Demographic Bias: A Challenge for Fingervein Recognition Systems?
This addresses a potential fairness issue in biometric systems for users, but it is incremental as it extends bias analysis from facial recognition to fingervein recognition.
The paper investigated whether fingervein recognition systems exhibit demographic bias based on sex and age, benchmarking several popular algorithms and finding no evidence of bias in the tested systems, though it notes the need for larger datasets to confirm these results.
Recently, concerns regarding potential biases in the underlying algorithms of many automated systems (including biometrics) have been raised. In this context, a biased algorithm produces statistically different outcomes for different groups of individuals based on certain (often protected by anti-discrimination legislation) attributes such as sex and age. While several preliminary studies investigating this matter for facial recognition algorithms do exist, said topic has not yet been addressed for vascular biometric characteristics. Accordingly, in this paper, several popular types of recognition algorithms are benchmarked to ascertain the matter for fingervein recognition. The experimental evaluation suggests lack of bias for the tested algorithms, although future works with larger datasets are needed to validate and confirm those preliminary results.