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.
Research advances technology of AI assistance for anesthesiologists
A new deep-learning algorithm trained to optimize doses of propofol to maintain unconsciousness during general anesthesia could augment patient monitoring.
An explorer in the sprawling universe of possible chemical combinations
Heather Kulik embraces computer models as “the only way to make a dent” in the vast number of potential materials that could solve important problems.
The downside of machine learning in health care
Assistant Professor Marzyeh Ghassemi explores how hidden biases in medical data could compromise artificial intelligence approaches.
2021-22 Takeda Fellows: Leaning on AI to advance medicine for humans
New fellows are working on electronic health record algorithms, remote sensing data related to environmental health, and neural networks for the development of antibiotics.
Artificial intelligence system rapidly predicts how two proteins will attach
The machine-learning model could help scientists speed the development of new medicines.