Summary
Is the human mind an evolutionary one-off? Or does it reflect a ‘universal mind’ in which similar cognitive mechanisms repeatedly evolve via convergent evolution? Avian cognition offers a powerful model system for answering this fundamental question about the nature of our mind, because birds last shared a common ancestor with humans 312 million years ago and have evolved brains with a very different structure. However, to unlock the potential of this model system we need to robustly test whether mechanistic convergence has occurred between the minds of birds and humans (the convergent mind hypothesis) and rule out cognitive similarities between birds and humans due to shared ancestry (the ancestral mind hypothesis). UNI PROB takes advantage of decades of research on probabilistic inference, a central, but imperfect aspect of human cognition, to overcome these challenges. To test for mechanistic convergence, UNI PROB will use the cognitive biases and errors humans show in their probabilistic inferences (e.g. the conjunction fallacy, base rate neglect and the hot hand fallacy) as diagnostic signatures for the presence of a similar cognitive system in a species demonstrating the best performances on probabilistic inference tasks of any animal tested to date: the kea parrot. To test for shared ancestry, UNI PROB will present novel, non-verbal probabilistic inference problems not only to humans and kea, but also to a phylogenetic control for shared ancestry: rats. If convergent evolution has occurred, then only humans and kea will solve these problems while showing the same cognitive biases and errors. By testing for the convergent evolution of this cognitive system, UNI PROB can generate conclusive evidence that probabilistic biases are adaptive features of the human mind and discover if there is a new frontier in cognitive science, namely a universal mind that evolves repeatedly via convergent evolution.
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| Web resources: | https://cordis.europa.eu/project/id/101043986 |
| Start date: | 01-03-2023 |
| End date: | 30-04-2028 |
| Total budget - Public funding: | 2 051 921,00 Euro - 2 051 921,00 Euro |
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Original description
Is the human mind an evolutionary one-off? Or does it reflect a ‘universal mind’ in which similar cognitive mechanisms repeatedly evolve via convergent evolution? Avian cognition offers a powerful model system for answering this fundamental question about the nature of our mind, because birds last shared a common ancestor with humans 312 million years ago and have evolved brains with a very different structure. However, to unlock the potential of this model system we need to robustly test whether mechanistic convergence has occurred between the minds of birds and humans (the convergent mind hypothesis) and rule out cognitive similarities between birds and humans due to shared ancestry (the ancestral mind hypothesis). UNI PROB takes advantage of decades of research on probabilistic inference, a central, but imperfect aspect of human cognition, to overcome these challenges. To test for mechanistic convergence, UNI PROB will use the cognitive biases and errors humans show in their probabilistic inferences (e.g. the conjunction fallacy, base rate neglect and the hot hand fallacy) as diagnostic signatures for the presence of a similar cognitive system in a species demonstrating the best performances on probabilistic inference tasks of any animal tested to date: the kea parrot. To test for shared ancestry, UNI PROB will present novel, non-verbal probabilistic inference problems not only to humans and kea, but also to a phylogenetic control for shared ancestry: rats. If convergent evolution has occurred, then only humans and kea will solve these problems while showing the same cognitive biases and errors. By testing for the convergent evolution of this cognitive system, UNI PROB can generate conclusive evidence that probabilistic biases are adaptive features of the human mind and discover if there is a new frontier in cognitive science, namely a universal mind that evolves repeatedly via convergent evolution.Status
SIGNEDCall topic
ERC-2021-COGUpdate Date
09-02-2023
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