Melding data, systems, and society
A new book from Professor Munther Dahleh details the creation of a unique kind of transdisciplinary center, uniting many specialties through a common need for data science.
A new book from Professor Munther Dahleh details the creation of a unique kind of transdisciplinary center, uniting many specialties through a common need for data science.
Forget optimists vs. Luddites. Most people evaluate AI based on its perceived capability and their need for personalization.
The winning essay of the Envisioning the Future of Computing Prize puts health care disparities at the forefront.
With demand for cement alternatives rising, an MIT team uses machine learning to hunt for new ingredients across the scientific literature.
The Institute-wide effort aims to bolster industry and create jobs by driving innovation across vital manufacturing sectors.
Sendhil Mullainathan brings a lifetime of unique perspectives to research in behavioral economics and machine learning.
Words like “no” and “not” can cause this popular class of AI models to fail unexpectedly in high-stakes settings, such as medical diagnosis.
With support from the Stone Foundation, the center will advance cutting-edge research and inform policy.
MAD Fellow Alexander Htet Kyaw connects humans, machines, and the physical world using AI and augmented reality.
A new method from the MIT-IBM Watson AI Lab helps large language models to steer their own responses toward safer, more ethical, value-aligned outputs.