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. Artificial Intelligence is one of the top topics today and is inflating expectations beyond what the technology can do in the foreseeable future. The future cannot be predicted, but the future of some elements of our society, such as technology, can be estimated. This book merges the modeling of human reasoning with the power of AI technology allowing readers to make more informed decisions about their personal or financial decisions or just being more educated on current technologies. This book presents a model that sketches potential future scenarios based on a discussion of the expectations today, the analysis of the current gap in the literature, and a view of possible futures in terms of technology and use cases. Specifically, this book merges literature on the technology aspects, the sociological impacts, and philosophical aspects.
Rezensionen / Stimmen
"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)
Reihe
Sprache
Verlagsort
Verlagsgruppe
Springer International Publishing
Zielgruppe
Illustrationen
2
36 farbige Abbildungen, 2 s/w Abbildungen
XVII, 149 p. 38 illus., 36 illus. in color.
Maße
Höhe: 240 mm
Breite: 168 mm
Dicke: 10 mm
Gewicht
ISBN-13
978-3-031-53749-3 (9783031537493)
DOI
10.1007/978-3-031-53747-9
Schweitzer Klassifikation
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.
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.
