After many years during which it languished in relative obscurity, in remote classrooms of computer science departments and in small prototype projects for tech companies, artificial intelligence (AI) is now a searingly hot topic across the media. Yet much of the public discussion is so feverish that an understanding of the basic scientific and engineering elements of the field is easily lost, often resulting in exaggerated claims, as well as dangerously neglected threats.

This concise and sober book presents a brief history of AI, explaining in clear language the central engineering innovations that have produced the current revolution. It distinguishes between imagined dangers and the very real problems that AI is creating. Spread across seven short and accessible chapters, this book explains the developments behind deep learning and the applications of deep neural networks (DNNs). It addresses both the imagined and actual risks posed by the AI revolution, before outlining the elements of a rational public policy on AI, covering topics like tech monopolies, disinformation, bias, hate speech, intellectual property rights, and inequality.

Suitable for the general reader, Understanding the Artificial Intelligence Revolution: Between Catastrophe and Utopia is the ideal book for anyone seeking a clear and informed introduction to AI.

After many years during which it languished in relative obscurity, in remote classrooms of computer science departments and in small prototype projects for tech companies, artificial intelligence (AI) is now a searingly hot topic across the media. Yet much of the public discussion is so feverish that an understanding of the basic scientific and engineering elements of the field is easily lost, often resulting in exaggerated claims, as well as dangerously neglected threats.

This concise and sober book presents a brief history of AI, explaining in clear language the central engineering innovations that have produced the current revolution. It distinguishes between imagined dangers and the very real problems that AI is creating. Spread across seven short and accessible chapters, this book explains the developments behind deep learning and the applications of deep neural networks (DNNs). It addresses both the imagined and actual risks posed by the AI revolution, before outlining the elements of a rational public policy on AI, covering topics like tech monopolies, disinformation, bias, hate speech, intellectual property rights, and inequality.

Suitable for the general reader, Understanding the Artificial Intelligence Revolution: Between Catastrophe and Utopia is the ideal book for anyone seeking a clear and informed introduction to AI.

After many years during which it languished in relative obscurity, in remote classrooms of computer science departments and in small prototype projects for tech companies, artificial intelligence (AI) is now a searingly hot topic across the media. Yet much of the public discussion is so feverish that an understanding of the basic scientific and engineering elements of the field is easily lost, often resulting in exaggerated claims, as well as dangerously neglected threats.

This concise and sober book presents a brief history of AI, explaining in clear language the central engineering innovations that have produced the current revolution. It distinguishes between imagined dangers and the very real problems that AI is creating. Spread across seven short and accessible chapters, this book explains the developments behind deep learning and the applications of deep neural networks (DNNs). It addresses both the imagined and actual risks posed by the AI revolution, before outlining the elements of a rational public policy on AI, covering topics like tech monopolies, disinformation, bias, hate speech, intellectual property rights, and inequality.

Suitable for the general reader, Understanding the Artificial Intelligence Revolution: Between Catastrophe and Utopia is the ideal book for anyone seeking a clear and informed introduction to AI.