When software developers were given access to an AI coding tool, productivity increased — particularly among newer hires and more junior employees.
Machine learning can drive climate action initiatives, but its widespread use could have negative implications, according to Climate Change AI’s Priya Donti.
From designing intelligent decision processes to tapping the full power of deep learning, here are data practices to adopt now from MIT Sloan analytics faculty.
A “red light, yellow light, green light” framework can help companies streamline AI governance and decision-making.
MIT Sloan research explores the promise and limits of using AI in medicine, hiring, and creative pursuits.
Three AI implementation guides from MIT provide research-based insights on AI maturity, which AI tool to use, and the human capabilities that will be even more essential in the future.
2 MIT researchers say we’ve got to rethink mind and machine, product and platform, and core and crowd.
Work against algorithmic bias and climate change challenges “status quo … preoccupied with reproducing itself.”
The work tasks that AI is least likely to replace are those that depend on uniquely human capacities, such as empathy, judgment, ethics, and hope.
MIT Sloan Action Learning - In each project the ultimate goal is to improve the quality of healthcare and patient outcomes.
