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.
A model’s ability to generalize is influenced by both the diversity of the data and the way the model is trained, researchers report.
Online course from the MIT Center for Advanced Virtuality seeks to empower students and educators to critically engage with media.
Polish journalist Ada Petriczko, an Elizabeth Neuffer Fellow at MIT, discusses ethical and cross-border journalism, freedom of speech, and the rise of autocracy.
Assistant Professor Marzyeh Ghassemi explores how hidden biases in medical data could compromise artificial intelligence approaches.
MIT scientists discuss the future of AI with applications across many sectors, as a tool that can be both beneficial and harmful.
In 2.C01, George Barbastathis demonstrates how mechanical engineers can use their knowledge of physical systems to keep algorithms in check and develop more accurate predictions.
PhD student's research centers on ethics, including bioethics, and the philosophy of action.
Probabilistic programming language allows for fast, error-free answers to hard AI problems, including fairness.
Advancing the study and practice of thinking responsibly in computing education, research, and implementation.
Panel explores the complexities of Asian American identity and recognition, at the Institute and in higher education.
Responsible AI for Social Empowerment and Education (RAISE) seeks to empower more people to participate in, and benefit from, AI.
Black women are more vulnerable than white men, illustrating how race and gender intersect to shape health outcomes.
Future of Data, Trust, and Privacy initiative aims to address AI-driven analytics and changing attitudes about personal data.
Regina Barzilay, Fotini Christia, and Collin Stultz describe how artificial intelligence and machine learning can support fairness, personalization, and inclusiveness in health care.
Study: On social media, most people do care about accurate news but need reminders not to spread misinformation.