Data, Systems, and Society: Harnessing AI for Societal Good

by Munther A Dahleh

Harnessing the power of data and AI methods to tackle complex societal challenges requires transdisciplinary collaborations across academia, industry, and government. In this compelling book, Munther A. Dahleh, founder of the MIT Institute for Data, Systems, and Society (IDSS), offers a blueprint for researchers, professionals, and institutions to create approaches to problems of high societal value using innovative, holistic, data-driven methods. Drawing on his experience at IDSS and knowledge of similar initiatives elsewhere, Dahleh describes in clear, non-technical language how statistics, data science, information and decision systems, and social and institutional behavior intersect across multiple domains. He illustrates key concepts with real-life examples from optimizing transportation to making healthcare decisions during pandemics to understanding the media's impact on elections and revolutions. Dahleh also incorporates crucial concepts such as robustness, causality, privacy, and ethics and shares key lessons learned about transdisciplinary communication and about unintended consequences of AI and algorithmic systems.

155 pages, Hardcover

Published March 27, 2025

Reviews

[Kai · Rating 5 out of 5]

This book carries some in-depth history on how mathematics and engineering-based solutions can lead to bizarre outcomes once human joins the loop. In some ways, it points out discourse in classifical fields and how they are essentially re-purposed for most AI x Society discourse.

Provided insights into what it takes to begin a new department at a school like MIT, although I don't think I fully grasp the differences between transdisciplinarity and interdisciplinarity just yet.