Fair human-centric image dataset for ethical AI benchmarking.

ABSTRACT: Computer vision is central to many artificial intelligence (AI) applications, from autonomous vehicles to consumer devices. However, the data behind such technical innovations are often collected with insufficient consideration of ethical concerns^1-3. This has led to a reliance on datasets that lack diversity, perpetuate biases and are collected without the consent of data rights holders. These datasets compromise the fairness and accuracy of AI models and disenfranchise stakeholders^4-8. Although awareness of the problems of bias in computer vision technologies, particularly facial recognition, has become widespread⁹, the field lacks publicly available, consensually collected datasets for evaluating bias for most tasks^3,10,11. In response, we int

SUBMITTER: Xiang A 

PROVIDER: S-EPMC12675298 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature