Prediction Machines: The Simple Economics of Artificial Intelligence

by Ajay Agrawal

AI is a prediction technology, predictions are inputs to decision making, and economics provides a perfect framework for understanding the trade-offs underlying any decision.

Our first key insight is that the new wave of artificial intelligence does not actually bring us intelligence but instead a critical component of intelligence—prediction.

Each startup in our lab is predicated on exploiting the benefits of better prediction.

Economics provides a well-established foundation for understanding uncertainty and what it means for decision making. As better prediction reduces uncertainty, we use economics to tell you what AI means for the decisions you make in the course of your business. This, in turn, provides insight into which AI tools are likely to deliver the highest return on investment for the work flows inside your business. This then leads to a framework for designing business strategies, such as how you might rethink the scale and scope of your business to exploit the new economic realities predicated on cheap prediction. Finally, we lay out the major trade-offs associated with AI on jobs, on the concentration of corporate power, on privacy, and on geopolitics.

the economics toolkit for evaluating the implications of a drop in the cost of prediction is rock solid;

More data means less privacy. More speed means less accuracy. More autonomy means less control.

The rise of the internet was a drop in the cost of distribution, communication, and search.

Reframing a technological advance as a shift from expensive to cheap or from scarce to abundant is invaluable for thinking about how it will affect your business.

When search became cheap, companies that made money selling search through other means

found themselves in a competitive crisis. At the same time, companies that relied on people finding them (for example, self-publishing authors, sellers of obscure collectibles, homegrown moviemakers) prospered.

When the price of something fundamental drops drastically, the whole world can change.

Light is so cheap that you use it with abandon.

Virtually nothing we have today would be possible had the cost of artificial light not collapsed to almost nothing.

Technological change makes things cheap that were once expensive.

Tim Bresnahan, a Stanford economist and one of our mentors, pointed out that computers do arithmetic and nothing more.

we also used the newly cheap arithmetic for applications that were not traditionally associated with arithmetic, like music.

Charles Babbage

Arithmetic was such an important input into so many things that, when it became cheap, just as light had before, it changed the world.