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.
Still, the basic process of making associations—considered a lower-level thinking technique—is the same between the test-taking pigeons and the latest AI advances. 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.
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.