MIT Professor Munther Dahleh Advocates for Interdisciplinary Approach to Solving Societal Challenges with AI
In an era increasingly defined by complex global challenges, Munther Dahleh, a professor at MIT, champions the necessity of melding data, systems, and societal understanding. Dahleh, a professor of electrical engineering and computer science, argues that the intricate problems facing the world—from climate change to AI regulation—demand a departure from traditional disciplinary silos.
Dahleh’s vision led to the creation of MIT’s Institute for Data, Systems, and Society (IDSS), designed to foster lasting collaborations across diverse fields. His recently published book, “Data, Systems, and Society: Harnessing AI for Societal Good,” details the institute’s formation and its mission to integrate engineering, policy, economics, and data analysis.
“The book is my attempt to describe our thinking that led us to the vision of the institute. What was the driving vision behind it?” Dahleh explains. He aims to guide students in addressing societal challenges using AI and data science effectively.
A core concept driving IDSS is “the triangle,” representing the interaction between physical systems, human interaction with these systems, and the policies governing them. Data acts as the central connector, informing and being informed by each component. Dahleh emphasizes the importance of understanding the societal impact of technological solutions, cautioning against marginalizing any group.
The COVID-19 pandemic serves as a prime example of this interconnectedness. The biological aspects, social behavior, and policy decisions all interacted in real-time, highlighting the need for integrated analysis and decision-making. IDSS became a crucial convening place during the pandemic due to its interdisciplinary approach.
Dahleh also addresses the ethical considerations of AI, using self-driving cars as an example. He illustrates how ethical programming decisions can have unintended negative consequences, affecting adoption rates and overall safety.
He differentiates “transdisciplinary” research from typical cross-disciplinary efforts, emphasizing the need for lasting structures like shared journals, common spaces, and a strong sense of community to maximize societal impact. IDSS aims to provide this fixed and lasting framework at MIT.
While such interactions already occurred at MIT, IDSS provides a unified space for students to engage with these principles simultaneously. The doctoral program includes core courses spanning statistics, optimization theory, computation, social sciences, and humanities.
Reflecting on his role in creating IDSS, Dahleh recognizes the importance of documenting its origins and guiding principles. His book serves as a historical record and a guide for future interdisciplinary endeavors.
“I want to have people read this and sort of understand it from a historical perspective, how something like this happened, and I did my best to make it as understandable and simple as I could,” Dahleh concludes.
