A realistic picture of how AI fits into today’s economy

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There’s a difference between a shiny new thing and a thing that works. You just need to look at the annual Consumer Electronics Show (CES) in Las Vegas to see how much of the technology we create just doesn’t cut it and gets tossed into the wastebin of innovation because it doesn’t find a working business model.

Where does artificial intelligence stand? Recent advances in machine learning have surely created a lot of excitement — and fear — around artificial intelligence. Game-playing bots that outmatch human champions. A text-generating AI that writes articles in mere seconds. Medical imaging algorithms that detect cancer years in advance.

How much of these technological advances are actually making it to the mainstream? How much of it is unwarranted hype? How will AI affect jobs? How is machine learning changing the business model of companies?

In their book Prediction Machines: The Simple Economics of Artificial Intelligence, professors Ajay Agrawal, Joshua Gans, and Avi Goldfarb, answer these and many other questions and paint a very realistic picture of the how machine learning fits into today’s economy.

Prediction Machines provides a very accessible and high-level overview of machine learning and the power and limits of the predictions provided by AI algorithms. The book is a must-read for business leaders and executives. But it is also a very valuable study for engineers and scientists who want to understand the implications of their innovations and how the technology they create integrates into the greater economy.

The book contains plenty of detailed and useful information and examples of how machine learning is changing how we do things. Here are some of my key takeaways.

[Read: Are EVs too expensive? Here are 5 common myths, debunked]

The power of prediction machines

There are many misunderstandings about the meaning and difference of artificial intelligence, machine learning, and other related terms. There’s are also a lot of scientific discussions about AI’s advances toward human-level thinking and understanding and whether singularity is within reach or not.

But the authors of Prediction Machines break down the current state of AI to a very simple albeit unexciting concept: prediction. “The new wave of artificial intelligence does not actually bring us intelligence but instead a critical component of intelligence — prediction,” they write.

The predictive power of machine learning algorithms remains the core concept of the book and helps us understand its effect at various levels.

Prediction Machines book cover
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