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Different Physical Intuitions Exist Between Tasks, Not Domains

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Abstract

Does human behavior exploit deep and accurate knowledge about how the world works, or does it rely on shallow and often inaccurate heuristics? This fundamental question is rooted in a classic dichotomy in psychology: human intuitions about even simple scenarios can be poor, yet their behaviors can exceed the capabilities of even the most advanced machines. One domain where such a dichotomy has classically been demonstrated is intuitive physics. Here we demonstrate that this dichotomy is rooted in how physical knowledge is measured: extrapolation of ballistic motion is idiosyncratic and erroneous when people draw the trajectories but consistent with accurate physical inferences under uncertainty when people use the same trajectories to catch a ball or release it to hit a target. Our results suggest that the contrast between rich and calibrated versus poor and inaccurate patterns of physical reasoning exists as a result of using different systems of knowledge across tasks, rather than being driven solely by a universal system of knowledge that is inconsistent across physical principles.

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Notes

  1. We could not simply determine where the drawn predictions crossed the line of each bucket height, since many drawings did not extend that far or ended at the left or right side of the drawing area. Therefore, we used a common extrapolation technique for all drawings.

  2. Non-linear extrapolated trajectories, such as adding a quadratic term to the path, would make these non-physical models equivalent to a physical model of a parabolic ballistic trajectory; thus, only linear extrapolation paths are guaranteed to differ from physical extrapolation.

  3. For instance, if the bucket were directly below the center of the pendulum, there are two periods when the ball could be released: when it is to the left of the bucket and traveling rightward or when it is to the right of the bucket and traveling leftward.

  4. Even if the “impetus” model is not included (because no participants drew diagrams consistent with impetus physics), there are still no participants who shared a non-physical classification between the interactive and drawing tasks. All except one of the participants who were best fit by the impetus model would be best fit by the calibrated model if the impetus model were not included, and that remaining participant drew a calibrated path but was best fit by the angled model.

  5. Because we captured points along the drawn line as part of the task we did not have third parties mark each drawing, but the technique for extrapolating lines from the drawn points was identical.

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Acknowledgments

The authors would like to thank Frank Jäkel, Nancy Kanwisher, Joshua Tenenbaum, Gary Marcus, and Ernest Davis for their helpful discussion and comments, as well as Chaz Firestone and one anonymous reviewer for their insightful feedback.

KAS and EV were supported by NSF CPS grant 1239323 and a UCSD Interdisciplinary Collaboratories grant. KAS, EV, and PB were supported by the Intelligence Advanced Research Projects Activity (IARPA) via Department of the Interior (DOI) contract D10PC20023. KAS was supported by CBMM funded by NSF STC award CCF-1231216 and ONR grant N00014-13-1-0333.

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Authors and Affiliations

  1. Department of Brain and Cognitive Science, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA, 02139, USA

    Kevin A Smith & Peter W Battaglia

  2. DeepMind, London, EC4A 3TW, UK

    Peter W Battaglia

  3. Department of Psychology, University of California San Diego, San Diego, CA, 92093, USA

    Edward Vul

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  1. Kevin A Smith
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Correspondence to Kevin A Smith.

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Smith, K.A., Battaglia, P.W. & Vul, E. Different Physical Intuitions Exist Between Tasks, Not Domains. Comput Brain Behav 1, 101–118 (2018). https://doi.org/10.1007/s42113-018-0007-3

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