Demographic Fairness in Biometric Systems: What do the Experts say?

TL;DR

This paper summarizes expert opinions and discussions on demographic fairness in biometric systems, highlighting evaluation metrics, transparency, legal, and ethical issues in the context of widespread biometric applications.

Contribution

It provides a comprehensive overview of expert perspectives on demographic fairness, evaluation standards, and ethical considerations in biometric technology.

Findings

Experts emphasize the importance of transparent evaluation metrics.

Discussion on the need for standards and regulations in biometric fairness.

Highlighting ethical and legal challenges in deploying biometric systems.

Abstract

Algorithmic decision systems have frequently been labelled as "biased", "racist", "sexist", or "unfair" by numerous media outlets, organisations, and researchers. There is an ongoing debate whether such assessments are justified and whether citizens and policymakers should be concerned. These and other related matters have recently become a hot topic in the context of biometric technologies, which are ubiquitous in personal, commercial, and governmental applications. Biometrics represent an essential component of many surveillance, access control, and operational identity management systems, thus directly or indirectly affecting billions of people all around the world. In order to provide a forum for experts in the field, the European Association for Biometrics organised an event series with "demographic fairness in biometric systems" as an overarching theme. The events featured presentations by international experts from academic, industry, and governmental organisations and facilitated interactions and discussions between the experts and the audience. Further consultation of experts was undertaken by means of a questionnaire. This work summarises opinions of experts and findings of said events on the topic of demographic fairness in biometric systems including several important aspects such as the developments of evaluation metrics and standards as well as related issues, e.g. the need for transparency and explainability in biometric systems or legal and ethical issues.