How should numeric probabilities be translated into words? Maybe they shouldn't be.
"Words of estimative probability" wreak havoc in high-stakes communication like #intelligenceCommunity assessments and briefings, in part because intelligence and defense institutions map numbers to different words (!) — see Amelia Kahn's forthcoming work at ameliakahn.wordpress.com.
Maths/CogSci/MathPsych lazyweb: Are there any algebras in which you have subtraction but don't have negative values? Pointers appreciated. I am hoping that the abstract maths might shed some light on a problem in cognitive modelling.
The context is that I am interested in formal models of cognitive representations and I want to represent things (e.g. cats), don't believe that we should be able to represent negated things (i.e. I don't think it should be able to represent anti-cats), but it makes sense to subtract representations (e.g. remove the representation of a cat from the representation of a cat and a dog, leaving only the representation of the dog).
We know that the task demands of cognitive tests most scores: if one version of a problem requires more work (e.g., gratuitously verbose or unclear wording, open response rather than multiple choice), people will perform worse.
Most of the Artificial Neural Net simulation research I have seen (say, at venues like NeurIPS) seems to take a very simple conceptual approach to analysis of simulation results - just treat everything as independent observations with fixed effects conditions, when it might be better conceptualised as random effects and repeated measures. Do other people think this? Does anyone have views on whether it would be worthwhile doing more complex analyses and whether the typical publication venues would accept those more complex analyses? Are there any guides to appropriate analyses for simulation results, e.g what to do with the results coming from multi-fold cross-validation (I presume the results are not independent across folds because they share cases).
An easy way to improve scoring of memory span tasks: The edit distance, beyond "correct recall in the correct serial position"
Gonthier in Behav. Res. Methods 2023
"in addition to being more logically consistent, edit-distance scoring demonstrates similar or better psychometric properties than partial-credit, with comparable validity, a small increase in reliability, and a substantial increase of test information"
What makes someone a cognitive scientist? Is it a degree in cognitive science? Or in one of its constitutive disciplines along with a research focus on the mind? Or publishing in cognitive science journals? Or something else? 🤔
Are #philosophy students’ intuitions about thought experiments different because of expertise?
Longitudinal studies of philosophy and #CogSci students (N = 226) didn't seem to reveal as much: there were some group differences in intuitions, but a selection/indoctrination effect seemed more likely than “a general expertise” or “expertise specific to particular subfields”.
On #Monday Louie Favela and Edouard Machery summarize the target article: "Investigating the concept of representation in the neural and psychological sciences."
On #Tuesday and #Thursday, Ben Baker (Colby College) and Inês Hipólito (Macquarie) will comment.
On #Wednesday and #Friday, Louie and Edouard will respond to the comments.
“In the early days of modern consciousness science, back in the 1990s, researchers focused on identifying empirical correlations between aspects of conscious experience and properties of brain activity. […] In recent years, however, there has been a blossoming of neurobiological theories of consciousness.”
It's relatively commonly recognised that AI is a somewhat misleading umbrella term that covers a variety of different scientific and non-scientific projects.
In a new preprint, I articulate, defend, and illustrate a central scientific project for AI that is somewhat neglected or vaguely recognised, which I call AI-as-exploration (taking the cue from a recent paper by @olivia, @Iris et al).
The Priesemann Lab ( @ViolaPriesemann) is looking for PhD candidates (12 free positions) and PostDocs (2) in a very interesting project investigating the neural basis and cognitive properties of #curiosity. Start: summer 2024 in #Göttingen
Very excited to share a substantially updated version of our preprint “Language models show human-like content effects on reasoning tasks!” TL;DR: LMs and humans show strikingly similar patterns in how the content of a logic problem affects their answers. Thread: 1/10 #LanguageModels#lms#AI#cogsci#machinelearning#nlp#nlproc#cognitivescience
Department of #Brain and #CogSci faculty members Ev Fedorenko, Ted Gibson, and Roger Levy believe they can answer a fundamental question: What is the purpose of #language? | MIT News
(FYI, there are these cool new things called hyperlinks, great for reporting on debates, sharing multiple perspectives, supporting one's claims, giving due credit, and saving reader time.)
Running tutorials for undergrads on jsPsych this semester. Just made a course blog with screencasts that will be updated weekly this semester. Sharing in case it's useful for others.
I'm looking for review papers on the general topic of memory for pictures. I've found some pre 1990s, but haven't found review papers after that...(except Madigan, 2014). Any picture #cognition folks know of some? #cogsci#psychsci#psych#cogpsy
I'm fairly confident that I won't be writing on panpsychism again any time soon... My interests switched to reevaluating physicalism again, especially in connection with cognitive science and empirically-informed approaches to consciousness in a broader sense. I don't have a strong opinion on which position is 'true' - and maybe that's bad for a philosopher - I just go by what I find worthy of further investigation 🤷🏻♂️