49 citations · 59 across the 9 of their papers we have counts for
3 papers · 1 filter
Reality Check: A New Evaluation Ecosystem Is Necessary to Understand AI's Real World Effects
Reva Schwartz, Rumman Chowdhury, Akash Kundu +17
Conventional AI evaluation approaches concentrated within the AI stack exhibit systemic limitations for exploring, navigating and resolving the human and societal factors that play…
Bound by the Bounty: Collaboratively Shaping Evaluation Processes for Queer AI Harms
Organizers of QueerInAI, Nathan Dennler, Anaelia Ovalle +11
Bias evaluation benchmarks and dataset and model documentation have emerged as central processes for assessing the biases and harms of artificial intelligence (AI) systems. However…
Image Cropping on Twitter: Fairness Metrics, their Limitations, and the Importance of Representation, Design, and Agency
Kyra Yee, Uthaipon Tantipongpipat, Shubhanshu Mishra
Twitter uses machine learning to crop images, where crops are centered around the part predicted to be the most salient. In fall 2020, Twitter users raised concerns that the automa…