Mick West describes an old gaming project where the client complained that the artificial intelligence was too good:
Twenty years ago, I was working on my first commercial game: Steve Davis World Snooker, one of the first snooker/pool games to have an AI opponent. The AI I created was very simple. The computer just picked the highest value ball that could be potted, and then potted it.Since it knew the precise positions of all the balls, it was very easy for it to pot the ball every time. This was fine for the highest level of difficulty, but for easy mode I simply gave the AI a random angular deviation to the shot.
Toward the end of the project, we got some feedback from the client that the AI was “too good.” I was puzzled by this and assumed the person wanted the expert mode to be slightly less accurate. So I changed that. But then I heard complaints about the decreased accuracy, and again that the AI was still too good.
Eventually the clients paid a visit to our offices and tried to demonstrate in person what they meant. It gradually came out that they thought the problem was actually with the “easy” mode.
They liked that the computer missed a lot of shots, but they thought that the positional play was too good. The computer always seemed to be leaving the white ball in a convenient position after its shot, either playing for safety or lining up another ball. They wanted that changed.
The problem was, there was no positional play! The eventual position of the white ball was actually completely random. The AI only calculated where the cue ball should hit the object ball in order to make that object ball go into a pocket.
It then blindly shot the cue ball toward that point with a speed proportional to the distance needed to travel, scaled by the angle, plus some fudge factor. Where the white ball went afterward was never calculated, and it quite often ended up in a pocket.
So why was it a problem? Why did they think the AI was “too good” when it was actually random?
Humans have a tendency to anthropomorphize AI opponents. We think the computer is going through a thought process just like a human would do in a similar situation.
When we see the ball end up in an advantageous position, we think the computer must have intended that to happen.
The effect is magnified here by the computer’s ability to pot a ball from any position, so for the computer, all positions are equally advantageous.
Hence, it can pot ball after ball, without having to worry about positional play. Because sinking a ball on every single shot would be impossible for a human, the player assumes that the computer is using positional play.