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The Shortcut
An influential scientist in the field of artificial intelligence (AI) explains its fundamental concepts and how it is changing culture and society . A particular form of AI is now embedded in our tech, our infrastructure, and our lives. How did it get there? Where and why should we be concerned? And what should we do now? The Why Intelligent Machines Do Not Think Like Us provides an accessible yet probing exposure of AI in its prevalent form today, proposing a new narrative to connect and make sense of events that have happened in the recent tumultuous past, and enabling us to think soberly about the road ahead. This book is divided into ten carefully crafted and easily digestible chapters. Each chapter grapples with an important question for AI. Ranging from the scientific concepts that underpin the technology to wider implications for society, it develops a unified description using tools from different disciplines and avoiding unnecessary abstractions or words that end with -ism. The book uses real examples wherever possible, introducing the reader to the people who have created some of these technologies and to ideas shaping modern society that originate from the technical side of AI. It contains important practical advice about how we should approach AI in the future without promoting exaggerated hypes or fears. Entertaining and disturbing but always thoughtful, The Shortcut confronts the hidden logic of AI while preserving a space for human dignity. It is essential reading for anyone with an interest in AI, the history of technology, and the history of ideas. General readers will come away much more informed about how AI really works today and what we should do next.
186 pages, Paperback
Published March 8, 2023
2 people are currently reading
30 people want to read
About the author
Nello Cristianini
20 books1 followerNello Cristianini is a professor of Artificial Intelligence in the Department of Computer Science at the University of Bath.
His research contributions encompass the fields of machine learning, artificial intelligence and bioinformatics. Particularly, his work has focused on statistical analysis of learning algorithms, to its application to support vector machines, kernel methods and other algorithms. Cristianini is the co-author of two widely known books in machine learning, An Introduction to Support Vector Machines and Kernel Methods for Pattern Analysis and a book in bioinformatics, "Introduction to Computational Genomics".
Recent research has focused on the philosophical challenges posed by modern artificial intelligence, big-data analysis of newspapers content, the analysis of social media content. Previous research had focused on statistical pattern analysis; machine learning and artificial intelligence; machine translation; bioinformatics.
As a practitioner of data-driven AI and Machine Learning, Cristianini frequently gives public talks about the need for a deeper ethical understanding of the effects of modern data-science on society.
Cristianini is a recipient of the Royal Society Wolfson Research Merit Award and of a European Research Council Advanced Grant.
His research contributions encompass the fields of machine learning, artificial intelligence and bioinformatics. Particularly, his work has focused on statistical analysis of learning algorithms, to its application to support vector machines, kernel methods and other algorithms. Cristianini is the co-author of two widely known books in machine learning, An Introduction to Support Vector Machines and Kernel Methods for Pattern Analysis and a book in bioinformatics, "Introduction to Computational Genomics".
Recent research has focused on the philosophical challenges posed by modern artificial intelligence, big-data analysis of newspapers content, the analysis of social media content. Previous research had focused on statistical pattern analysis; machine learning and artificial intelligence; machine translation; bioinformatics.
As a practitioner of data-driven AI and Machine Learning, Cristianini frequently gives public talks about the need for a deeper ethical understanding of the effects of modern data-science on society.
Cristianini is a recipient of the Royal Society Wolfson Research Merit Award and of a European Research Council Advanced Grant.
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April 26, 2024
Don't let your boyfriend read Superintelligence.
The last couple years in machine learning work have been, broadly, a technological and economic triumph in keeping with an intellectual and moral catastrophe. Research and development has collapsed into data scaling, artists have become the main casualties of an economy already apathetic to their existence, and the only institutions casually concerned with the public interest, (academic labs) have been all but shut out from social media APIs. Silicon Valley's figureheads--and a concerning number of its engineers--have adopted Andreeson Horowitz's self-serving, fundamentally incurious "techno-optimist" posture, and, in a dialectical sort of way, manifested the conditions for a techno-pessimist, "neo-Luddite" counterculture. Neither current is capable or perhaps even incentivized to meaningfully reconcile contemporary society with technology.
Cristianini has written a humble sort of thing: an ambitious revisionist history, but one primarily concerned with what is not yet known. His narrative of intelligent machines leads not to Chat-GPT or a more speculative fantasy of humanoid robotics, but to Facebook, Twitter, and other familiar platforms. It is an accessible introduction to machine learning, eschewing details for broader (but largely explanatory) changes in research methodology: from logic operations to statistical correlations.
When someone--particularly a man--expresses a newfound interest in AI, this will minimize the damage.
P.S. It is strange and bad that this history excludes Fei-Fei Li's major contributions to neural network research. I do not understand this choice.
The last couple years in machine learning work have been, broadly, a technological and economic triumph in keeping with an intellectual and moral catastrophe. Research and development has collapsed into data scaling, artists have become the main casualties of an economy already apathetic to their existence, and the only institutions casually concerned with the public interest, (academic labs) have been all but shut out from social media APIs. Silicon Valley's figureheads--and a concerning number of its engineers--have adopted Andreeson Horowitz's self-serving, fundamentally incurious "techno-optimist" posture, and, in a dialectical sort of way, manifested the conditions for a techno-pessimist, "neo-Luddite" counterculture. Neither current is capable or perhaps even incentivized to meaningfully reconcile contemporary society with technology.
Cristianini has written a humble sort of thing: an ambitious revisionist history, but one primarily concerned with what is not yet known. His narrative of intelligent machines leads not to Chat-GPT or a more speculative fantasy of humanoid robotics, but to Facebook, Twitter, and other familiar platforms. It is an accessible introduction to machine learning, eschewing details for broader (but largely explanatory) changes in research methodology: from logic operations to statistical correlations.
When someone--particularly a man--expresses a newfound interest in AI, this will minimize the damage.
P.S. It is strange and bad that this history excludes Fei-Fei Li's major contributions to neural network research. I do not understand this choice.
Displaying 1 of 1 review