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Preparing for the Future of Work
The Stanford Digital Economy Lab’s first conference featured conversations and insights from visionary leaders across...
How Machine Learning is Transforming Drug Discovery
Daphne Koller, a veteran of AI, explains why she left academia for a chance to change the pharmaceutical industry. ...
Developing Better, Less-Biased Facial Recognition Technology
Researchers discuss possible ways to regulate, improve this highly contentious technology during a HAI workshop.
A Legal Approach to “Affirmative Algorithms”
Solutions to fix algorithmic bias could collide with law. Two scholars propose a solution.
When Algorithmic Fairness Fixes Fail: The Case for Keeping Humans in the Loop
Attempts to fix clinical prediction algorithms to make them fair also make them less accurate.
What is Computation’s Role in Neuroscience?
Wu Tsai Neurosciences Institute's William Newsome discusses motivation, consciousness, and the fascinating challenges of...
When Algorithms Compete, Who Wins?
Over time, prediction algorithms become specialized for an increasingly narrow slice of the population, and the average...
What Can AI Learn from Human Intelligence?
HAI’s fall conference explored opportunities at a critical three-way intersection of artificial intelligence,...
Earthquake-Monitoring AI Could Help Anticipate, Understand Major Quakes
Tiny movements in Earth’s outermost layer tell us a lot about big quakes. New algorithms that work a little like human...
What Does the Future of Work Look Like?
The inaugural conference and launch of HAI’s Digital Economy Lab features experts from industry, government, and...
Assistive Feeding: AI Improves Control of Robot Arms
Algorithms developed by Stanford researchers could one day help people with disabilities intuitively control robot arms...
Susan Athey: How AI Can Aid in U.S. Economic Recovery
The HAI associate director testified to the House Budget Committee on everything from AI’s falling cost to AI-driven...