How A.I. Can Solve World’s Problems: Challenge It to a Game of Bridge

Artificial intelligence is increasingly making important decisions, but we can’t have faith in its choices unless we know how they’re made. When a decision about a mortgage, a health care policy or a medical treatment is challenged, we currently turn to a human for resolution. If and when artificial intelligence becomes the ultimate arbiter, its reasoning needs to be clear enough so that if it’s mistaken, we can intervene. Trouble is, AI learning is opaque — it involves building associations and relying on patterns that humans can’t understand, and the tech industry is struggling to make AI explain itself.

To solve this transparency problem, I’d like to challenge AI to a game of bridge.

If AI is able to map its decision-making process to the rules of a game, it could then lay out those rules for us to see. IBM’s Deep Blue learned the rules of chess so well that it was able to beat human champ Garry Kasparov. Google DeepMind’s AlphaGo, likewise, beat top-ranked Go player Lee Sedol. In these cases, we were able to understand how the AI made its choices because we spoke the same language: the rules of the game.

AI that could not only win the game but also explain the rationale for its moves in response to a string of unknown factors would have limitless applications.

The next step is to try to apply this shared decision-making language to nongame contexts. Could AI address real-world problems, ranging from energy…