How Machines Are Taking Over the World's Stock Markets

Time magazine interviewed Marcos L��pez de Prado, a specialist in using machine learning for investment and finance. This quote caught my eye:

���Machine learning should be used as a research tool, not as a forecasting tool. It should be used to identify new theories, and once you identify a new theory, you throw the machine away, you don���t want the machine.���

���Marcos L��pez de Prado

A caveat: L��pez de Prado is speaking specifically about machine learning for market predictions, and he notes that markets resist prediction. “Markets evolve,” he said. “You are an investor and when you extract money from the market, the market learns to prevent you from extracting profits next year.”

Still, this resonates with a strong philosophy I’ve developed since I started working with AI and machine learning: machine learning is better used for signals than for answers.

The first generation of mainstream AI applications has focused too much on providing just-the-facts answers. The machines are flaky, with narrow and literal interpretations of the world. That means they’re brittle for decision-making. Instead of replacing human judgment, AI should amplify it. Machine learning is a crummy substitute for human judgment and individual agency, but it’s an excellent signal booster for both.

I love the way L��pez de Prado frames it: use the machines to surface patterns, signals, and suggestions to develop a theory for action���and then humans make the decisions from there.

Time | How Machines Are Taking Over the World's Stock Markets