Building explainability into the components of machine-learning models
Researchers develop tools to help data scientists make the features used in machine-learning models more understandable for end users.
Researchers develop tools to help data scientists make the features used in machine-learning models more understandable for end users.
Graduate student Sarah Cen explores the interplay between humans and artificial intelligence systems, to help build accountability and trust.
Researchers use artificial intelligence to help autonomous vehicles avoid idling at red lights.
For individuals who communicate using a single switch, a new interface learns how they make selections, and then self-adjusts accordingly.
Researchers design a user-friendly interface that helps nonexperts make forecasts using data collected over time.
Veteran and PhD student Andrea Henshall has used MIT Open Learning to soar from the Air Force to multiple aeronautics degrees.
The computer-vision technique behind these maps could help avoid contrail production, reducing aviation’s climate impact.
MIT Energy Initiative edX course asks students to rethink how we operate power systems.
A new model shows that the more polarized and hyperconnected a social network is, the more likely misinformation will spread.
Strategy accelerates the best algorithmic solvers for large sets of cities.
A new method forces a machine learning model to focus on more data when learning a task, which leads to more reliable predictions.
A visual analytics tool helps child welfare specialists understand machine learning predictions that can assist them in screening cases.
A new control system, demonstrated using MIT’s robotic mini cheetah, enables four-legged robots to jump across uneven terrain in real-time.
Researchers hope more user-friendly machine-learning systems will enable nonexperts to analyze big data — but can such systems ever be completely autonomous?
PhD student Heng Yang is developing algorithms to help driverless vehicles quickly and accurately assess their surroundings.