Data, Systems, and Society

Auteur
Munther A. Dahleh is William Coolidge Professor of Electrical Engineering and Computer Science and Founding Director of the Institute for Data, Systems, and Society at the Massachusetts Institute of Technology. He is well known for his seminal contributions to the foundations of the field of decisions under uncertainty, impacting several application domains including transportation systems, power grids, and social, economic, and financial networks. He is a four-time recipient of the IEEE CSS George S. Axelby Outstanding Paper Award for papers in the 'IEEE Transactions on Automatic Control' and the 1993 recipient of the Eckman Award for outstanding control engineers under thirty-five.

Texte du rabat

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.

Contenu
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.