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Oct 6, 2022 7 tweets 10 min read Read on X
"Knowledge Representation in Judgment and Decision Making"

Today's SFI Seminar by @sdpbht (@Penn)

Follow this 🧵 for highlights!

Streaming now:


#knowledge #cognition #behavior Image
@sdpbht @Penn How do people evaluate potential decisions — the tradeoffs, the risks?

"How do people make assessments, and how can we *improve* those assessments?"
- @sdpbht

AND: What role does #memory (episodic and semantic) play in all of this?

#psychology #taxonomy ImageImage
Categorical thinking empowers inductive #reasoning.

(Here: How does what people know about #dolphins inform the likelihoods they assign to other agents, such as #ET?)



#Cognitive #Psychology Image
"Psychologists typically build models of cognitive PROCESSES. They oftentimes test these in artificial, highly abstracted laboratory tests, using highly stylized stimuli. But in the real world, when we're choosing or reasoning, we need to apply processes TO CONTENT."
- @sdpbht Image
"This was effectively the foundation of cognitive psychology. The first paragraph from #HerbertSimon's 1979 paper uses 'process' or 'mechanism' five times. It doesn't use 'knowledge representation' AT ALL."
- @sdpbht (@Penn)

Image
"Of course, if you need a *complete* theory of human #cognition, you also need to specify how [#knowledge] representations are *acquired*..."
- @sdpbht (@Penn)



#judgment #memory #reasoning Image
@sdpbht @Penn "How do we start predicting human judgments of the 100Ks of kinds of food out there in the world? First we need to understand how knowledge is represented."

With word vector models.

Landauer & Dumais 1997:
psycnet.apa.org/record/1997-03…

Turney & Pantel, 2010:
arxiv.org/abs/1003.1141?… Image

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More from @sfiscience

Mar 10, 2023
🧵 "The Smell of Inhibition. A Code in the Nose?"

ICYMI, this week's SFI Seminar by Fractal Faculty Stuart Firestein (@Columbia) on "what started out ass a very simple-seeming problem [re: #olfaction] and turned out to be very complicated":

"Everything we know about the world comes through these little holes in our head and the skin covering our body, processed through tissue specialized to interpret it."

"The thing to notice about [sight and hearing] is that they're [processing] fairly low-dimensional stimuli."
"Even a simple smell is composed of a VARIETY of molecules, and these are high-dimensional from a chemical point of view. And it's also a somewhat discontinuous stimulus. How do we get from this bunch of molecules to this unitary perception of something like a rose?"
Read 8 tweets
Mar 10, 2023
🧵 "#Possibility Architectures: Exploring Human #Communication with Generative #AI"

Today's SFI Seminar with ExFac Simon DeDeo @LaboratoryMinds (@CarnegieMellon), streaming now:
"A key feature of this is talk is that we make sense of what each other are saying IN PART by what they say, but ALSO by what we expect of them."
"Language transmits info against a background of expectations – syntactic, semantic, and this larger cultural spectrum. It's not just the choices of make but [how] we set ourselves up to make later choices."

@LaboratoryMinds re: work led by @clairebergey:
Read 15 tweets
Mar 9, 2023
"I think what really drives [the popularity of the #multiverse in #scifi] is regret... There's a line in @allatoncemovie where #MichelleYeoh is told she's the worst version of herself."

"I don't think we should resist melting brains. I think we should just bite the bullet."
"When you measure the spin of an electron, or the position...what happened to all of the other things you could have seen? Everett's idea is that they're all real. They all become real in that measurement."
- SFI Fractal Faculty @seanmcarroll at @guardian
theguardian.com/science/audio/…
"At the level of the equations there is zero ambiguity, but the metaphors break down. The two universes it splits into aren't as big as the original universe. The thickness of the two new universes adds up to the thickness of the original universe."
Read 4 tweets
Dec 14, 2022
"Compositionality in Vector Space Models of Meaning"

Today's SFI Seminar by @marthaflinders, streaming:


Follow this 🧵 for highlights!
"Scientists gather here
Santa Fe Institute, oh so near
Inquiring minds seek truth"

#haiku about SFI c/o @marthaflinders & #ChatGPT

...but still, #AI fails at simple tasks:
"One way to represent the kind of #compositionality we want to do is with this kind of breakdown...eventually a kind of representation of a sentence. On the other hand, vector space models of #meaning or set-theoretical models put into a space have been very successful..."
Read 14 tweets
Dec 13, 2022
"Humans are prone to giving machines ambiguous or mistaken instructions, and we want them to do what we mean, not what we say. To solve this problem we must find ways to align AI with human preferences, goals & values."
- @MelMitchell1 at @QuantaMagazine:
quantamagazine.org/what-does-it-m…
“All that is needed to assure catastrophe is a highly competent machine combined with humans who have an imperfect ability to specify human preferences completely and correctly.”

- Stuart Russell (@UCBerkeley) as quoted by @MelMitchell1 in her latest @QuantaMagazine article
"It’s a familiar trope in #ScienceFiction — humanity threatened by out-of-control machines who have misinterpreted human desires. Now a not-insubstantial segment of the #AI research community is concerned about this kind of scenario playing out in real life."
- @MelMitchell1
Read 6 tweets
Dec 12, 2022
"Training Machines to Learn the Way Humans Do: an Alternative to #Backpropagation"

Today's SFI Seminar by Sanjukta Krishnagopal
(@UCBerkeley & @UCLA)

Starting now — follow this 🧵 for highlights:
Image
"When we learn something new, we look for relationships with things we know already."

"I don't just forget Calculus because I learned something else."

"We automatically know what a 'cat-dog' would look like, if it were to exist."

"We learn by training on very few examples." Image
1, 2) "[#MachineLearning] is fundamentally different from the way humans learn things."

3) Re: #FeedForward #NeuralNetworks

"You choose some loss function...maybe I'm learning the wrong weights. So I define some goal and then I want to learn these weights, these thetas." ImageImageImage
Read 13 tweets

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