Auditing checklists and measures
Along with compliance standards and code reviews, quantifying the results for model bias is a critical step in building accountable ML systems. In this section, we will provide a list of some of these checklists and measures.
Datasheets for datasets
Datasheets for datasets is an initiative aimed at improving transparency, accountability, and an understanding of the datasets used in the development and training of ML models. Introduced by Timnit Gebru, an AI ethicist and former co-leader of Google’s ethical AI team, as well as Kate Crawford and others, this initiative proposes using a standard way to report datasets, which its creators refer to as datasheets33. Their rationale was inspired by the electronics industry, where datasheets provide important information about the components being used:
