Dear all,
You are warmly invited to the next MQ Philosophy Work in Progress (WIP) seminar which will be given by *Raphaël Millière (University of Oxford).* The details are as follows: Date: Tuesday 18th of August Time: 13:00-14:00 Room: 17WW 113 Zoom Link: *https://macquarie.zoom.us/j/86932261160?pwd=k5qDEdWLQa9hfux1D3bhduEaaNt3U5.1* <https://aus01.safelinks.protection.outlook.com/?url=https%3A%2F%2Fmacquarie.zoom.us%2Fj%2F86932261160%3Fpwd%3Dk5qDEdWLQa9hfux1D3bhduEaaNt3U5.1&data=05%7C02%7Cemily.hughes%40mq.edu.au%7Cc45d45a4293a4de7129b08def1e758dd%7C82c514c1a7174087be06d40d2070ad52%7C0%7C0%7C639214173087963968%7CUnknown%7CTWFpbGZsb3d8eyJFbXB0eU1hcGkiOnRydWUsIlYiOiIwLjAuMDAwMCIsIlAiOiJXaW4zMiIsIkFOIjoiTWFpbCIsIldUIjoyfQ%3D%3D%7C0%7C%7C%7C&sdata=DReFWMb0SyNUF4Vu2fv1ZLDLw0kS7JsQCtYzrQD2CRA%3D&reserved=0> *Title: *A Bayesian Framework for Comparative Cognitive Science (joint work with Jennifer Hu) *Abstract:* Suppose a language model and human subjects both achieve high performance on a test designed to measure a given cognitive ability (e.g., analogical reasoning or theory of mind). Should we conclude that they both have that ability to the same degree? Performance data alone can't settle this question. Cognitive evaluation is an inverse problem: the target ability is a latent variable that is not directly observed, and many hidden causes can produce the same pattern of performance. Memorization, surface cues, and response bias can enable good performance without the target ability, while auxiliary task demands or measurement error can result in observed failure despite the ability. We propose a Bayesian framework to formalise the evaluation of cognitive capacities in humans, animals, and machines. In this framework, a pattern of performance provides evidence only through a comparison. The observed result supports attributing an ability to the extent that it was more expected under a predictive model of the subject with the ability than under a model of the subject without it. This ratio (the Bayes factor) depends on modelling credible routes to success and failure under each hypothesis, and comes apart from prior beliefs about whether subject has the ability. It follows that the same pattern of evidence can carry different evidence for different subjects. This framework explains what makes a cognitive test diagnostic, and how to choose which experiment to perform next as function of the uncertainty it is expected to remove about the subject. In particular, it suggests that the relative evidential weight of behavioural and mechanistic experiments is quite different for human subjects and for artificial neural networks. Beyond the framework's value as a regulative ideal for comparative cognitive science, we review some of its practical implications for experimental design. Further information about the seminar series including details on future talks can be found at the seminar webpage: *https://mqphilosophy.github.io/seminars/* <https://mqphilosophy.github.io/seminars> We look forward to seeing you there. *Dr Emily Hughes *(she/her) ARC Discovery Early Career Research Award (DECRA) Fellow in Philosophy School of Humanities, Faculty of Arts Michael Kirby Building, 17 Wally's Walk Level 2, Room 233 Macquarie University – Wallumattagal Campus, Dharug Country NSW 2109 Australia E: [email protected] W: https://researchers.mq.edu.au/en/persons/emily-hughes *I acknowledge that Macquarie University stands on the land of the Dharug Nation, land that was never ceded. I pay my respects to the Dharug people, the Wallumattagal clan, and their Elders past and present. Always was, always will be, Aboriginal land.* --------- SydPhil mailing list To unsubscribe, change your membership options, find answers to common problems, or visit our online archives, please go to the list information page: https://mailman.sydney.edu.au/mailman/listinfo/sydphil
