Bird-Brained AI: Pigeons and Artificial Intelligence Share Surprising Learning Techniques

Pigeon AI Technology Concept

In a study conducted by the University of Iowa, researchers found that pigeons share similarities with artificial intelligence in their learning process. By subjecting pigeons to complex categorization tests, the birds were able to reach nearly 70% accuracy through repetitive, trial-and-error learning. This form of associative learning, where connections are made between objects or patterns, is also utilized by AI systems. Despite being considered a lower-level thinking technique, associative learning allows both pigeons and AI to excel at certain tasks, challenging the perception that it is rigid and unsophisticated.

Using associative learning, in some ways a pigeon’s peck can mirror high tech.

A University of Iowa examined the workings of the pigeon brain and how the “brute force” of the bird’s learning shares similarities with artificial intelligence.

The researchers gave the pigeons complex categorization tests that high-level thinking, such as using logic or reasoning, would not aid in solving. Instead, the pigeons, by virtue of exhaustive trial and error, eventually were able to memorize enough scenarios in the test to reach nearly 70%

AI Masters

University of Iowa researchers concluded pigeons use the same base learning principle, called associative learning, as artificial intelligence. The pigeons mastered exhaustive, repetitive tests such as the one shown above. In the center square are 16 sample stimuli out of the thousands the pigeons had to categorize. The stimuli were drawn from two different categories, shown on either side. Credit: Ed Wasserman, University of Iowa

“You hear all the time about the wonders of AI, all the amazing things that it can do,” says Ed Wasserman, Stuit Professor of Experimental Psychology in the Department of Psychological and Brain Sciences at Iowa and the study’s corresponding author. “It can beat the pants off people playing chess, or at any video game, for that matter. It can beat us at all kinds of things. How does it do it? Is it smart? No, it’s using the same system or an equivalent system to what the pigeon is using here.”

The researchers sought to tease out two types of learning: one, declarative learning, is predicated on exercising reason based on a set of rules or strategies—a so-called higher level of learning attributed mostly to people. The other, associative learning, centers on recognizing and making connections between objects or patterns, such as, say, “sky-blue” and “water-wet.”

Numerous animal studied pigeon intelligence for five decades. “You have to memorize the individual stimuli or regions from where the stimuli occur in order to do the task.”

Each of the four test pigeons began by correctly answering about half the time. But over hundreds of tests, the quartet eventually upped their score to an average of 68% right.

“The pigeons are like AI masters,” Wasserman says. “They’re using a biological algorithm, the one that nature has given them, whereas the computer is using an artificial algorithm that humans gave them.”

The common denominator is that AI and pigeons both employ associative learning, and yet that base-level thinking is what allowed the pigeons to ultimately score successfully. If people were to take the same test, Wasserman says, they’d score poorly and would probably give up.

“The goal was to see to what extent a simple associative mechanism was capable of solving a task that would trouble us because people rely so heavily on rules or strategies,” Wasserman adds. “In this case, those rules would get in the way of learning. The pigeon never goes through that process. It doesn’t have that high-level thinking process. But it doesn’t get in the way of their learning. In fact, in some ways it facilitates it.”

Wasserman sees a paradox in how associative learning is viewed.

“People are wowed by AI doing amazing things using a learning algorithm much like the pigeon,” he says, “yet when people talk about associative learning in humans and animals, it is discounted as rigid and unsophisticated.”

The study, “Resolving the associative learning paradox by category learning in pigeons,” was published online on February 7 in the journal DOI: 10.1016/j.cub.2023.01.024

Study co-authors include Drew Kain, who graduated with a neuroscience degree from Iowa in 2022 and is pursuing a doctorate in neuroscience at Iowa; and Ellen O’Donoghue, who earned a doctorate in psychology at Iowa last year and is now a postdoctoral scholar at Cardiff University.

The National Institutes of Health funded the research.

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