Towards a calibrated trust-based approach to the use of facial recognition technology

• Main Author: CHAN, Gary Kok Yew
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2021
• Subjects: facial recognition technology; artificial intelligence; privacy; data protection; bias; trust; Science and Technology Law; Technology and Innovation
• Online Access: https://ink.library.smu.edu.sg/sol_research/3471; https://ink.library.smu.edu.sg/context/sol_research/article/5429/viewcontent/TowardsCalibratedTrust_sv.pdf
• Institution: Singapore Management University

The use of facial recognition technology has given rise to much debate relating to issues concerning privacy infringements, bias and inaccuracies of data and outputs, possibilities of covert use, the lack of data security and the problem of function creep. Certain states and jurisdictions have called for bans and moratoria on the use of facial recognition technology. This paper argues that a blanket ban on facial recognition technology would be overly precautionary without fully considering the wide range of uses and benefits of the innovation. To promote its acceptance, trust in facial recognition technology should be developed in a calibrated fashion taking into account the relative risks and benefits, risk mitigation measures and safeguards based on legal and ethical considerations. This paper recommends some guidelines for a calibrated trust-based approach.