An Ethical Highlighter for People-Centric Dataset Creation
This work addresses the problem of ethical concerns in computer vision datasets of people, aiming to provide guidance for dataset creators and evaluators to prevent issues leading to dataset withdrawal.
This paper proposes an analytical framework to guide the ethical evaluation of existing computer vision datasets of people and assist future dataset creators in avoiding ethical missteps. The framework is informed by a review and analysis of prior works, highlighting where ethical challenges arise in people-centric datasets.
Important ethical concerns arising from computer vision datasets of people have been receiving significant attention, and a number of datasets have been withdrawn as a result. To meet the academic need for people-centric datasets, we propose an analytical framework to guide ethical evaluation of existing datasets and to serve future dataset creators in avoiding missteps. Our work is informed by a review and analysis of prior works and highlights where such ethical challenges arise.