Watch out, aspiring game designers; a computer may be coming for your job, too.

Researchers at the Georgia Institute of Technology will present research this week at the Foundations of Digital Games Conference about a new artificial intelligence system that analyzes a preexisting videogame, learning its rules, then procedurally generates new game levels that follow those same rules.

How it learns those rules is the crazy part: Like today's children, the AI just sits and watches YouTube videos of people playing the game in question. Through analysis of, for example, Shigeru Miyamoto's hand-crafted levels in Super Mario Bros., it begins to learn the basic rules of Mario level design: Treetops are placed on top of trunks. Gaps must only be so wide, so that Mario can leap over them successfully. Octopus enemies go underwater, Goombas go on the ground.

Georgia Institute of Technology

Super Mario Bros., the 1985 Nintendo Entertainment System game, was chosen for this presentation, but the system can also be applied to "similar" games. When the system watches the YouTube (or Twitch, or any sort of) videos, it pays particular attention to the areas of the game that the players spend the most time in—the researchers' assumption here is that these so-called "high interaction" portions of the levels are the richest for data mining about the game's design rules.

"An initial evaluation of our approach indicates an ability to produce level sections that are both playable and close to the original without hand coding any design criteria," said Matthew Guzdial, the project's lead researcher, in a blog post Wednesday. The levels that are generated, Georgia Tech said, do not appear to players to be random. The next step in the research, it said, will be to analyze how players actually play when they get into these computer-generated Mario levels, comparing it to how they interact within the hand-crafted levels of the original game.