FATE (fairness, accountability, transparency, ethics) in AI

FATE (fairness, accountability, transparency, ethics)

We study the complex social implications of AI, machine learning, data science, large-scale experimentation, and increasing automation. Our aim is to facilitate computational techniques that are both innovative and ethical while drawing on the deeper context surrounding these issues from sociology, history, and science and technology studies.

The types of questions we are exploring are:

• How can AI assist users and offer enhanced insights, while avoiding exposing them to discrimination in health, housing, law enforcement, and employment?
• How can we balance the need for efficiency and exploration with fairness and sensitivity to users?
• As our world moves toward relying on intelligent agents, how can we create a system that individuals and communities can trust?

We are committed to working closely with AI research institutions—including those highlighted below—to address the need for transparency, accountability, and fairness in AI and machine learning systems. We also publish our research in a variety of disciplines, including machine learning, information retrieval, systems, sociology, political science, and science and technology studies