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How Humans Judge Machines
How people judge humans and machines differently, in scenarios involving natural disasters, labor displacement, policing, privacy, algorithmic bias, and more.
How would you feel about losing your job to a machine? How about a tsunami alert system that fails? Would you react differently to acts of discrimination depending on whether they were carried out by a machine or by a human? What about public surveillance?
How Humans Judge Machines compares people's reactions to actions performed by humans and machines. Using data collected in dozens of experiments, this book reveals the biases that permeate human-machine interactions.
Are there conditions in which we judge machines unfairly? Is our judgment of machines affected by the moral dimensions of a scenario? Is our judgment of machine correlated with demographic factors such as education or gender?
César Hidalgo and colleagues use hard science to take on these pressing technological questions. Using randomized experiments, they create revealing counterfactuals and build statistical models to explain how people judge artificial intelligence and whether they do it fairly. Through original research, How Humans Judge Machines bring us one step closer tounderstanding the ethical consequences of AI.
How would you feel about losing your job to a machine? How about a tsunami alert system that fails? Would you react differently to acts of discrimination depending on whether they were carried out by a machine or by a human? What about public surveillance?
How Humans Judge Machines compares people's reactions to actions performed by humans and machines. Using data collected in dozens of experiments, this book reveals the biases that permeate human-machine interactions.
Are there conditions in which we judge machines unfairly? Is our judgment of machines affected by the moral dimensions of a scenario? Is our judgment of machine correlated with demographic factors such as education or gender?
César Hidalgo and colleagues use hard science to take on these pressing technological questions. Using randomized experiments, they create revealing counterfactuals and build statistical models to explain how people judge artificial intelligence and whether they do it fairly. Through original research, How Humans Judge Machines bring us one step closer tounderstanding the ethical consequences of AI.
250 pages, Kindle Edition
Published February 2, 2021
11 people are currently reading
242 people want to read
About the author
César A. Hidalgo
6 books79 followersCésar A. Hidalgo is a Chilean-Spanish-American scholar known for his contributions to economic complexity and for his applied work on data visualization and artificial intelligence. Hidalgo is a tenured professor at the Toulouse School of Economics’ (TSE) Department of Social and Behavioral Sciences and the head of the Center for Collective Learning a multidisciplinary research laboratory with offices at Institute for Advanced Study (IAST) at TSE and the Corvinus Institute of Advanced Studies (CIAS) at Corvinus University of Budapest. He is also an Honorary Professor at the Alliance Manchester Business School of the University of Manchester.
Between 2010 and 2019 Hidalgo led MIT’s Collective Learning group and prior to that he was a research fellow at Harvard’s Kennedy School of Government. Hidalgo is also a founder of Datawheel, an award winning company specialized in public data distribution and economic development strategy. He holds a PhD in Physics from the University of Notre Dame and a Bachelor in Physics from Universidad Católica de Chile.
Hidalgo’s contributions have been recognized with numerous awards, including the 2018 Lagrange Prize and three Webby Awards. Hidalgo's has authored dozens of peer-reviewed papers and of three books: Why Information Grows (Basic Books, 2015), The Atlas of Economic Complexity (MIT Press, 2014), and How Humans Judge Machines (MIT Press, 2021). His latest book, The Infinite Alphabet (Allan Lane/Penguin-Random House, 2025) explores the principles governing the growth, value, and diffusion of knowledge.
Between 2010 and 2019 Hidalgo led MIT’s Collective Learning group and prior to that he was a research fellow at Harvard’s Kennedy School of Government. Hidalgo is also a founder of Datawheel, an award winning company specialized in public data distribution and economic development strategy. He holds a PhD in Physics from the University of Notre Dame and a Bachelor in Physics from Universidad Católica de Chile.
Hidalgo’s contributions have been recognized with numerous awards, including the 2018 Lagrange Prize and three Webby Awards. Hidalgo's has authored dozens of peer-reviewed papers and of three books: Why Information Grows (Basic Books, 2015), The Atlas of Economic Complexity (MIT Press, 2014), and How Humans Judge Machines (MIT Press, 2021). His latest book, The Infinite Alphabet (Allan Lane/Penguin-Random House, 2025) explores the principles governing the growth, value, and diffusion of knowledge.
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Displaying 1 - 5 of 5 reviews
November 9, 2020
Concise, short read on the role (and responsibility) of humans in developing machine intelligence.
April 3, 2021
Cool graphics design on every chapter beginning.
Although the book is mainly about how humans see the actions of fellow humans and machines, the book provides lots of insights and future directions on how AI product liability should be approached. The book also models the wrongness using mathematical models with moral dimensions as variables. I liked the conclusion part in particular where the author brings bureaucracy as a scenario and draws conclusions based on how the people view bureaucracy, whether machine like system or attributing the function to leaders running the bureaucracy.
Although the book is mainly about how humans see the actions of fellow humans and machines, the book provides lots of insights and future directions on how AI product liability should be approached. The book also models the wrongness using mathematical models with moral dimensions as variables. I liked the conclusion part in particular where the author brings bureaucracy as a scenario and draws conclusions based on how the people view bureaucracy, whether machine like system or attributing the function to leaders running the bureaucracy.
November 1, 2021
This book could perfectly be a long paper. It doesn't mean that is not an important and (mostly) easy to read book about how people judge machines and their behavior compared to human counterparts. It is always good to have some numbers on things that appear more or less intuitive. As the authors reported, it would be great to have similar data in different cultural contexts (the study was done in the US, using Mechanical Turk, with all the good and bad that it implies).
At the end, we need more studies like this, across countries, ages, etc.
At the end, we need more studies like this, across countries, ages, etc.
November 3, 2025
I mean it’s fine. I did not enjoy this book since it was required reading for a critical thinking course. But I won’t give it a poor score just because the content is not all that interesting to me. This book is still a valuable tool for others.
May 5, 2022
A fantastic book about the relationship of humans and machines in the mind of humans.
Displaying 1 - 5 of 5 reviews