Fighting discrimination in mortgage lending
A new technique for removing bias in datasets can enable machine-learning models to make loan approval predictions that are both fair and accurate.
A new technique for removing bias in datasets can enable machine-learning models to make loan approval predictions that are both fair and accurate.
Associate professor and principal investigator with the MIT Schwarzman College of Computing’s Science Hub discusses the future of robotics and the importance of industry-academia collaborations.
MIT AI Hardware Program launches with five inaugural companies to advance AI technologies for the next decade.
“Privid” could help officials gather secure public health data or enable transportation departments to monitor the density and flow of pedestrians, without learning personal information about people.
An MIT team incorporates AI to facilitate the detection of an intriguing materials phenomenon that can lead to electronics without energy dissipation.
CSAIL scientists came up with a learning pipeline for the four-legged robot that learns to run entirely by trial and error in simulation.
Veteran and PhD student Andrea Henshall has used MIT Open Learning to soar from the Air Force to multiple aeronautics degrees.
Chemical engineers use neural networks to discover the properties of metal-organic frameworks, for catalysis and other applications.
In collaboration with industry representatives, Momentum students tackle wildfire suppression and search-and-rescue missions while building soft skills.
Empowering a global community of learners in displacement.
MEng graduate students engage with IBM to develop their research skills and solutions to real-world problems.
The Social and Ethical Responsibilities of Computing publishes a collection of original pedagogical materials developed for instructional use on MIT OpenCourseWare.
Researchers surveyed 100 high-performing companies to determine which of them are leading adopters of machine intelligence and data analytics, and how they succeed.
A new technique boosts models’ ability to reduce bias, even if the dataset used to train the model is unbalanced.
A new machine-learning technique could pinpoint potential power grid failures or cascading traffic bottlenecks in real time.