This sentence also puzzled me:
> Lots of people agree that psychology is stuck because it doesn’t have a paradigm
Psychology might not have a grand unifying paradigm, but it's been highly paradigm-driven since its inception.
Another example for all you computer folks out there: ultimately, all software
engineering is just moving electrons around. But imagine how hard your job would
be if you could only talk about electrons moving around. No arrays, stacks,
nodes, graphs, algorithms—just those lil negatively charged bois and their
comings and goings.
While this is true, we're usually targeting a platform, either x86 or arm64, that are incredibly complex pieces of engineering. Unless you are in the IoT or your application requires you to optimize at the hardware level, we're so distant from the hardware when we're programming in python for instance that the level of awareness required about the hardware isn't that much more complicated than the basic Turing machine.
I can rely on a TCP socket guaranteeing delivery, but I am not very well versed in the algorithms that guarantee that, and I would be completely out of my depth if I had to explain the inner workings of the silicon underneath.
Most programmers never think once about electrons. They know how things work at a much higher level than that.
so it is indirectly based on knowledge of how color works, it's simply not physics as we understand it but it's "physics" as the biology of the eye "understands" it.
red is an abstraction whose connection to how colors work is itself another abstraction, but of a much deeper complexity than 'red' which is a rather direct abstraction as far as abstraction can go nowadays
Understanding the underlying concepts is irrelevant.
In physics, color has been redefined as a surface reflectance property with an experiential artefact as a mental correlate. But this understanding is the result of the assumptions made by Cartesian dualism. That is, Cartesian dualism doesn't prove that color as we commonly understand it doesn't exist in the world, only in the mind. No, it defines it to be the case. Res extensa is defined as colorless; the res cogitans then functions like a rug under which we can sweep the inexplicable phenomenon of color as we commonly understand it. We have a res cogitans of the gaps!
Of course, materialists deny the existence of spooky res cogitans, admitting the existence of only res extensa. This puts them in a rather embarrassing situation, more awkward that the Cartesian dualist, because now they cannot explain how the color they've defined as an artefact of consciousness can exist in a universe of pure res extensa. It's not supposed to be there! This is an example of the problem of qualia.
So you are faced with either revising your view of matter to allow for it to possess properties like color as we commonly understand them, or insanity. The eliminativists have chosen the latter.
Only once you're at the eye level does anyone start talking about "color". And yes, they define it by going back to physics and deciding on some representative spectra for "primary" colors (c.f. CIE 1931).
Point being: everything is an abstraction. Everything builds on everything else. There are no simple ideas at the top of the stack.
This is unnecessarily pedantic. Your explanation demonstrates that.
> There are no simple ideas at the top of the stack.
I don't know what a "simple idea" is here, or what an abstraction is in this context. The latter has a technical meaning in computer science which is related to formalism, but in the context of physical phenomena, I don't know. It smells of reductionism, which is incoherent [0].
models ≠ knowledge, and a high degree of certainty is not certainty. This is tiring.
This really does matter a lot more when floating signifiers get involved; I'm not actually contesting that our models of electrical engineering model reality quite well.
Haven't you heard about vibe coding?
That is literally how we approach transformers.
Obviously, being able to use a computer is useful, just as using a telescope is useful or being able to use a pencil is useful, but it's not what CS or software engineering are about. Software is not a phenomenon of the physical device. The device merely simulates the software.
This "centering" of the computing device is a disease that plagues many people.
It's not just a comparator, it’s how long I’ve been off (I), how fast I’m drifting (D), and how far I am right now (P).
In this framework, emotional regulation looks like control theory. Anxiety isn't just a feeling—it's high D-gain ie: a system overreacting to projected errors.
Depression? Low P (blunted response), high I (burden of unresolved past errors), and broken D (no expected future improvement).
Mania? Cranked P and D, and I disabled.
In addition to personality being setpoints, our perceptions of the past, present, and future might just be PID parameters. What we call "disorders" are oscillations, deadzones, or gain mismatch. But like the article pointed out, it's not really a scientific theory unless it's falsifiable.
Skimming through its chapter on AI, made me think of Dave from EEVblog fame. In some of his videos he wears a T-shirt saying "always give negative feedback!". Which is correct - for those who understand electronics (specifically: opamps).
In short: design circuit such that when output is above target, circuit works to lower it (voltage, in this context). When below, circuit works to raise it. Output stability requires a feedback loop constructed to that effect.
There's analogies in many fields of technology (logistics, data buffering, manufacturing, etc etc, and yes, thermostats).
I'll leave it there, other sites like Wikipedia (or EEVblog!) better explain opamp-related design principles.
From what I've read, current AI systems appear like opamp circuitry with no (or poor) feedback loop: a minor swing in input causes output to go crazy. Or even positive feedback: same thing, but self-reinforcing. Guardrails are not the fix: they just clip the output to ehm.. 'politically correct' or whatever. Proper fix = better designed feedback loops. So yes, authors of this book may definitely be onto something.
Want an oscillator? Design an amplifier. Want an amplifier? Design an oscillator.
The sensations we tie to urination or breathing have quick cycle times making it easy to test the causal loop. Thus confounding factors such as a UTI causing a bladder full sensation, or nitrogen asphyxiation without feeling suffocation are things we understand well.
The "Make Sure You Spend Time with Other People System" is a good example for a blog post but it’s already a fair bit looser. But when you consider they want to investigate things without preexisting understanding as well as we understand loneliness it smells like sneaking back towards tautologically defined systems like "zest for life."
It's still just fluff though. So the author thinks the mind is a control system... Sure, that's a model.
Does it explain observations better? What predictions does this model let us make that differ from other models?
The article was needlessly wordy that I might have missed if this was hiding somewhere
If the concept of multiplicity (we humans being a system of smaller systems) resonates with you, consider reading No Bad Parts by Richard C. Schwartz. I've personally found it immensely helpful.
> Those divisions are given by the dean, not by nature.
"Is Human Behavior Just Running and Tumbling?": https://osf.io/preprints/psyarxiv/wzvn9_v1 (This used to be a blog post, but its down, so here's a essentially identical preprint.) A scale-invariant control-loop such as chemotaxis may still be the root algorithm we use, just adjusted for a dopamine gradient mediated by the prefrontal cortex.
"Give-up-itis: Neuropathology of extremis": https://www.sciencedirect.com/science/article/abs/pii/S03069... What happens when that dopamine gradient shuts down?
needing-to-breathe-ness is (probably) a gimme, but what are the units that will explain which route i take on my walk today? and how do you avoid defining units that aren't impressionistic once you need to rely on language and testimony to understand your research subject's mental state?
my understanding of psychological constructs is that they're earnest attempts to try and resolve this problem, even if they've led us to the tautological confusion we're in now.
Well, this is definitely happening for some parts of medicine, like IBS or many forms of chronic pain.
> If you feel like you’re drowning, your Oxygen Governor is like “I GIVE THIS A -1000!”. When you can breathe again, though, maybe you only get the -1000 to go away, and you don’t get any happiness on top of that. You feel much better than you did before, but you don’t feel good.
Anecdote but: you absolutely feel good. At least, I did.
"The Emotion Machine", by Marvin Minksy (the AI view)
&
"The Art of Empathy", by Karla McLaren (the Internal / Emotional View)
It's also important to note that other control systems in the body that affect control systems in the mind, eg. endocrine.
almosthere•8h ago
bbor•8h ago
d3ckard•7h ago
yeahsure•7h ago
I also lost a dear friend to suicide and he was very succesful and active on his field when it happened. Nobody saw it coming.
It's just not that simple.
kayodelycaon•6h ago
As I see it, you can either deal with a problem on your own terms or you can let it eventually deal with you on its terms.
yeahsure•7h ago
Trasmatta•7h ago
perching_aix•7h ago