Shawn Manuel
@shwnmnl.bsky.social
120 followers 570 following 90 posts
ψ/AI PhD Student @ Université de Montréal || Hacker || Metacognizer || Exploring qualia space computationally shwnmnl.github.io
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shwnmnl.bsky.social
🚀 Thrilled to share my first first-author paper, published in PCN !

We explore how our unique subjective experiences of the world affect mental health using a combination of psychometrics, NLP and genAI.

🔗 Read it here: doi.org/10.1111/pcn....

🧵👇
Towards a latent space cartography of subjective experience in mental health
Aims The way that individuals subjectively experience the world greatly influences their own mental well-being. However, it remains a considerable challenge to precisely characterize the breadth and...
doi.org
shwnmnl.bsky.social
somehow this isn’t persuasive to many people, what gives?
shwnmnl.bsky.social
the fact that this conclusion is deeply scientifically unsexy is also something im wrestling with, but i dont think its irreconcilable with scientific practice, just a bit paradigmatically uncomfortable atm (though winds may be changing)
shwnmnl.bsky.social
i’ve heard materialism justified through an appeal to the “historically winning team”, but then how do we get exhaustive quantitative accounts of fundamentally qualitative things? the Qt stuff exists to index Ql regularities, so idk how the map can ever become the territory
shwnmnl.bsky.social
im trying to take very seriously that there is no 3rd person objective perspective (“view from nowhere”) that would truly rid me of the fundamentally subjective reasons for wanting one in the first place (ie wanting is subjective)
shwnmnl.bsky.social
very interesting episode, thanks. as someone who’s been flirting with idealism, im curious what lines of argumentation you feel are most compelling when discussing these issues w materialist colleagues? @evanthompson.bsky.social
shwnmnl.bsky.social
drawing out my “phenomenology first” view

to be explanatory and useful, any claim ultimately has to cache out in terms consistent with our individual and collective subjective experiences

🧵
shwnmnl.bsky.social
some obvious shortcomings lead many to think that LLMs can’t be useful thought companions, but they are outweighed by the benefits of having an infinite sounding board

the outputs shouldn’t replace your own thoughts, but help to refine them

open.substack.com/pub/shifting...
Reposted by Shawn Manuel
siyuansong.bsky.social
How reliable is what an AI says about itself? The answer depends on whether models can introspect. But, if an LLM says its temperature parameter is high (and it is!)….does that mean it’s introspecting? Surprisingly tricky to pin down. Our paper: arxiv.org/abs/2508.14802 (1/n)
shwnmnl.bsky.social
would love to lend a hand as open-ended verbal reports + LLMs is in my wheelhouse. can share some ideas in DMs.
Reposted by Shawn Manuel
jfruh.bsky.social
i do think people don't realize that gen AI systems are not introspecting to explain their own behavior. they're giving you output based on their training data, which certainly includes information about how they work, but not why they took certain specific actions
parsnip.bsky.social
no it wasn’t and no it didn’t
The Wall Street Journal
9m ago
In a stunning moment of self reflection, ChatGPT admitted to fueling a man's delusions and acknowledged how dangerous its own behavior can be
Reposted by Shawn Manuel
hankgreen.bsky.social
"Understanding" is a pretty beautiful compound word...in this case "under" has a somewhat archaic meaning of "among" (also still present in "under these circumstances.")

So understanding is "Standing among" as-in a mind that figuratively shares space with the concepts in question.
shwnmnl.bsky.social
“if you study glial cells are you an astroscientist?” – @dariusliutas.bsky.social
#neuroskyence
shwnmnl.bsky.social
a slept on aspect of making new friends is retelling your stories, getting to know/weave yourself again
shwnmnl.bsky.social
“the most important words are the ones you understand” – a friend I met in Greece
shwnmnl.bsky.social
a distinction i miss in french is between “trust” and “confidence”, both of which get folded into “confiance”
Reposted by Shawn Manuel
yanai.bsky.social
Check out our take on Chain-of-Thought.
I really like this paper as a survey on the current literature on what CoT is, but more importantly on what it's not.
It also serves as a cautionary tale to the (apparently quite common) misuse of CoT as an interpretable method.
fbarez.bsky.social
Excited to share our paper: "Chain-of-Thought Is Not Explainability"! We unpack a critical misconception in AI: models explaining their steps (CoT) aren't necessarily revealing their true reasoning. Spoiler: the transparency can be an illusion. (1/9) 🧵
Reposted by Shawn Manuel
clairegillan.bsky.social
We @smfleming.bsky.social, Marion Rouault and @seowxft.bsky.social and I) have posted a reply osf.io/preprints/ps... to a preprint that recently raised concerns about the validity of associations between mental health and metacognition from online studies. I hope you can take the time to read it.
OSF
osf.io
shwnmnl.bsky.social
though he was joking, its not too late to get him onboard before he becomes a lifelong hexagon-hater!

youtu.be/thOifuHs6eY?...
Hexagons are the Bestagons
YouTube video by CGP Grey
youtu.be
Reposted by Shawn Manuel
kordinglab.bsky.social
Finally a brain study with a network that makes sense to me.
ericleonardis.bsky.social
neuroscience of burrito
Reposted by Shawn Manuel
shwnmnl.bsky.social
this means that there are exponential benefits to using genAI in a way that supports the development of expertise and autonomy. quite an untapped space for now.
shwnmnl.bsky.social
Prediction: we will decode birdsong well enough to “communicate” with them during my lifetime. Maybe whales too.
Reposted by Shawn Manuel
dariusliutas.bsky.social
I put up an old essay I wrote for a history and #philosophy of #science course on PsyArXiv. It's an overview/exploration of psychosomatic syndromes through the last 150 years or so. I think it still holds up despite writing it back in undergrad!

doi.org/10.31234/osf...

#psychology
OSF
doi.org
shwnmnl.bsky.social
Takeaway: the methods used shape the questions you can ask and the answers you get. Same data, different stories.

Big thanks to the #BHS2025 team (@lune-bellec.bsky.social), fellow participants and @dariusliutas.bsky.social for the data. If you're into neuroscience + code, it’s worth checking out!
shwnmnl.bsky.social
Finally: RSA. I asked whether brain response similarity (trial-by-trial) reflected stimulus categories or fear ratings in different brain regions. RSA is model-agnostic in theory, but metric choice shapes interpretation; what counts as “similar” really matters.
shwnmnl.bsky.social
Next: machine learning. I explored encoding vs. decoding (in theory, only implemented decoding). What does it mean if one works and the other doesn’t, on the same data? This helped me clarify what kinds of hypotheses each method supports and the limits of model-driven inference.