Study: Some language reward models exhibit political bias
Research from the MIT Center for Constructive Communication finds this effect occurs even when reward models are trained on factual data.
Technology and society
What do we know about the economics of AI?
Nobel laureate Daron Acemoglu has long studied technology-driven growth. Here’s how he’s thinking about AI’s effect on the economy.
Artist and designer Es Devlin awarded Eugene McDermott Award in the Arts at MIT
Exploring biodiversity, linguistic diversity, and collective AI-generated poetry, her work will be honored with a $100K prize, artist residency, and public lecture at MIT in spring 2025.
MIT launches new Music Technology and Computation Graduate Program
The program will invite students to investigate new vistas at the intersection of music, computing, and technology.
Study: Transparency is often lacking in datasets used to train large language models
Researchers developed an easy-to-use tool that enables an AI practitioner to find data that suits the purpose of their model, which could improve accuracy and reduce bias.
First AI + Education Summit is an international push for “AI fluency”
The three-day, hands-on conference hosted by the MIT RAISE Initiative welcomed youths and adults from nearly 30 countries.
Dimitris Bertsimas named vice provost for open learning
Leveraging more than 35 years of experience at MIT, Bertsimas will work with partners across the Institute to transform teaching and learning on and off campus.
Helping Olympic athletes optimize their performance, one stride at a time
The startup Striv, which went through MIT’s START.nano accelerator program, has developed a shoe sole for athletes that can track force, movement, and form.
Marking a milestone: Dedication ceremony celebrates the new MIT Schwarzman College of Computing building
Members of the MIT community, supporters, and guests commemorate the opening of the new college headquarters.
When to trust an AI model
More accurate uncertainty estimates could help users decide about how and when to use machine-learning models in the real world.