Q&A: Global challenges surrounding the deployment of AI
Aleksander Madry, Asu Ozdaglar, and Luis Videgaray, co-chairs of the AI Policy Forum, discuss key issues facing the AI policy landscape today.
Aleksander Madry, Asu Ozdaglar, and Luis Videgaray, co-chairs of the AI Policy Forum, discuss key issues facing the AI policy landscape today.
In MIT’s Experiential Ethics summer course, students grapple with real-world ethical decision making, often while interning in the very fields they’re studying.
Danielle Li takes a close look at scientific practices and organizational decisions — and provides data about improving them.
Chaplain to the Institute and associate dean of the Office of Religious, Spiritual, and Ethical Life reflects on the office’s priorities and how the community still surprises her.
The faculty members will work together to advance the cross-cutting initiative of the MIT Schwarzman College of Computing.
New research ties inaccuracies in pulse oximeter readings to racial disparities in treatment and outcomes.
The MIT Museum director describes how the museum is reinventing itself for the 21st century.
“Interpretability methods” seek to shed light on how machine-learning models make predictions, but researchers say to proceed with caution.
Methods that make a machine-learning model’s predictions more accurate overall can reduce accuracy for underrepresented subgroups. A new approach can help.
The second AI Policy Forum Symposium convened global stakeholders across sectors to discuss critical policy questions in artificial intelligence.
In annual T.T. and W.F. Chao Distinguished Buddhist Lecture Series, Baker takes up “Environment, Ethics and Embodiment: Buddhist Approaches to Climate Change.”
MIT political science master’s student Milain Fayulu is building brands to bring change to his home country.
MIT's Council for the Uncertain Human Future convenes small circle groups to reckon with the climate crisis in solidarity.
PhD candidate Jonathan Zong found a lack of systems that earn and maintain public trust in large-scale online research — so he made one himself.
A multidisciplinary team of graduate students helps infuse ethical computing content into MIT’s largest machine learning course.