MIT Sloan’s Guide to Navigating a New Age of AI, with Sam Ransbotham, Host of the Me, Myself and AI Podcast - Modern CTO Recap

Podcast: Modern CTO

Published: 2025-12-15

Duration: 54 min

Summary

In this episode, Sam Ransbotham discusses the evolution of AI research at MIT Sloan and introduces the concept of agentic AI, highlighting the balance between data privacy and the benefits of sharing health data for better outcomes.

What Happened

In this episode, host Joel Beasley sits down with Sam Ransbotham, AI Editor at MIT Sloan Management Review and the host of the Me, Myself, and AI podcast. They delve into nine years of AI research, which originated from a broader study on analytics. Ransbotham reflects on the transition to focusing on AI in 2017 as a pivotal moment, noting, "We just happen to be in the right place at the right time." This year, the spotlight is on the notion of agentic AI, where systems are evolving to act more independently, shifting from mere tools to partners in decision-making.

Ransbotham also emphasizes the importance of how research is conducted, explaining their traditional approach of gathering insights through interviews and well-designed survey questions. He shares his background in teaching machine learning and AI, highlighting how this gives him a practical perspective on the technologies he studies. A key area of his current research involves data privacy in healthcare, advocating for a reevaluation of data sharing norms established back in 1996, arguing that the landscape of machine learning has evolved significantly since then, warranting a new conversation about privacy and data sharing for better healthcare outcomes.

Key Insights

Key Questions Answered

What is agentic AI?

Agentic AI refers to systems that are increasingly able to act independently, transitioning from tools to teammates. Ransbotham describes this shift as a significant development in AI, where these systems can operate more autonomously, allowing for more complex interactions and decision-making.

How has AI research evolved at MIT Sloan?

Ransbotham explains that the AI research at MIT Sloan started out of a broader interest in analytics, particularly after the emergence of popular data-driven narratives like Moneyball. By 2017, the focus shifted to artificial intelligence, marking a pivotal transition for their research program.

What are the current trends in healthcare data privacy?

Ransbotham is currently researching data privacy in healthcare, particularly how the balance between privacy and the benefits of data sharing has changed since the enactment of HIPAA in 1996. He argues that advancements in AI necessitate a new dialogue on how much healthcare data should be shared to improve outcomes.

What role do surveys play in AI research?

The podcast highlights the importance of conducting well-designed surveys to gather nuanced insights. Ransbotham emphasizes that the quality of the questions asked can significantly influence the results, advocating for intentional design in survey methodologies.

What are the implications of increased data availability for AI models?

Ransbotham discusses how more extensive data sets lead to improved model performance, particularly for underrepresented subgroups. He notes that advancements in algorithms mean that they are now more capable of leveraging larger data sets effectively, making a strong case for reconsidering data sharing policies.