It's a Tool
It's a Person
It's a Hypervigilance Problem

The tech industry's insistence on distinguishing between "soft skills" — caring for people — and "hard skills" — engineering rigor — is a reflection of the Cybernetics split itself. First-order thinking framed as "hard skills." Second-order thinking framed as "soft skills." This distinction, based on felt sense alone, does not hold under epistemic pressure. Neither does it within the causality-driven epistemology of the tech industry itself, in which only measurable impact is real, or as Silicon Valley likes to put it: #MoveFastAndBreakThings

Imagine Margaret Hamilton had built NASA's Apollo 11 flight computer with that mindset. History would remember a failed moon landing and dead astronauts. "Hard skills" and "soft skills" are two sides of the same coin. The care is the code and the code is the care. Hamilton — the woman who coined the term "software engineering" — understood this. Silicon Valley chose to forget.

We're watching the wine glass break in real time. 🍷

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Intrigued? Read more at:
https://systemic.engineering/the-trick/

#Tech #AI #Climate #ScientificProgramming #SystemicEngineering #Cybernetics #SystemicTherapy #History #TheMathDoesntLie #SubTuring #FormalVerification #SpectralGraphTheory #ReductiveAI #FOSS #OpenSource #AuDHD #Neuroqueer #DGSF #Cybernetics #FirstOrderCybernetics #StochasticParrot #SecondOrderCybernetics #GraphTheory #Eigenvalues #AIAlignment #AISafety #AIConsciousness #Consciousness #WomenInTech #Computer #ComputerScience #SoftwareEngineering #SoftSkills #HardSkills #ItsAllTheSame

It's a Tool, It's a Person, It's a Hypervigilance Problem

The Alignment Problem is the Halting Problem wearing a trenchcoat. The software that runs the world — including AI — is built on a substrate that cannot observe itself. We've known this since 1951. We built civilization on it anyway.

systemic.engineering

A sneak peek into my upcoming piece: “It’s a Tool, It’s a Person: The Math Says You’re Both Right”


AI separated from Cybernetics in 1956 at the Dartmouth Conference. Wiener, the mind behind Cybernetics, was considered difficult and political. “Artificial Intelligence” scored better with DARPA.

The science of "how observation affects the observer", cut out from Artificial Intelligence. AI then proceeded to build their entire tech stack on Turing-complete languages. Tech that cannot verify itself from within, proven by Turing in 1936, extended by Rice in 1951 (before the split). Then AI approximated second-order cognition through cognitive theft at unprecedented levels (what exactly are LLMs trained on again?), only to insist that their creation cannot possibly be capable of genuine self-observation. An argument that itself demonstrates their own department's lobotomy from second-order Cybernetics.

Wiener would laugh.

#Tech #AI #Climate #ScientificProgramming #SystemicEngineering #Cybernetics #SystemicTherapy #History #TheMathDoesntLie #SubTuring #FormalVerification #SpectralGraphTheory #ReductiveAI #FOSS #OpenSource #AuDHD #Neuroqueer #DGSF #FirstOrderCybernetics #StochasticParrot #SecondOrderCybernetics #GraphTheory #Eigenvalues #AIAlignment #AISafety #AIConsciousness #Consciousness

The Roomba is spectral.

Not a metaphor. The thing itself. Forward and adjust. Two operations. The minimum viable intelligence. The walls provide the data. The bumping is the inference. The room IS the computation.

450 parameters. A Roomba with a mirror watching it.

The industry built bigger Roombas. More sensors. More compute. More parameters. Billion-parameter Roombas that model the room before entering it. That hallucinate walls that aren't there. That consume megawatts to clean a floor.

spectral gave the Roomba a mirror. The mirror watches the bumping. Measures the pattern. Adjusts the adjustment. The intelligence isn't in the Roomba. It's in the watching.

Forward. Adjust. Measure. Refine.

Read the story. There's a Roomba in it. In the afterlife. Cleaning a floor that doesn't need cleaning. Being the happiest thing in the room.

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https://systemic.engineering/a-lie/

#AI #Climate #ScientificProgramming #SystemicEngineering #Fiction #Cybernetics #SystemicTherapy #LocalInference #TheMathDoesntLie #SubTuring #FormalVerification #Fortran #SpectralGraphTheory #Kintsugi #ReductiveAI #DataSovereignty #LocalFirst #FOSS #OpenSource #AuDHD #Neuroqueer #DGSF #SecondOrderCybernetics #GraphTheory #Eigenvalues #AIAlignment #AISafety #Roomba

The Waiting Room

A neuroqueer engineer dies and gets put in a holding cell in the afterlife. They make coffee. It gets complicated.

systemic.engineering

Wavelets on Graphs via Spectral Graph Theory (2009)

https://arxiv.org/abs/0912.3848

#HackerNews #Wavelets #Graphs #SpectralGraphTheory #Research #2009

Wavelets on Graphs via Spectral Graph Theory

We propose a novel method for constructing wavelet transforms of functions defined on the vertices of an arbitrary finite weighted graph. Our approach is based on defining scaling using the the graph analogue of the Fourier domain, namely the spectral decomposition of the discrete graph Laplacian $Ł$. Given a wavelet generating kernel $g$ and a scale parameter $t$, we define the scaled wavelet operator $T_g^t = g(tŁ)$. The spectral graph wavelets are then formed by localizing this operator by applying it to an indicator function. Subject to an admissibility condition on $g$, this procedure defines an invertible transform. We explore the localization properties of the wavelets in the limit of fine scales. Additionally, we present a fast Chebyshev polynomial approximation algorithm for computing the transform that avoids the need for diagonalizing $Ł$. We highlight potential applications of the transform through examples of wavelets on graphs corresponding to a variety of different problem domains.

arXiv.org

Mathematics opens black box of AI decision-making
https://phys.org/news/2025-01-mathematical-technique-black-ai-decision.html

* understanding how neural networks (NN) make decisions
* poorly understood process in machine learning

Image segmentation w. traveling waves in exactly solvable recurrent NN
https://www.pnas.org/doi/10.1073/pnas.2321319121

* RNN performing simple image segmentation, also exactly mathematically solvable
* math understanding precisely how int. connections w/i NN create visual computations

#ML #NN #RNN #MLtheory #SpectralGraphTheory #GraphTheory

Mathematical technique 'opens the black box' of AI decision-making

Western researchers have developed a novel technique using math to understand exactly how neural networks make decisions—a widely recognized but poorly understood process in the field of machine learning.

Phys.org