In the new economics course 14.163 (Algorithms and Behavioral Science), students investigate the deployment of machine-learning tools and their potential to understand people, reduce bias, and improve society.
Graduate student Nolen Scruggs works with a local tenant association to address housing inequality as part of the MIT Initiative on Combatting Systemic Racism.
A new “consensus game,” developed by MIT CSAIL researchers, elevates AI’s text comprehension and generation skills.
A new algorithm learns to squish, bend, or stretch a robot’s entire body to accomplish diverse tasks like avoiding obstacles or retrieving items.
TorNet, a public artificial intelligence dataset, could help models reveal when and why tornadoes form, improving forecasters’ ability to issue warnings.
A new technique can be used to predict the actions of human or AI agents who behave suboptimally while working toward unknown goals.
MIT Sea Grant students apply machine learning to support local aquaculture hatcheries.
Lincoln Laboratory researchers are using AI to get a better picture of the atmospheric layer closest to Earth’s surface. Their techniques could improve weather and drought prediction.
MIT Center for Transportation and Logistics Director Matthias Winkenbach uses AI to make vehicle routing more efficient and adaptable for unexpected events.
Researchers create a curious machine-learning model that finds a wider variety of prompts for training a chatbot to avoid hateful or harmful output.
