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, these auditing processes have been
criticized for their failure to integrate the knowledge of marginalized
communities and consider the power dynamics between auditors and the
communities. Consequently, modes of bias evaluation have been proposed that
engage impacted communities in identifying and assessing the harms of AI
systems (e.g., bias bounties). Even so, asking what marginalized communities
want from such auditing processes has been neglected. In this paper, we ask
queer communities for their positions on, and desires from, auditing processes.
To this end, we organized a participatory workshop to critique and redesign
bias bounties from queer perspectives. We found that when given space, the
scope of feedback from workshop participants goes far beyond what bias bounties
afford, with participants questioning the ownership, incentives, and efficacy
of bounties. We conclude by advocating for community ownership of bounties and
complementing bounties with participatory processes (e.g., co-creation).Comment: To appear at AIES 202