Author ORCID Identifier

Mangalam - https://orcid.org/0000-0001-6369-0414

Document Type

Article

Publication Date

8-2020

Abstract

Povinelli’s (2000) studies with chimpanzees (Pan troglodytes) reported in “Folk Physics for Apes” were firmly grounded in a Cartesian view of knowledge, which posits that humans use abstract concepts such as force, gravity, and shape to reason causally about events and plan our actions (with tools in the case of Folk Physics for Apes). Povinelli set out to examine if chimpanzees, like humans, used causal concepts to solve mechanical problems, as the Cartesian view predicts. However, Povinelli’s findings uniformly challenged his expectations. Povinelli’s book stimulated research and contributed to the development of alternate understandings of how animals (including humans) use tools. We summarize one alternative approach, Ecological psychology, elucidate how predictions drawn from this approach, explain (post hoc) the findings presented in Folk Physics for Apes, and suggest directions for continuing work on this topic from an Ecological approach. Ecological psychology posits direct perception and requires analysis of the animal-task-environment system, thus providing a distinct alternative to the Cartesian approach. Twenty years on, Povinelli’s elegant exposition in Folk Physics for Apes of the Cartesian view of how animals use tools, and his efforts to explain the findings of his experiments in this framework, still stimulate those who study animal behavior and cognition from different theoretical perspectives.

Comments

This is an open access article licensed under the Creative Commons Attribution license. https://doi.org/10.26451/abc.07.03.12.2020

DOI

https://doi.org/10.26451/abc.07.03.12.2020

Journal Title

Animal Behavior and Congnition

Volume

7

Issue

3

First Page

457

Last Page

473

Creative Commons License

Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.

Included in

Biomechanics Commons

Share

COinS