Prediction Machines: The Simple Economics of Artificial Intelligence by Ajay Agrawal Joshua Gans & Avi Goldfarb

Prediction Machines: The Simple Economics of Artificial Intelligence by Ajay Agrawal Joshua Gans & Avi Goldfarb

Author:Ajay Agrawal, Joshua Gans & Avi Goldfarb [Agrawal, Ajay; Gans, Joshua; Goldfarb, Avi]
Language: eng
Format: epub
ISBN: 9781633695689
Publisher: Harvard Business Review Press
Published: 2018-04-17T04:00:00+00:00


13

Decomposing Decisions

Today’s AI tools are far from the machines with human-like intelligence of science fiction (often referred to as “artificial general intelligence” or AGI, or “strong AI”). The current generation of AI provides tools for prediction and little else.

This view of AI does not diminish it. As Steve Jobs once remarked, “One of the things that really separates us from the high primates is that we’re tool builders.” He used the example of the bicycle as a tool that had given people superpowers in locomotion above every other animal. And he felt the same about computers: “What a computer is to me is it’s the most remarkable tool that we’ve ever come up with, and it’s the equivalent of a bicycle for our minds.”1

Today, AI tools predict the intention of speech (Amazon’s Echo), predict command context (Apple’s Siri), predict what you want to buy (Amazon’s recommendations), predict which links will connect you to the information you want to find (Google search), predict when to apply the brakes to avoid danger (Tesla’s Autopilot), and predict the news you will want to read (Facebook’s newsfeed). None of these AI tools are performing an entire work flow. Instead, each delivers a predictive component to make it easier for someone to make a decision. AI empowers.

But how should you decide whether you should use an AI tool for a particular task in your business? Every task has a group of decisions at its heart, and those decisions have some predictive element.

We provide a way of evaluating AI within the context of a task. Just as we suggested identifying tasks by breaking down a work flow to find out whether AI might have a role, we now suggest taking each of those tasks and decomposing them into their constituent elements.



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