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This project is part of a parallel research endeavor with GSK Manufacturing. By simulating how scientists at the Upper Providence site in...
This project is the first of two projects in collaboration with GSK. We are developing a computational simulation that allows a human use...
We recently led a workshop in Saudi Arabia, with staff from the Riyadh Development Authority, to test a new version of our CityScope plat...
The Storytelling project uses machine-based analytics to identify the qualities of engaging and marketable media. By developing models wi...
Ira Winder and the Tactile Matrix won the award for best demonstration at the IEEE Future Technologies Conference.
A case study implemented by Inioluwa Raji under the guidance of Joy Buolamwini
The Gender Shades project pilots an intersectional approach to inclusive product testing for AI.Algorithmic Bias PersistsGender Shades is...
All people are created equal, but in the eyes of the algorithm, not all faces are just yet.A new study from MIT and Microsoft r...
A new review of face recognition software found that, when identifying gender, the software is most accurate for men with light skin...
Examination of facial-analysis software shows error rate of 0.8 percent for light-skinned men, 34.7 percent for dark-skinned women.
New research out of MIT’s Media Lab is underscoring what other experts have reported or at least suspected before: facial recognition tec...
Developed by Ira Winder with the MIT Centre for Transportation and Logistics, the model seeks to use real population data and create a si...
Facebook volunteers and work-at-home moms might be making city planning decisions, thanks to AI research conducted by MIT scientists. Res...
Using computer vision to examine Google Street View, the researchers analyzed how streets and blocks have changed in five American cities.
Tested with five American cities, Streetchange quantifies the physical improvement or deterioration of neighborhoods.
A recently published paper in the Proceedings of the National Academy of Sciences (PNAS) looks at factors that predict neighborhood change.
Researchers have used machine learning to quantify the physical improvement or deterioration of neighborhoods in five American cities.
With over a billion people carrying camera-phones worldwide, we have a new opportunity to upgrade the classic bar code to encourage a fle...
Paiva, Prada, W., (Eds.)., 4738, datePaiva, Prada, W., (Eds.)., 4738, datePaiva, Prada, W., (Eds.)., 4738, date