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During the Gilded Age of the late 19th century, and the early decades of the 20th century, U.S. captains of industry such as William Randolph Hearst and Jay Gould used their massive […]
By Nolan HigdonIt may be counterintuitive. But some argue that the key to training AI systems that must work in messy real-world environments, such as self-driving cars and warehouse robots, is not, […]
By Eliza StricklandDorothy R. Santos is a Filipino American storyteller, poet, artist, and scholar, and she is an assistant teaching professor in the art department and Principal Founding Faculty for Creative Technologies […]
This story is the introduction to MIT Technology Review’s series on AI colonialism, which was supported by the MIT Knight Science Journalism Fellowship Program and the Pulitzer Center. Read the […]
By Karen HaoPaidamoyo Chapfuwa, a postdoctoral research fellow at Stanford University, will deliver a talk as part of CSRAI’s Young Achievers Symposium. The Young Achievers Symposium highlights early career researchers in […]
“Challenges and Frontiers in Deploying Transparent Machine Learning” Explainable machine learning offers the potential to provide stakeholders with insights into model behavior, yet there is little understanding of how organizations […]
Su Lin Blodgett, a postdoctoral researcher in the Fairness, Accountability, Transparency, and Ethics (FATE) group at Microsoft Research Montréal, will deliver a talk as part of CSRAI’s Young Achievers Symposium. […]
“Mind the Gap: From Predictions to ML-Informed Decisions” Machine learning (ML) is increasingly being used to support decision-making in many organizational settings. However, there is currently a gap between the […]
André Brock is an Associate Professor in the School of Literature, Media & Communication at the Georgia Institute of Technology. Dr. Brock is one of the preeminent scholars of Black […]
Crystal Lee is a PhD candidate at MIT and a Senior Fellow in Responsible Computer Science at Mozilla. Her work investigates what she calls the “life-cycle of data representations,” or […]
Mark Díaz is a research scientist with the Ethical Artificial Intelligence team at Google. His primary research probes the origins of social bias in data sets and its influence on […]