Love, BC;
Mok, RM;
(2023)
You can't play 20 questions with nature and win redux.
Behavioral and Brain Sciences
, 46
, Article e402. 10.1017/S0140525X23001747.
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Abstract
An incomplete science begets imperfect models. Nevertheless, the target article advocates for jettisoning deep-learning models with some competency in object recognition for toy models evaluated against a checklist of laboratory findings; an approach which evokes Alan Newell's 20 questions critique. We believe their approach risks incoherency and neglects the most basic test; can the model perform its intended task.
| Type: | Article |
|---|---|
| Title: | You can't play 20 questions with nature and win redux |
| Location: | England |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1017/S0140525X23001747 |
| Publisher version: | http://dx.doi.org/10.1017/s0140525x23001747 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Div of Psychology and Lang Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Div of Psychology and Lang Sciences > Experimental Psychology |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10185677 |
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