How artificial intelligence can help combat systemic racism
MLK Visiting Professor S. Craig Watkins looks beyond algorithm bias to an AI future where models more effectively deal with systemic inequality.
Learning to fly
Veteran and PhD student Andrea Henshall has used MIT Open Learning to soar from the Air Force to multiple aeronautics degrees.
When it comes to AI, can we ditch the datasets?
A machine-learning model for image classification that’s trained using synthetic data can rival one trained on the real thing, a study shows.
Computational modeling guides development of new materials
Chemical engineers use neural networks to discover the properties of metal-organic frameworks, for catalysis and other applications.
Unlocking new doors to artificial intelligence
MEng graduate students engage with IBM to develop their research skills and solutions to real-world problems.
3 Questions: Fotini Christia on racial equity and data science
A new MIT-wide effort launched by the Institute for Data, Systems, and Society uses social science and computation to address systemic racism.
A new resource for teaching responsible technology development
The Social and Ethical Responsibilities of Computing publishes a collection of original pedagogical materials developed for instructional use on MIT OpenCourseWare.
The benefits of peripheral vision for machines
Researchers find similarities between how some computer-vision systems process images and how humans see out of the corners of our eyes.
Study examines how machine learning boosts manufacturing
Researchers surveyed 100 high-performing companies to determine which of them are leading adopters of machine intelligence and data analytics, and how they succeed.
Injecting fairness into machine-learning models
A new technique boosts models’ ability to reduce bias, even if the dataset used to train the model is unbalanced.
Using artificial intelligence to find anomalies hiding in massive datasets
A new machine-learning technique could pinpoint potential power grid failures or cascading traffic bottlenecks in real time.
Deep-learning technique predicts clinical treatment outcomes
A new methodology simulates counterfactual, time-varying, and dynamic treatment strategies, allowing doctors to choose the best course of action.
More sensitive X-ray imaging
Improvements in the material that converts X-rays into light, for medical or industrial images, could allow a tenfold signal enhancement.
Can machine-learning models overcome biased datasets?
A model’s ability to generalize is influenced by both the diversity of the data and the way the model is trained, researchers report.
Toward a stronger defense of personal data
Engineers build a lower-energy chip that can prevent hackers from extracting hidden information from a smart device.