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Prediction Machines: The Simple Economics of Artificial Intelligence
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Prediction Machines: The Simple Economics of Artificial Intelligence

3.91  ·  Rating details ·  2,343 ratings  ·  231 reviews

"What does AI mean for your business? Read this book to find out." -- Hal Varian, Chief Economist, Google

Artificial intelligence does the seemingly impossible, magically bringing machines to life--driving cars, trading stocks, and teaching children. But facing the sea change that AI will bring can be paralyzing. How should companies set strategies, governments design p

Kindle Edition, 272 pages
Published April 17th 2018 by Harvard Business Review Press
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Joe Flynn They are very different, I have recently finished both. One is an economics book on machine learning, one more of a (socia)l science book on particula…moreThey are very different, I have recently finished both. One is an economics book on machine learning, one more of a (socia)l science book on particular type of human decision making. Little overlap, though both are good 👍(less)

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Feb 05, 2019 rated it really liked it
This is a pretty good book about how artificial intelligence (AI) can be applied to businesses. It is not a technical book--you won't find any details about the wide range of technologies being used for machine learning. Instead, you will find many ingenious ways to put AI to use, as well as all the business ramifications. Three professionals from Toronto's Rotman School of management collaborated to write this book. The book is unified, and reads as if it were written by a single person. Howeve ...more
Aug 27, 2018 rated it liked it
This book is one of those “assuming a perfectly spherical cow” things.

If we reduce AI down to ML and ignore the messy realities of the real world (i.e. assume that the curse of dimensionality isn’t a thing and the only limitation on creating perfect predictions is access to sufficient training data), then we get the analysis in this book. It paints a picture of a world where the only barrier to self-driving cars is a sufficiently rich training set so that the AI can predict what a driver would d
Adrian Hon
May 07, 2018 rated it liked it
More of a 3.5 stars. If you aren't familiar with AI, this is probably a very good introduction, although the examples will date very quickly and some of them are plain incorrect (e.g. face tags now sync across Mac and iOS). The point about prediction being a central part of AI is well-made and important, but like most popular economics books, they take this new insight rather too far and with too much confidence. ...more
Scott Wozniak
Nov 04, 2018 rated it it was amazing
I've read a lot of book on artificial intelligence--this is by far the best one. The others were good, but mostly focused on defining what it is from a technical standpoint. And they all shared ideas on how to use it. But not until I read this one did I realize that all the others are focused on specific situations. This book is the first I've read that focuses on the principles behind the specifics.

For example, they frame AI as a prediction tool, and then discuss the ways that our life and wor
David Veitch
Jun 24, 2018 rated it really liked it
Shelves: tech, stats, econ
This review originally appeared on my website:

Recently I read Prediction Machines by Ajay Agrawal, Joshua Gans, and Avi Goldfarb, three professors from UofT’s Rotman School of Management. I recommend this book to anyone who wants to go ‘beyond the headlines’ with respect to what impact on the world machine learning & AI will have.


“Where others see transformational new innovation, we see a simple fall in price.”

The key idea the book revolves around is
David Ball
Jan 12, 2019 rated it really liked it
I was recently asked to organize my company’s strategic offsite. I wanted a keynote speaker who could discuss machine learning and its impact on the investment industry. I came across the name, Ajay Agrawal, the founder of Creative Destruction Labs - a remarkable organization at the forefront of science, data, and technology based in Toronto - and the author Prediction Machines. Agrawal’s premise is fascinating: as predictions get cheaper to make it will change how we use them - similar to how c ...more
Mar 08, 2019 rated it really liked it  ·  review of another edition
It is difficult to have a timely and relevant book on such a broad topic as artificial intelligence; some parts will be familiar while other parts are new and fascinating. This book would probably interest knowledge workers or anyone wanting to know how AI is changing our environment and behaviors. For example, we used to review our credit card statements to see if there were any fraudulent charges. Now based on our purchasing habits, credit card companies are flagging possible fraudulent charge ...more
Oct 11, 2018 rated it liked it
The book was a good high level introduction to AI and its implications, especially from a business perspective.

It was very repetitive at times but this allows the core message to come across clearly: AI helps with making more accurate and faster predictions. Hence, when you find that the cost of prediction falls, industries are either disrupted or new industries proliferate.

Overall, three stars (more likely makes sense as a three-and-a-half) for being informative but not providing a significant
May 19, 2018 rated it really liked it
The authors provide a good framework for understanding the changes that Artificial Intelligence effect in businesses and the economy. A book that avoids getting excessively technical (either about economics or computer science) while still avoiding the hype and shallowness of most discussions on the theme. A greater attention to the impacts of AI on outside stakeholders could have improved the overall result, but the book still achieves its framing goals.
Yousef M

A practical examination of understanding innovations In Artificial Intelligence (specifically Machine Learning) and how commercial applications of AI have already impacted (and will continue to affect) business models, the role of government, and the economic and social relationship between machines and human.


The three authors are professors of economics at U of Toronto Rotman School of Management who are also founders of an innovation incubator with investments in AI and deep learni
Joe Flynn
Aug 13, 2020 rated it really liked it
Very good (5* for narrow audience) if niche book on the economics of AI/machine learning.

By narrow audience and mean for business leaders, decision makers, and people learning more on the subject, could be students or economists. It is explicitly aimed at them not a lay audience. It is not a computer science book, rather an economics book on the the impact of the new technology of cheap prediction - wonky but not overly complex or jargon filled. Well structured, some may just read for relevent
Jul 30, 2020 rated it it was amazing
A good read for anyone with the soul of an economist and an interest in AI. The ideas presented are for the most part basic (perhaps 'foundational' is better) but they are clearly described in economic terms and in a sensible order. The authors begin by looking at the fundamental impact that AI in its current form will have on the production function of various goods/services as well as on the demand for labour, before going on to consider how company leaders might evaluate (and manage) the bene ...more
Masatoshi Nishimura
Aug 11, 2020 rated it liked it
What's magical about AI and machine learning? They let us predict better and cheaply. That's the premise of the books. Authors talk about what we as humans can do alongside with these predictions but I'd say we are far off from. Being able to perfectly predict the future. We can't even predict the GDP in 2 years. Have we heard of the pandemic coming 1 year ago? We still need to work on a lot more on being able to predict better.

Overall, I didn't find much depth in the book and it was similar t
Jay Rain
Sep 07, 2018 rated it really liked it
Rating - 8.5

Fascinating & pointed read that focuses on both the strategic & operational aspect of AI - great use of corporate examples to underly and/or analogize the decisions required to succeed going forward

Writing is very clear & concise, chapters are kept relatively short & summations at the end of each chapter reinforce the key points; Economic hypotheses are consistent, driving home a new, new normal

Key Points
Alexa has replaced the parent as the all-knowing source of information in the ey
Agustín Armellini Fischer
Nov 17, 2018 rated it it was amazing
”Prediction machines will have their most immediate impact at the decision level. But decisions have six other key elements. When someone (or something) makes a decision, they take input data from the world that enables a prediction. That prediction is possible because training occurred about relationships between different types of data and which data is most closely associated with a situation. Combining the prediction with judgment on what matters, the decision maker can then choose an action ...more
Daniela D
Aug 10, 2018 rated it it was amazing
This review has been hidden because it contains spoilers. To view it, click here.
Dane Cobain
Sep 24, 2019 rated it really liked it
I’ve been putting this book off for a little while, and I’m not really sure why. I think I thought it was going to be slow going, but it turns out that I whizzed through it in a day or so. I wasn’t too worried about the subject matter, even though it’s non-fiction about artificial intelligence from the Harvard Business Review press.

This was actually recommended to me by a client of mine, Emmanuel Fombu, who specialises in writing and talking about the future of healthcare. It was a good recommen
Maurício Linhares
Apr 28, 2019 rated it it was amazing
One of the best books on the possibilities, advantages and disadvantages of using AI, that doesn't focuses solely on buzzwords or useless examples. It starts from what actually matters in AI, prediction, goes on to talk about how we apply prediction and how multiple fields have changed completely after we decided to go for a prediction approach (like translation, that stopped being something that was trying to be done with linguistics and became a prediction problem) and how this shift in paradi ...more
Jason Furman
Apr 30, 2018 rated it it was amazing
An excellent book on the economics of Artificial Intelligence. Steeped in both economics and AI/ML, this book steers clear of hype (or anti-hype), applying standard economic concepts to a rapidly emerging phenomenon. The book is geared to business readers not economists or policymakers but it has a lot to offer to everyone.

At the heart of the book is the concept that AI/ML is a "prediction machine" that is dramatically lowering the cost of making predictions, which will lead to making it cheaper
Jan 26, 2020 rated it liked it
In a series of efforts to understand what AI means and what it actually can, I started reading books about artificial intelligence. This book argues AI is, in some sense, a prediction machine based on a large body of data. It is better than human beings at crunching numbers in a fast and accurate manner.

Prediction, however, is not tantamount to judgment, valuation, let alone decision-making. It is far from causation. It is a mere correlation between events. It lacks cultural, political, ethical
Aug 17, 2019 rated it it was amazing
Full disclosure: I read this for work, as one of the writers recently joined my organization’s board. That said, this book is great for someone familiar with the concept of AI & curious about how it may (or may not) impact business in general, but doesn’t need a length functional/technical review.

I found it really interesting and written simply; it wasn’t formulas or math but a simple cause-and-effect look at how the cost of computer-based prediction (AI) is falling, and what that will mean to
Bahruz Garamammadov
Aug 09, 2018 rated it liked it
It is a 4 star or may be even 5 star if you have not done proper reading on AI business before.
It introduces some good ideas here and there (e.g. AI canvas). But they can be derived by the reader herself, too. So nothing revolutionary. The impact of AI on micro and macro level is not discussed in detail I was expecting.
The reason I am putting 3 starts is the preface section where top AI guys say very nice (luring?) words about the book. I don’t think they mean the words they say.
But anyway, it
Kuldeep Charan
Feb 06, 2020 rated it liked it
Authors, the three economists from university of Toronto, do the great job of demystifing artificial intelligence by examining it through the lens of standard economic theory.but I'm recommends this to you only if you are a business leader, policy maker and try to understand about how artificial intelligence will shaping the world economy, then this book will helpful for you. The authors insightful journey into the topic will leave you surprised by how transformative this technological waves wil ...more
Minervas Owl
Jan 15, 2019 rated it liked it
The book does include some good examples about application of AI in the business world. It should also be useful for people who know about machine learning but not much about economics. However, the book feels a bit light for readers who has an ECON background.

The book talks about man VS. machine, but in the modeling world, people might be more interesting in the topic of classical model (linear regression/logistic regression) VS. machine learning model. The book does not cover it.
Laura Uzcategui
Feb 01, 2019 rated it it was amazing
AI and Machine Learning are on the rise now more than ever, with the increase and evolution of computational power it seems easier to work with it and even further companies such as Google, Facebook and Amazon among others are pretty well positioned on basing its Economic growth in such a technological evolment. I would recommend this book to anyone who is interested to learn more about AI and ML and understand how important it is and it will be in the near future
Sep 22, 2018 rated it it was amazing
The book breaks down how humans make decisions and how machine prediction might assist in the process very well. My favourite part is that it forces you to think about the tasks you perform at work and how they might be different (which actions we would do more of or less of) if AI is introduced into the workflow.
Mar 25, 2019 rated it liked it
Perfectly adequate summary of the functioning and implications of current machine learning / neural network models of "AI." I thought it was primarily useful for recasting AI as driving a "drop in the cost of accurate predictions" (similar to how the internet's primary innovation was a "drop in the cost of searching for relevant data"). ...more
Dec 31, 2019 rated it did not like it
This is probably a 1.5 as the book isn't unreadable, it's just not particularly informative about prediction machines aka ai or as far as I can tell how to use them in your business. I don't own a business admittedly, nor am I a manager, so maybe this is useful but it seems incredibly dumbed down and I mostly feel like I waster 7 hours or how ever long it took me to get through it. ...more
Jul 04, 2018 rated it it was ok
Shelves: technology
A quite disappointing read.. Informative, but not particularly thoughtful. The kind of book which simply “documented a lot of things I already know”. I expected a much profounder analysis if this is THE book to understand the AI economics.
Michael Madigan
Jul 25, 2018 rated it really liked it
Good high level overview of ML & AI in business. Not meant for a technical Data Scientist, but very beneficial for understand how to explain things at a high level to a non technical audience and bring up some interesting discussions.
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