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portada How To Think About AI. A Guide For The Perplexed (en Inglés)
Formato
Libro Físico
Editorial
Año
2027
Idioma
Inglés
N° páginas
224
Encuadernación
Tapa Blanda
Dimensiones
7.72x5.08 in
ISBN13
9780197932650

How To Think About AI. A Guide For The Perplexed (en Inglés)

Richard Susskind (Autor) · OUP Oxford · Tapa Blanda

How To Think About AI. A Guide For The Perplexed (en Inglés) - Richard Susskind

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Reseña del libro "How To Think About AI. A Guide For The Perplexed (en Inglés)"

Susskind tells the unfolding story of AI, explaining what it does and how it has evolved, offering unconventional views on its ups and downs. He suggests that the main error we make in thinking about AI is anthropomorphizing, that is, evaluating and discussing current and future AI systems by reference to humans.

Revealing the unfolding story of Artificial Intelligence, Richard Susskind presents a short non-technical guide which challenges us to think differently about AI. Susskind brings AI out of the computing laboratories, out of big tech companies, out of start-ups — and into everyday life.

In recent years, and certainly since the launch of ChatGPT, there has been massive public and professional interest in Artificial Intelligence. Much of the related discussion is Manichean — both in opposition to and in support of AI. People are confused about what AI is, what it can and cannot do, what is likely in the future, and, in broad terms, whether AI is good or bad for humanity. There is also confusion about how we might regulate AI or if we should do so at all; and over where and how we might draw moral boundaries on its use.

In How To Think About AI, Richard Susskind explores the unraveling history of Artificial Intelligence, explaining what it does and how it has evolved. Throughout, the author offers unconventional views on AI: looking at the ups and downs (arguing that the 'winter' of AI was caused by the birth of the web); reflecting on AI's depiction in fiction and film; positioning ChatGPT and generative AI as the latest chapter in artificial intelligence; and positing that we are still at the foothills of developments. Susskind suggests that the main error we make in thinking about AI is anthropomorphizing, that is, evaluating and discussing current and future AI systems by reference to humans, our abilities, our strengths and limitations, and our ways of living, working, and thinking. This book gives readers a different roadmap.

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