According to a new study published in iScience, the way pigeons problem-solve matches artificial intelligence. The Guardian reports: In the study, 24 pigeons were given a variety of visual tasks, some of which they learned to categorize in a matter of days, and others in a matter of weeks. The researchers found evidence that the mechanism that pigeons used to make correct choices is similar to the method that AI models use to make the right predictions. “Pigeon behavior suggests that nature has created an algorithm that is highly effective in learning very challenging tasks,” said Edward Wasserman, study co-author and professor of experimental psychology at the University of Iowa. “Not necessarily with the greatest speed, but with great consistency.”
On a screen, pigeons were shown different stimuli, like lines of different width, placement and orientation, as well as sectioned and concentric rings. Each bird had to peck a button on the right or left to decide which category they belonged to. If they got it correct, they got food, in the form of a pellet; if they got it wrong, they got nothing. “Pigeons don’t need a rule,” said Brandon Turner, lead author of the study and professor of psychology at Ohio State University. Instead they learn through trial and error. For example, when they were given a visual, say “category A”, anything that looked close to that they also classified as “category A”, tapping into their ability to identify similarities.
Over the course of the experiments, pigeons improved their ability to make right choices from 55% to 95% of the time when it came to some of the simpler tasks. Presented with a more complex challenge, their accuracy went up from 55% to 68%. In an AI model, the main goal is to recognize patterns and make decisions. Pigeons, as research shows, can do the same. Learning from consequences, when not given a food pellet, pigeons have a remarkable ability to correct their errors. Similarity function is also at play for pigeons, by using their ability to find resemblance between two objects. “With just those two mechanisms alone, you can define a neural network or an artificial intelligent machine to basically solve these categorization problems,” said Turner. “It stands to reason that the mechanisms that are present in the AI are also present in the pigeon.”
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