Mark Díaz is a Research Scientist in Google’s Responsible AI organization. He works on ways of accounting for social bias in dataset…

Divy Thakkar is Google’s Program Manager Lead in University Relations and AI for Social Good, based in India. Divy is an human-centered…

Courtney Heldreth and Michal Lahav lead the Equitable ASR program at Google that aims to identify and eradicate biases in voice…

Opinions in PAIR Q&As are those of the interviewees, and not necessarily those of Google. In the spirit of participatory ML research, we…

Donald Martin discusses working with communities to understand complex societal issues and proactively mitigate machine learning bias.

A look at some of the ways machine learning has the potential to enrich humanities research.

Thryn Shapira discusses balancing user control and automation in AI-powered reminiscing features.

The second edition of PAIR’s AI design guidance adds action-oriented materials to help product teams put theory into practice.

Designed to help researchers and product teams better understand datasets, improve data quality and mitigate bias issues.

A look at PAIR’s papers from CHI 2021. They cover everything from AI’s role in creative endeavors to the human side of data collection.

If “just different enough” were simply a quantitative measure of difference, recommendations would be easy. Alas, it is not.

“What PAIR is reading” is a reading list series compiled by PAIR team members on a rotating basis.

Through new co-creation and speculative design methodologies, the LocAI team explores the role of local context in AI product design.

Will we learn from ML to attach confidence levels to much of what we say? The rise of hashtags gives clues.

Trust researcher Frens Kroeger talks about the need to move from explainability to trust in AI ecosystems.

On Wednesday, November 18, PAIR hosted a virtual symposium focused on boundary objects for participatory machine learning.

Catherine D’Ignazio and Lauren Klein spoke with Fernanda Viégas and Martin Wattenberg about their new book, Data Feminism.

For machine learning, expressing a lack of confidence can be a sign of strength.

Google Research’s Courtney Heldreth and Diana Akrong discuss their work on how AI can help improve the lives of farmers in the Global South

By David Weinberger

PAIR’s latest AI Explorable dives into privacy.