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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.

Read the ABOUT ML Reference Document here.


ABOUT ML Resources Library

A library of resources designed to help organizations and individuals begin implementing AI/ML transparency at scale.


Get Involved

Start Here

Contribute to future work

Our goal for 2021 is to design testable pilots in a multi stakeholder manner. To make this process more tractable, we’ve broken this into two different workstreams. Each button below leads to a key subtask in this process, and we invite you to share your thoughts, comments, and feedback on any that you are interested in.

Process workstream

Help us solve the challenge of how documentation can be created at scale within an organization.

Artifact workstream

Join the debate on what information stakeholders deserve to know about ML systems, and how that information should be presented.

Future Work

Designing ABOUT ML pilots
Running + Testing ABOUT ML pilots

Implement and scale what works


Deployed Examples of ML Documentation

See real-world deployed examples of ML documentation which can focus on datasets, models, and ML systems. Provide your feedback on these examples as part of ABOUT ML’s public feedback comment process.

To guide ABOUT ML, let the steering committee know what you think of these examples. Which questions are useful? What questions are these examples missing? Is there anything about the format of one of these examples that is effective? Leave a comment with the comment button on the left.


The ABOUT ML group of advisors and experts is comprised of experts, researchers and practitioners recruited from a diverse set of PAI Partner organizations. We continue to provide meaningful updates and invitations for them to participate in the work. We are grateful for their contributions to this community work enabling responsible AI by increasing transparency and accountability with machine learning system documentation.

Himani Agrawal
Data Scientist
AT&T Research Labs

Norberto Andrade
Privacy & Public Policy Manager

Amir Banifatemi
General Manager, Innovation & Growth

Rachel Bellamy
Principal Researcher & Manager
Human-AI Collaboration IBM

Umang Bhatt
Student Fellow
Leverhulme Centre for The Future of Intelligence

Diane Chang
Distinguished Data Scientist

Jacomo Corbo
Chief Scientist

Daniel First
Associate/Data Scientist

Ben Garfinkel
Research Fellow
Future of Humanity Institute

Jeremy Gillula
Tech Projects Director

Jerremy Holland
Director of AI Research

Sara Jordan
Senior Counsel, AI & Ethics
Future of Privacy Forum

Joohyung Lee
Corporate VP/Head of Lab

Brenda Leong
Senior Counsel & Director 
of Strategy
Future of Privacy Forum

Tyler Liechty
Data Engineer

Lassana Magassa
Graduate Research Associate
Tech Policy Lab/University of Washington

Meg Mitchell
AI/ML Researcher

Amanda Navarro
Managing Director

Sinead O’Brien
AI/ML Engagement Lead

Irina Raicu
Director, Internet Ethics Program
Markkula Center for Applied Ethics

Deborah Raji
Mozilla Foundation

Becca Ricks
Mozilla Foundation

Andrew Selbst
Postdoctoral Scholar
Data & Society

Ramya Sethuraman
Product Manager

Moninder Singh
Research Staff Member

Spandana Singh
Policy Analyst
Open Technology Institute

Amber Sinha
Senior Programme Manager
Centre for Internet & Society

Michael Spranger
Senior Research Scientist
Collaboration Office Sony

Andrew Strait
Associate Director of Research Partnerships
ADA Lovelace Institute

Hanna Wallach
Senior Principal Researcher

Adrian Weller
Senior Research Fellow
Leverhulme Center for the Future of Intelligence

Abigail Wen
Author & Filmmaker

Alexander Wong
Vision & Image Processing(VIP) Research Group(University of Waterloo)

Jennifer Wortman Vaughan
Senior Principal Researcher

Andrew Zaldivar
Senior Developer Advocate

We also consult with many of our other Partners.

Steering Committee

Michael Hind

Distinguished Research Staff Member

IBM Research

Meg Mitchell

Research and Chief Ethics Scientist

Hugging Face

Kush R Varshney

Distinguished Research Scientist and Manager

IBM Research

Hanna Wallach

Partner Research Manager

Microsoft Research

Jennifer Wortman Vaughan

Senior Principal Researcher



As you explore ABOUT ML, we invite you to learn more about this work’s origins and the amazing researchers who helped from the very beginning.

Notably, Hanna Wallach, Meg Mitchell, Jenn Wortman Vaughan, Timnit Gebru, Lassana Magassa, and Jingying Yang were instrumental in the foundations of the work and we thank them for their significant contributions. Francesa Rossi and Kush Varshney, both from IBM, and Eric Horvitz at Microsoft were also key contributors in making this work possible. Please read more about the origins of ABOUT ML and contributors to the project below.

Webinar: Understanding the Value of ML Documentation