For my seminar (Master's program CogNeuro), I am looking for papers/articles that argue in favor of or against AI (gladly with focus on machine learning) as a means of understanding mind/brain. General design of seminar is intended to be a pro and cons discussion format.
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Definitely modeling! Both papers that you suggested are already very helpful. I suspect the Palmeri paper to be great to get into the topic, which can be challenging for psych students, who haven't thought much about mind/brain in computational/mathmatical language
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I second what
@o_guest wrote: AI as a means to understand mind/brain would be part of the#cogsci endeavor, which has a long tradition. A focus on ML would IMO be an unnecessarily narrow focus. See also these considerations (embedded thread):https://twitter.com/AnneEUrai/status/1038152066483535874 … -
In addition, AI != machine learning. Other fields of AI (e.g. robotics, reasoning under uncertainty) offer a meaningful contribution to cognitive/systems neuroscience 1/2
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Didn't intend to claim it is equal; robotics would be very interesting (any literature recs?)! I guess because I am still researching possibilites for the seminar, I used umbrella terms and phrasing that actually needed to be used with more caution
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There is the field of developmental robotics which sometimes extends to CNS. There is low-level sensorimotor stuff. And we (
@DI_PPGroup) use robots as a tool for exploration of gaps, ambiguities and inconsistencies in theories such as Predictive Processing http://www.socsci.ru.nl/johank/RoboHavioral.pdf … -
Mind that the latter work is still in its infacy. There are currently several MSc projects initiated in the group that look promising but have not yet led to publishable results.
End of conversation
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very few people have the interdisciplinary training to bridge between existing philosophy (of mind, epistemology) and the practice of science. Most fruitful to delineate what philosophical considerations impact experiments, and what current philo thinking is