Data, Systems, and Society
Harnessing AI for Societal Good

A blueprint for addressing complex social issues using data science and AI through collaboration across academia, industry, and government.

Munther A. Dahleh (Author)

9781009446198, Cambridge University Press

Hardback, published 27 March 2025

155 pages
23.5 x 15.8 x 1.3 cm, 0.37 kg

'Munther Dahleh's breadth of knowledge is showcased in this discussion that ranges from the history of AI to the building of the world's preeminent institute of data science. Munther provides fascinating insights on the challenges, promise, and successes of using data to improve societies, and delivers a must-read for everyone from budding data scientists to policy makers and institution builders.' Matthew O. Jackson, Stanford University

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.

Preface: when problems get real
1. The pitfalls, promises, and challenges of data
2. A confluence of fields – some historical perspective
3. Who – and what – should drive decision-making? Harnessing data for the good of society
4. A transdiscipline is born
5. Complexity versus relevance – the power of abstractions
6. The care and feeding of a new discipline at MIT
7. People, programs, and research – perpetuating a virtuous cycle
8. Personal reflections on the journey
Acknowledgments
References
Index.

Subject Areas: Databases [UN]