VOLUME LXVI | JUN 2022

Unraveling the Challenges of Comparing Biological and Artificial Intelligences

Understanding the similarities and differences between human intelligence, animal intelligence, and artificial intelligence can be like trying to match puzzle pieces that could fit in multiple places. Previous attempts to bridge this gap have relied on measuring success in problem-solving tasks, but there is another approach called ‘signature-testing’ that focuses on finding patterns, errors, and biases in information processing. This alternative framework provides a fresh perspective on studying intelligences and opens up new avenues for exploration. By shifting the attention from success to understanding the underlying cognitive processes, we can uncover valuable insights about how biological and artificial intelligences function. To learn more about this fascinating research and delve into the intricacies of mapping different types of intelligence, dive into the full article!

Margaret Campbell

Margaret is a Scottish-Canadian educator and bioethicist from Alberta, focusing on ethical considerations in human enhancement technologies. She authors pieces on balancing ambition with moral integrity, rooted in her clan's emphasis on community and perseverance.

Making inferences from behaviour to cognition is problematic due to a many-to-one mapping problem, in which any one behaviour can be generated by multiple possible cognitive processes. Attempts to cross this inferential gap when comparing human intelligence to that of animals or machines can generate great debate. Here, we discuss the challenges of making comparisons using ‘success-testing’ approaches and call attention to an alternate experimental framework, the ‘signature-testing’ approach. Signature testing places the search for information-processing errors, biases, and other patterns centre stage, rather than focussing predominantly on problem-solving success.
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