THE TERM WICKED PROBLEM has become a standard way for policy analysts to describe a social issue whose solution is inherently elusive. Wicked problems have many causal factors, complex interdependencies, and no ability to test all of the possible combinations of plausible interventions. Often, the problem itself cannot be articulated in a straightforward, agreed-upon way. Classic examples of wicked problems include climate change, substance abuse, international relations, health care systems, education systems, and economic performance. No matter how far computer science advances, some social problems will remain wicked.
The latest developments in artificial intelligence represent an enormous advance in computer science. Could that technological advance give bureaucrats the tool they have been missing to allow them to plan a more efficient economy? Many advocates of central planning seem to think so. Their line of thinking appears to be:
1. Chatbots have absorbed an enormous amount of data.
2. Large amounts of data produce knowledge.
3. Knowledge will enable computers to plan the economy.
These assumptions are wrong. Chatbots have been trained to speak using large volumes of text, but they have not absorbed the knowledge contained in the text. Even if they had, there is knowledge that is critical for economic operations that is not available to a central planner or a computer.
THE PROMISE OF PATTERN MATCHING
THE NEW CHATBOTS
are trained on an enormous amount of text. But they have not absorbed this data in the sense of understanding the meaning of the text. Instead, they have found patterns in the data that enable them to write coherent paragraphs in
