Societal Impacts of Artificial Intelligence and Machine Learning

AvCarlo Lipizzi

Inbunden, Engelska, 2024

Del i serien Synthesis Lectures on Computer Science

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Häftad

496 kr

Beskrivning

This book goes beyond the current hype of expectations generated by the news on artificial intelligence and machine learning by analyzing realistic expectations for society, its limitations, and possible future scenarios for the use of this technology in our current society.

Produktinformation

Utgivningsdatum:2024-03-14
Mått:168 x 240 x 17 mm
Vikt:452 g
Format:Inbunden
Språk:Engelska
Serie:Synthesis Lectures on Computer Science
Antal sidor:149
Förlag:Springer International Publishing AG
ISBN:9783031537462

Utforska kategorier

Informationsteknik: allmänt inom Data och IT
Artificiell intelligens inom Data och IT

Mer om författaren

Carlo Lipizzi, Ph.D., is a Professor at the School of Systems and Enterprises at Stevens Institute of Technology, where he is also the Director for the Center for Complex Systems and Enterprises. He received his Ph.D. in Systems Engineering from Stevens Institute of Technology, an Executive Management degree from the International Institute for Management Development (IMD), and an M.S. in Mathematics from the University of Rome. His research focus is on machine learning, data science, and natural language processing in addition to teaching, researching, and consulting on machine learning and natural language processing.

Recensioner i media

“The book is academically grounded, it is accessible enough for general readers who want to better understand the broader implications of AI. This makes it a valuable resource for students, researchers, and professionals in fields ranging from computer science to ethics and social policy. Overall, Lipizzi’s work encourages readers to make informed decisions about AI and machine learning, providing a much-needed reality check on the often-inflated expectations for these technologies.” (Wael Badawy, Computing Reviews, October 22, 2024)

Innehållsförteckning

AI and Machine Learning: Fast Forwarding the Technology from Then to Now.- A Brief Overview of the Current Technology and Applications.- Mimicking Humans: Do We Need a Model for our Reasoning?.- The Literature and Academic Bias: Statistics on Steroids vs. Philosophy.- The News and Market Bias: Hyper Expectation Sells.- Projecting the Past to Get Indications on the Future: An Algorithm for Predictions.- Evaluating the Gap Between Expectations and Possible Future Scenarios.- The Impact on Technology: Evaluating the Current Developments Considering the Future Scenarios.- The impact on Society: The Expectations and the Possible Futures.