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Prediction Machines: The Simple Economics of Artificial Intelligence

3.93  ·  Rating details ·  1,768 ratings  ·  185 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

Kindle Edition, 272 pages
Published April 17th 2018 by Harvard Business Review Press
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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. ...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 isnt 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 do,
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.
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
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 ...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 ...more
David Veitch
Jun 24, 2018 rated it really liked it
Shelves: stats, econ, tech
This review originally appeared on my website:

Recently I read Prediction Machines by Ajay Agrawal, Joshua Gans, and Avi Goldfarb, three professors from UofTs 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
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
David Ball
Jan 12, 2019 rated it really liked it
I was recently asked to organize my companys 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. Agrawals premise is fascinating: as predictions get cheaper to make it will change how we use them - similar to how ...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.
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
Dane Cobain
Sep 24, 2019 rated it really liked it
Ive been putting this book off for a little while, and Im 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 wasnt too worried about the subject matter, even though its 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
Aug 17, 2019 rated it it was amazing
Full disclosure: I read this for work, as one of the writers recently joined my organizations 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 doesnt need a length functional/technical review.

I found it really interesting and written simply; it wasnt 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
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
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 dont think they mean the words they say.
But anyway, it
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.
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
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.
Nopadol Rompho
Nov 18, 2019 rated it really liked it
This book is easy to read. If you want to know how AI can affect our lives, I would recommend this book to you. There is no difficult technical term in the book, which I like it a lot. This book was written by economists so you can see another perspectives about AI.
Kent Winward
Feb 26, 2019 rated it really liked it
AI becomes more understandable in terms of economic analysis. The economic point of view oddly added more insight into the potential changes AI could bring.
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").
Gavin Blasczyk
Jan 10, 2019 rated it it was amazing
Title: Prediction Machines
Authors: Ajay Agrawal, Joshua Gans, Avi Goldfarb
Publish Year: 2018
An economists viewpoint on what will occur as our ability to better predict outcomes increases. What will change and what will become more or less valuable?
Part 1: Prediction
- Prediction has become cheap, which means more people will utilize it.
o Arithmetic and computing used to be expensive. As it became cheaper, people began experimenting and using arithmetic to solve problems that werent typically
Hungy Ye
Jan 01, 2019 rated it really liked it
The manager's handbook on how to pitch AI projects to your boss
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 ...more
Peter McCluskey
Sep 17, 2019 rated it really liked it
Three economists decided to write about AI. They got excited about AI, and that distracted them enough that they only said a modest amount about the standard economics principles that laymen need to better understand. As a result, the book ended up mostly being simple descriptions of topics on which the authors had limited expertise. I noticed fewer amateurish mistakes than I expected from this strategy, and they mostly end up doing a good job of describing AI in ways that are mildly helpful to ...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.
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.
A pragmatic way to think about AI. Perhaps the best book at the intersection of AI and business out right now.
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
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