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.
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.
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.
Fostering media literacy in the age of deepfakes
Online course from the MIT Center for Advanced Virtuality seeks to empower students and educators to critically engage with media.
3 Questions: Women’s rights and rising threats to press freedom worldwide
Polish journalist Ada Petriczko, an Elizabeth Neuffer Fellow at MIT, discusses ethical and cross-border journalism, freedom of speech, and the rise of autocracy.
The downside of machine learning in health care
Assistant Professor Marzyeh Ghassemi explores how hidden biases in medical data could compromise artificial intelligence approaches.
The promise and pitfalls of artificial intelligence explored at TEDxMIT event
MIT scientists discuss the future of AI with applications across many sectors, as a tool that can be both beneficial and harmful.
Physics and the machine-learning “black box”
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.
3 Questions: Sophie Gibert on ethics in action
PhD student's research centers on ethics, including bioethics, and the philosophy of action.
Exact symbolic artificial intelligence for faster, better assessment of AI fairness
Probabilistic programming language allows for fast, error-free answers to hard AI problems, including fairness.
3 Questions: David Kaiser and Julie Shah on social and ethical responsibilities of computing
Advancing the study and practice of thinking responsibly in computing education, research, and implementation.
A searching discussion about being Asian American at MIT
Panel explores the complexities of Asian American identity and recognition, at the Institute and in higher education.
Helping students of all ages flourish in the era of artificial intelligence
Responsible AI for Social Empowerment and Education (RAISE) seeks to empower more people to participate in, and benefit from, AI.
Study: Sex differences in Covid-19 mortality vary across racial groups
Black women are more vulnerable than white men, illustrating how race and gender intersect to shape health outcomes.
MIT launches new data privacy-focused initiative
Future of Data, Trust, and Privacy initiative aims to address AI-driven analytics and changing attitudes about personal data.