About the Project
ABOUT ML (Annotation and Benchmarking on Understanding and Transparency of Machine learning Lifecycles) is a multi-year, multi-stakeholder initiative led by PAI. This initiative aims to bring together a diverse range of perspectives to develop, test, and implement machine learning system documentation practices at scale.
The initiative is an ongoing, iterative process designed to co-evolve with the rapidly advancing field of AI development and deployment. In recognition that documentation is both an artifact and a process, ABOUT ML is structured into an artifact workstream and a process workstream. In 2020, ABOUT ML will produce one resource for each workstream:
A database of documentation questions, adapted by the domain of the machine learning application
A research-based guide to initiating and scaling a documentation pilot.
Documentation for machine learning systems can contribute to responsible AI development by bringing more transparency into “black box” models and by bridging the gap between increasingly pervasive AI ethics principles and day-to-day operations and practice. Documentation can shape practice because by asking the right question at the right time in the AI development process, teams will become more likely to identify potential issues and take appropriate mitigating actions.