsibilities and liabilities between developer and deployer should be made (through contractual framework) depending on the nature of application of FRT.
List different risk management functions to be considered by entities at the different steps of the FRT supply chain for fixing the accountability.
Difference in terms of responsibilities between developer and deployer must be considered while framing the grievance redress mechanism, else this can create duplication and inefficiency.
To avoid regulatory challenges that may arise due to fragmented approach in the implementation of FRTs across India, a coordination mechanism should be established for uniformity and certainty when FRT is deployed by multiple state agencies for analogous purposes (like surveillance and law enforcement).
Any future framework of FRT should be harmonised with the Digital Personal Data Protection Bill, 2022. To illustrate, while consent is an essential mechanism of responsible and ethical FRT system, excessive reliance on consent would not align with the DPDP Bill.
Imposing a blanket need for consent at every stage should be commensurate with the risks involved. Scope for inferred consent should be included in defined circumstances based on the risk involved.
Focus should be on highlighting use cases that merit additional safeguards and/or data types that require additional safeguards with examples to justify the same.

Please see the attachment for our detailed submission and recommendations.

For more details, please write to Varun Sen at: varun@nasscom.in or Sudipto Banerjee at: sudipto@nasscom.in.

artificial intelligence facial recognition technology NITI Aayog Digi Yatra

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Sudipto

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