The importance of addressing fairness and bias in artificial intelligence (AI) systems cannot
be over-emphasized. Mainstream media has been awashed with news of incidents around …

Recent work has advocated for training AI models on ever-larger datasets, arguing that as
the size of a dataset increases, the performance of a model trained on that dataset will …

Members of the Human-Robot Interaction (HRI) and Artificial Intelligence (AI) communities
have proposed Large Language Models (LLMs) as a promising resource for robotics tasks …

Multimodal AI models capable of associating images and text hold promise for numerous
domains, ranging from automated image captioning to accessibility applications for blind …

Computer vision systems have witnessed rapid progress over the past two decades due to
multiple advances in the field. As these systems are increasingly being deployed in high …

Artificial Intelligence (AI) has a growing impact on how research is conducted. While AI can
drastically increase efficiency, its use presents serious risks for research integrity, security …

Generative audio models are rapidly advancing in both capabilities and public utilization--
several powerful generative audio models have readily available open weights, and some …

The demands for accurate and representative generative AI systems means there is an
increased demand on participatory evaluation structures. While these participatory …

Images generated by text-to-image (T2I) models often exhibit visual biases and stereotypes
of concepts such as culture and profession. Existing quantitative measures of stereotypes …

Shortcuts, also described as Clever Hans behavior, spurious correlations, or confounders,
present a significant challenge in machine learning and AI, critically affecting model …