Abstract
It is highly difficult to pinpoint what is going through an animal’s mind when it appears to solve a problem by ‘insight’. Here, we searched for an information processing error during the emergence of seemingly insightful stone dropping in New Caledonian crows. We presented these birds with the platform apparatus, where a heavy object needs to be dropped down a tube and onto a platform in order to trigger the release of food. Our results show New Caledonian crows exhibit a weight inattention error: they do not attend to the weight of an object when innovating stone dropping. This suggests that these crows do not use an understanding of force when solving the platform task in a seemingly insightful manner. Our findings showcase the power of the signature-testing approach, where experiments search for information processing biases, errors and limits, in order to make strong inferences about the functioning of animal minds.
Highlights
When faced with a difficult problem, humans can often spend a prolonged period of time trying to solve the problem without success, only for the solution to arrive suddenly and unexpectedly, often accompanied by a subjective ‘aha’ moment
Only one bird had a significant preference for either block; picking the heavy block 15 times out of 20 (Binomial test p = 0.041.) The other birds had no significant preference for either block
The other crow continued stone dropping for the 10 trials of the experiment, without showing any preference for heavy blocks
Summary
When faced with a difficult problem, humans can often spend a prolonged period of time trying to solve the problem without success, only for the solution to arrive suddenly and unexpectedly, often accompanied by a subjective ‘aha’ moment. Such ‘insightful’ problem solving is an implicit process. How insight is defined in the animal cognition literature varies; one widely used definition, from Thorpe [8], states that insight occurs with “the sudden production of a new adaptive response not arrived at by trial-anderror behaviour”, while more recent definitions are more mechanistic, emphasising the importance of concepts such as mental models, means-end understanding, and causal knowledge in producing insightful behaviour [9,10,11].
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