For the third year in a row, MIT Sloan Management Review and Boston Consulting Group have assembled an international panel of AI experts that includes academics and practitioners to help us gain insights into how responsible artificial intelligence (RAI) is being implemented in organizations worldwide. Last year, we published a report titled...

If you’ve played with Photoshop’s Generative Fill feature or worked in Nvidia’s Omniverse platform, you’ve touched tools that Patrick Hebron’s work has made possible. A dual major in philosophy and film production, Patrick approaches creative pursuits with a deep curiosity and the belief that if a “tool gets used in exactly the way that we anticipated,...

Paul Garland We all love a good “what went wrong” story. Analyses of corporate failures are a staple of the management genre, alerting leaders to hidden dangers and unexamined vulnerabilities. But studying our weaknesses and mitigating them only goes so far; it doesn’t actually tell us how to succeed. Establishing a lasting advantage requires...

Auditing Algorithmic Risk Cathy O’Neil, Jake Appel, and Sam Tyner-Monroe Key Insight: A set of frameworks can help organizations identify potential harms posed by algorithms, AI tools, or large language models (LLMs). Top Takeaways: As business uses of artificial intelligence, LLMs, and other algorithmic applications expand, so, too, does...

Paul Garland “How can we protect the privacy of our customers’ personal data while leveraging that data via AI and analytics?” This question reflects a growing internal dilemma as companies pursue advanced analytics and artificial intelligence. The troves of data that customers’ ever-more-digitalized lives produce can be a rich source of insight...

Paul Garland The glare of attention on generative AI threatens to overshadow advanced analytics. Companies pouring resources into much-hyped large language models (LLMs) such as ChatGPT risk neglecting advanced analytics and their proven value for improving business decisions and processes, such as predicting the next best offer for each customer...