Prediction Machines: The Simple Economics of Artificial Intelligence

by Ajay Agrawal

Humans have three types of data that machines don’t. First, human senses are powerful. In many ways, human eyes, ears, nose, and skin still surpass machine capabilities. Second, humans are the ultimate arbiters of our own preferences. Consumer data is extremely valuable because it gives prediction machines data about these preferences. Grocery stores provide discounts to consumers who use loyalty cards in order to obtain data on their behavior. Stores pay consumers to reveal their preferences. Google, Facebook, and others provide free services in exchange for data that they can use in other contexts to target advertising. Third, privacy concerns restrict the data available to machines. As long as enough people keep their sexual activity, financial situation, mental health status, and repugnant thoughts to themselves, the prediction machines will have insufficient data to predict many types of behavior. In the absence of good data, our understanding of other humans will provide a role for our judgment skills that machines cannot learn to predict.