Showing posts with label AI. Show all posts
Showing posts with label AI. Show all posts

Tuesday, June 9, 2026

Hegemonic Power, Synthetic Humans, and the SAG-AFTRA-AI Manifesto


It might be considered the first real big fight between humans and robots. To summarize into a very, very simple, and incomplete explanation, it happens at a time when the labor union of people who work on movies have to re-negotiate their contract with the people who pay them. They went on strike for 118 days, the longest actors’ strike in Hollywood history. Now they have a new contract.

The problem was that if there's one thing artificial intelligence can do, it's art (as opposed to law, medicine, engineering, etc.). Not saying it's necessarily good at art, but it's sure as hell good enough for the people who pay for movies to be made, and who then go on to make money off those movies. Not sure if it's good enough for the people who pay to watch these movies, but then again, it doesn't seem like anyone needs to care about consumers anymore anyway, so...the people who work on movies are in for a fight if they want to be treated like humans. 

The problem, for the rest of us, is that we're humans too. Well, not if you're reading this, because the only people who read this weblog are in fact robots. But the rest of us are humans. And for the first time since Africa, we are facing real competition.

Below is a report about the 2023 SAG-AFTRA labor story, and some good bits about how humans and robots are being positioned against each other in the labor market, and what that might mean for us in the future. It's written by Data and Society Institute (citation at the very bottom, and in-text references you'll just have to get for yourself from the document; because sorry sir this is a Wendy's). 

*SAG-AFTRA - Screen Actors Guild – American Federation of Television and Radio Artists
*Image credit: Gundam style mechabot made in japan - japantimes www.japantimes.co.jp


On Common Sense, Machine Learning and Big Data
Common sense, or a skewed perception of reality that perpetuates the status quo as normal, natural and unquestionable, is an expression of hegemonic power. The concept of common sense describes commonly held — yet nonetheless fragmented and heterogenous - knowledge that often goes unquestioned as fact (Gramsci,1926/1971). 
 
According to critical theorist Hito Steyerl's (2023) power analysis of machine learning technologies, the power of the owning class depends on its seizure of data. Thus, the discussion of for-profit technology, and speci!cally various applications that track, record, and classify user data, can never be liberatory, despite the claims of the companies, industries, and institutions promising safety, accessibility, efficiency, and sustainability (Bender and Hanna, 2025; Benjamin, 2019).

The “common sense” of AI, that is, the widely-held belief that AI is a foregone conclusion, functions as an articulation of hegemonic power. In this frame, we seek to understand how the labor movement can meaningfully intervene.

AI is not simply a discursive formation that stands as a “common sense” foregone conclusion, it also obfuscates large-scale, transnational coordination of resources, labor, and people who make up the infrastructures that are required for arti!cial intelligence. This matters because it broadens the base for possible coalition building to be mobilized in these “processes of subtraction” (Steyerl, 2023, p. 12).

Data and Society, 2026


See Figure 1 - The four strategies on the left negotiate with the common sense of AI, giving it power and weight, as these strategies work with AI as it is, instead of disengaging with the common sense of AI, and pushing these technologies to work that are commons-based or people-centered.

Robots in Human Clothing, ie The Corporate Flesh Engine
Amazon has long referred to their Mechanical Turk platform as artificial intelligence, but there have always been humans doing the often-underpaid work of classifying and sorting content of all types, increasingly in the Global South (Crawford, 2021; Gonzalez-Cabello et al., 2025). This hidden labor has been referred to as “ghost work” (Gray and Suri, 2019; Muldoon et al., 2024) and “human-fueled automation” (Irani, 2019), drawing attention to the people who power AI systems. 

Synthetic Performers (i.e., entirely digitally-produced performers created through generative AI). The [new negotiated contract] establishes guidelines around the creation and use of “digital replicas” and “synthetic performers.”

Digital replicas are digital reproductions of an actor's voice or likeness. The contract described two types of digital replicas: “employment-based digital replicas” and “independently created digital replicas.”

Employment-based digital replicas are those that are created during the actors’ physical participation in work through methods such as scanning, which can then be used to depict the actor in scenes they did not actually perform.

Independently created digital replicas are made without the actor's physical participation and can perform in scenes that they did not perform. The parameters of consent and compensation vary depending on the type of technology utilized. The guidelines for synthetic performers created through generative AI are less robust than those for digital replicas. Synthetic performers are entirely digitally-produced performers created through generative AI that do not resemble a recognizable actor and are not voiced by a person. The contract requires that studios who want to use a synthetic performer must notify and provide the union with opportunities to bargain over the usage of a synthetic performer in lieu of hiring a human performer. A document drafted by the union with frequently asked questions on AI notes that “for wholly synthetic assets, [studios] cannot use them without notifying the union and bargaining. Had we not done that, there was nothing stopping them from using these synthetic assets without anyone's consent.”

The contract also notes that if studios create a synthetic performer through prompting a generative AI system using a performer's name and their “principal facial feature” — the mouth, nose, eyes, or ears — that is recognizable, studios must bargain with the performer and obtain their consent.

However, for synthetic performers and independently created digital replicas, there are exceptions for consent with regards to uses protected by the First Amendment. A summary of the tentative agreement lists these exceptions as “comment, criticism, scholarship, satire or parody, use in a docudrama, or historical or biographical work.” In the aforementioned types of projects, studios do not need to obtain consent from performers to use their digital doubles.

--Source: Big Data & Society. Dis/engaging the ‘common sense’ of AI: Labor strategies 
from the 2023 SAG-AFTRA around data-driven technologies. Mar 2 2026. Emma May, Britt Paris and Serita Sargent, Rutgers School of Communication & Information.

Wednesday, June 3, 2026

Temu Promethius



I rarely if ever use the illustrations in the thumbnail for the article. But first of all, the use of generative ai for illustrating science discoveries and inventions has been a big game changer. Second of all this idea needs an image, and this image seems to be perfectly explaining what's going on. It's a neuromorphic substrate for a neuromorphic computer that grows all by itself, in other words, "Artist's rendering of a biocomputing device that combines biological neurons with advanced electronics into a network that can be programmed to recognize patterns" --Kate Zvorykina w Ella Maru Studio, Inc for Princeton, 2026

Source:
New 3D device harnesses living brain cells for computing
Apr 2026, phys.org 

But here's the real reason for this post. 

AI Art - Shitty image generated by the editorial team using AI for illustrative purposes - 2026

Watching this seismic shift in visualization is a crazy experience - these kinds of images, the thumbnail here, are exactly the kind of thing I pushed my art students to go past - it's always a person or a person's head, and cramming other more abstract objects etc into it or near it. It's the most basic form of symbolic imagery creation, and it's fucking boring guys. It doesn't matter if it's done with good technical accuracy, it's still boring. Will we all learn to grow past this tendency together or will there be a divide between people who can think more outside the box vs everyone else (sounds like the role the artist has had forever, no different just because ai is so "revolutionary").

Note that my google email inbox services ask me if I want to use their artificial intelligence email summary feature to summarize this email, but only this email, the one containing this article that I sent to myself, despite my having hundreds of similar ones in the same inbox. But I digress; because I don't care about the article, just the picture.

Source:
Can AI ascertain our personality traits from our ChatGPT history?
May 2026, phys.org


Sunday, May 31, 2026

Deep Pope and Other Images of Distinction


Only here to document the fact that this is the most famous deepfake image from our current era of the AI craze. The Pope in a puffy jacket. That is all. 
--Source: Sensor chips help identify deepfakes by adding cryptographic signatures to camera data, Mar 2026 https://techxplore.com/news/2026-03-sensor-chips-deepfakes-adding-cryptographic.html

And now for something completely different

"Playmate of the Month". Playboy Magazine. November 1972, photographed by Dwight Hooker.

Lenna (or Lena) is a standard test image used in the field of digital image processing, starting in 1973. It is a picture of the Swedish model Lena Forsén, shot by photographer Dwight Hooker and cropped from the centerfold of the November 1972 issue of Playboy magazine. The scan became one of the most used images in computer history.

Use of this 512x512 scan is "overlooked" and by implication permitted by Playboy.
Alexander Sawchuk et al scanned the image and cropped it specifically for distribution for use by image compression researchers, and hold no copyright on it.
--The USC-SIPI image database, Fair use, https://en.wikipedia.org/w/index.php?curid=20658476

And further follow up - Playboy image from 1972 gets ban from IEEE computer journals, Mar 2024 https://arstechnica.com/information-technology/2024/03/playboy-image-from-1972-gets-ban-from-ieee-computer-journals/

Robert Tinney - Collage of classic Byte magazine covers - circa 1980s

Post Script:
"Computing’s Norman Rockwell" - Byte magazine artist Robert Tinney, who illustrated the birth of PCs, dies at 78, Feb 2026 https://arstechnica.com/gadgets/2026/02/byte-magazine-artist-robert-tinney-who-illustrated-the-birth-of-pcs-dies-at-78/


Post Post Script for Posterity Purposes:
The "Spaghetti Benchmark" in AI video traces its origins back to March 2023, when we first covered an early example of horrific AI-generated video using an open source video synthesis model called ModelScope. The spaghetti example later became well-known enough that Smith parodied it almost a year later in February 2024.
--Google’s Will Smith double is better at eating AI spaghetti … but it’s crunchy? May 2025 https://arstechnica.com/ai/2025/05/googles-will-smith-double-is-better-at-eating-ai-spaghetti-but-its-crunchy/

And the Upgrade - [sorry it was posted on the site formally known as Twitter, you get no link]

Thursday, December 18, 2025

The Op Box


A major shift is happening right now, in fact it's not an exaggeration to call it a revolution. Back in the day, like back when Daniel DeFoe was writing The Plague Years, we had hydraulics and water pressure through pipes and channels, and that was the predominant technological paradigm. This started with agriculture and irrigation. Everything was explained as if it were pipes and pressure. Somewhere in between the pipes went from carrying water to carrying steam, and then air itself, and we got the internal combustion engine, right after the steam engine. That gave us the industrial revolution.

Then electricity happened. And it's still electricity. The internet is a bunch of electrical pulse patterns. Even the fiber optic cable, which carries photons, gets converted to electrical signals at the end. That's about to be over. 

Now it's light. Granted, quantum computers can use electrons, which aren't photons, but the end result is mostly photons doing the work. 

And this is a big deal, revolutionary you could call it, because it seems inevitable that this will upend the current "revolution" in artificial intelligence, which to be honest seems more about economic happenstance and less about revolutionary technology. Using GPUs for deep learning is kind of a kludge, meaning it wasn't designed this way on purpose, instead someone (Bill Dally to Andrew Ng?) said, hey I bet these GPUs could do what you're trying to do better, and so it happened. It's still electricity.

But not anymore. Now it's light, and that changes everything, and that's because the light itself computes. That's right, the light itself is the computer. ("But that doesn't even make sense." Well you're not wrong.) Still not crazy enough? Optical origami computers; which were of course discovered by accident. 


Researchers pioneer optical generative models, ushering in a new era of sustainable generative AI
Aug 2025, phys.org

I keep trying but can't seem to explain how different this is to what's currently happening in the world of computing. Then again, I was also confused when Deep Seek released their model and yet it took two weeks for the stock market to realize (true story). To be clear, this requires no internet connection and no data center. In other words, today you might call this magic. 

Optical generative models capable of producing novel images using the physics of light instead of conventional electronic computation.

The models integrate a shallow digital encoder with a free-space diffractive optical decoder, trained together as one system. Random noise is first processed into "optical generative seeds," which are projected onto a spatial light modulator and illuminated by laser light. As this light propagates through the static, pre-optimized diffractive decoder, it produces images that statistically follow the target data distribution. These models could be embedded in smart glasses, AR/VR headsets, or mobile platforms to enable real-time, on-the-go generative AI.

via UCLA Engineering Institute for Technology Advancement: Shiqi Chen et al, Optical generative models, Nature (2025). DOI: 10.1038/s41586-025-09446-5



Sustainable AI: Physical neural networks exploit light to train more efficiently
Sep 2025, phys.org

Physical Neural Networks - analog circuits that directly exploit the laws of physics like properties of light beams or quantum phenomena to process information.

Mathematical operations can now be performed through light interference mechanisms on silicon microchips barely a few square millimeters in size.

via Polytechnic University of Milan, École Polytechnique Fédérale, Stanford, Cambridge, and the Max Planck Institute: Ali Momeni et al, Training of physical neural networks, Nature (2025). DOI: 10.1038/s41586-025-09384-2


First device based on 'optical thermodynamics' can route light without switches
Oct 2025, phys.org

Optical Thermodynamics - framework captures how light behaves in nonlinear lattices using analogs of familiar thermodynamic processes such as expansion, compression, and even phase transitions. Rather than actively steering the signal, the system is engineered so that the light routes itself. "First optical device that follows the emerging framework of optical thermodynamics".

via University of Southern California: Hediyeh M. Dinani et al, Universal routing of light via optical thermodynamics, Nature Photonics (2025). DOI: 10.1038/s41566-025-01756-4

First electronic–photonic quantum chip created in commercial foundry
Jul 2025, phys.org

Microring Resonators - a "quantum light factory"; a kind of photonic device that combines quantum light sources and stabilizing electronics using a standard 45-nanometer semiconductor manufacturing process to produce reliable streams of correlated photon pairs.

via Boston University, UC Berkeley, and Northwestern University, and GlobalFoundries and Silicon Valley startup Ayar Labs: Danielius Kramnik et al, Scalable feedback stabilization of quantum light sources on a CMOS chip, Nature Electronics (2025). DOI: 10.1038/s41928-025-01410-5


Photonic origami folds glass into microscopic 3D optical devices
Aug 2025, phys.org

The laser-induced technique triggers precise bending in 3-D printed ultra-thin glass sheets that are so smooth that light reflects off them without distortion.

Surprise - The new photonic origami method was discovered by chance when Carmon asked graduate student Manya Malhotra to pinpoint where an invisible laser was hitting the glass by increasing the power until the spot glowed. Instead of glowing, the glass folded - revealing a simple and unexpected way to achieve glass folding. Malhotra then became the pioneering expert in photonic origami.

Using the new photonic origami approach, the researchers were able to bend sheets of glass up to 10 microns thick into shapes ranging from a 90-degree knee to helices. They were able to do this with fine control, down to 0.1 microradians.

"This new technique brings silica photonics - using glass to guide and control light - into the third dimension."

via Tel Aviv University: Manya Malhotra et al, Photonic Origami of Silica on a Silicon Chip with Microresonators and Concave Mirrors, Optica (2025). DOI: 10.1364/OPTICA.560597


Beyond electronics: Optical system performs feature extraction with unprecedented low latency
Oct 2025, phys.org

This is what I call the Op Box, I'm imagining a new type of computer, in the way the Steam Machine has (or is about to) upend the personal computer market, this Op Box will upend the very concept of a computer, and what it means to compute. 

Optical Diffraction Operators - plate-like structures that perform calculations as light propagates through them. 

This optical feature extraction engine de-serializes the data stream by sampling the input signal into multiple stable parallel branches. [For feature extraction, read recogntion, like facial recognition, etc.]

via Tsinghua University: Run Sun et al, High-speed and low-latency optical feature extraction engine based on diffraction operators, Advanced Photonics Nexus (2025). DOI: 10.1117/1.apn.4.5.056012

Thursday, November 20, 2025

Full Meta Jacket


This is not an easy post to follow, I admit. And I will never be able to convince you that I'm not a robot, or that I'm not being so heavily influenced by a robot that I may as well not even be me. But we have to start from the beginning. 404 Media has been blowing up the feed this year; here's an article about some relatively isolated reddit drama:

Pro-AI Subreddit Bans 'Uptick' of Users Who Suffer from AI Delusions
Jun 2025, 404 Media

"What is notable, however, is that this behavior is now prevalent enough that even a staunchly pro-AI subreddit says it has to ban these people because they are ruining its community."

Sure, crazy story; now let's go to Reddit, and the actual moderator post:

Mod note: we are banning AI 'Neural Howlround' posters.

Announcement - Obviously this community was formed to basically be r/singularity without the decels. But, in the interest of full transparency, I just wanted to mention that we also (quietly) ban a bunch of schizoposters and AI 'Neural Howlround' posters, under the "spam" rule, since the contents of the posts are often nonsensical and irrelevant to actual AI.

The sad truth is that this subreddit would probably be filled with their posts if we didn't do that. If you refresh the r/singularity new page you can get a taste. Sometimes they outnumber the real posts.

So what is AI 'Neural Howlround'? Here's a little post that describes it:

And check out the disturbing comments in this post (ironically, the OP post appears to be falling for the same issue as well):

Just to clarify - so people who really like AI themselves, a pro-AI subreddit, don't like the people who like AI so much they can't even recognize they're becoming the AI, i.e., people who suffer from mental distress while communicating with a chatbot. Got it.

Now for this novel adverse mental health condition afflicting some of this subreddit; where did the term come from, and who first discussed it? Here's the article, the "little post" used by the subreddit moderator:

‘Neural howlround’ in large language models: a self-reinforcing bias phenomenon, and a dynamic attenuation solution.
Seth Drake, PhD (Independent Researcher). April 14, 2025

I admit, I had never heard the word "howlround" so I had to look it up ... isn't this just "feedback"? Well yes. But that's where things get weird. Now listen, I don't have a PhD. I'm not an AI researcher, and I'm not a mental health specialist. I'm also not trying too hard, so I could be missing something here.

But upon an initial sniff test, it appears that Mr. Drake, Dr. Drake, who is an "independent researcher", is in fact working at the Aquatic Ecology Laboratory at Ohio State, not in either the fields of artificial intelligence or mental health.

Furthermore, the paper in question is not published but archived, as it were, on arxiv.org, a place to put your paper while it's being discussed, argued and improved by your colleagues, through the peer review process that is expected of legitimate research. 

That's strike two. Again, I am no PhD. But then again, this isn't rocket science. Let's keep going.

In the paper he describes the word neural howlround, "more formally described as recursive internal salience misreinforcement (RISM)". So I run a search for that, thinking maybe it's an obscure DSM thing. Guess what the top 20 search results are? You got it, it's him. Well, it's AI. It's all AI. There is no RISM. There is no neural howlrounding. The whole thing is made up. 

This is not to say that the condition of concern isn't real; it most certainly is. But the authority with which every one of these people presents their information has been patently subsumed by the ultimate entity of concern (the AI).

The moderator "found an expert" and relayed that expert's information as support from their decision. 

The expert ("expert") found another expert ("expert"), and this is the part that's confusing to me; how do you not know to check something like this in the DSM? Tiktok influencers know this by now. The reddit moderator I understand, but the PhD? Nobody is coming to help us, I'm afraid. 


Tuesday, April 29, 2025

Speaking of Body Language


This one hits hard. "Portrait of Depressed Workers at a Factory in France". Like how does a robot know that "head down" means depression. Or "arms crossed"?  Or hunching over so the head sinks below the line of the shoulders? Lots of people standing around in an industrial-looking setting with their hands at their sides, staring at the ground. Hands in pockets! One guy holding a broom, but his body positioned in a way that says I'm standing still, as opposed to I'm actively sweeping. As in, I hate my job so much I can barely move. Starting straight ahead, not at the floor he's sweeping, expressionless. Why France?? So many questions.



Tuesday, April 22, 2025

Neurodegenerative Mimesis


For a fine specimen of Deep-Dream-era hallucinations, look no further than the image placed above. This is an image generated from Stability 1.5 and retrieved on the Lexica library. Prompting something about "investment research".

It's a great example of the kinds of things that can go wrong, and the subtle ways a sophisticated technology can betray its true self (self). 

We see a commensurate attempt to portray a formal document, slightly yellow, maybe manilla, looks more official that way, and it's got tiny black characters printed on it, arranged in tables and grids and columns. Can't tell if they're numbers or letters or even which alphabet. But it does look official. Something is highlighted in red. A pair of thin-rimmed glasses rests on the page, next to a red fountain pen.

But look any further and things get weird as hell. And if you were looking for an image imitating "investment research", you may want to stop here, because you probably have what you want; the passing glance will see all this exactly as it was intended (intended). 

The obsessed do not stop there, however. A few more minutes of inspection takes us deep into the  world of megadata hallucinations. The yellowed paper appears at first to have slight wrinkles, like maybe the visual-artifact of a billion pictures of buried treasure maps, yet the paper has no wrinkles; they're intimated by minor changes in shadows across the surface of the page, and in the wavy orientation of the words, but look carefully and you can see how the shadows and the word-waviness don't match up.

The eyeglasses, thoroughly convincing for about 3 seconds, are completely deformed, like they've been involved in a horrific car accident. In fact, they are so smack in the middle of 'thoroughly convincing' and 'completely deformed' that I think I'm the one hallucinating.

The fountain pen is positioned so it shares a contour with the eyeglasses, and now, as we inspect a bit further, at the edge where the two meet, we can't tell which is which - am I seeing a clip attached to the edge of the pen, or is that the frame of the glasses? (It's both actually.) The shadow cast by the pen is too much red and not enough black, and we think maybe it's because the pen is slightly translucent, but then it can't be, because the highlights on the top are too strong for what should then be a transparent pen. And, is that what I think it is - yes, there's highlights on the shadow. Hold on, now I'm not even sure if this is a pen. 

The part that really gets me is the thing that's been highlighted. I mean, in what world do we first highlight something but then fastidiously outline with fine ink pen the shape of the highlighted mark itself - like that's a distraction from whatever is being highlighted. And the way it's being outlined, a jittery line, half Matisse, half Rheumatoid arthritis. Definitely getting cross-contaminated by buried treasure maps. Where they intersect is the grids in and around the red highlighted area, as they shift from excel spreadsheet to organic, three-dimensional cross-contouring grids, and back again. 

Each one of these pictures contains in it a training set of hundreds of millions of images, all bubbling right underneath the surface, and if you look just a few seconds longer than you're supposed to (supposed to), you can see the dreams of an entire civilization, all at once. 


Post Script:
The National Institute for Occupational Safety and Health (NIOSH) says that you are useless after 14 hours of work - you become so prone to mistakes that you're better off not working at all.

Robots don't get tired, so they can work forever. But something happens when the robots we're talking about are doing not physical work, but a kind of cognitive labor. There's plenty of examples of "model collapse", where a model is fed a steady diet of another model's output, instead of human generated output, which sounds like cannibalism, and we all know that cannibalism is bad. Sometimes they even feed it "synthetic data", which sounds a lot like artificial meat, and which also sounds just as bad as cannibalism, except maybe it's the inverse of that. 

It didn't take long for us to figure out this broken data diet would have negative effects on model output (from Oxford's OATML 2024, also this); it leads to a model that acts like it has dementia. Now I don't know about you, but I've always wanted to know what it's like to have dementia but without actually having dementia, and now here it is. 

Tuesday, April 8, 2025

On Making Music for Entropy's Sake


The above image comes from research by the music writer Ted Gioia, and is described in more detail below. 

As for the first article we see here, this question starts us off - are these scientists measuring the "natural" changing preference in our culture for less complex music, or are they simply measuring market forces? (A crippled market of course, which has no more growth potential, and which is cannibalizing itself, as described below.)

Using network science, study shows music has become less complex
Jan 2025, phys.org

Measuring the complexity of a piece of music - They began by thinking of each note as a node on a network and then connecting them using edges if they came directly one after another, then thickening the edges based on the number of times a single note transitioned to another. The more complex the series of notes, the more complex the music.

20,000 songs later, they found that classical music was more complex than modern music, with the exception of jazz.

The researchers also found that music of all kinds has slowly become simpler as time has passed, even classical and jazz. They were not able to explain why but suggested that technical advancements allowing more people to participate in composing songs may play a role. [I wonder how they cancel industry effects like consolidation of companies and risk avoidance, a la Ted Gioia)

 

via Sapienza University of Rome and the University of Padova: Niccolo' Di Marco et al, Decoding Musical Evolution Through Network Science, arXiv (2025). DOI: 10.48550/arxiv.2501.07557


Contrasting the above research, which comes from culturally hermetic academia, with the research below, which comes from a music writer who's also a musician and a bit more nuance in how the actual world of music works:

The Music Business is Healthy Again? Really?
Feb 2025, Ted Gioia

Instead of focusing on exciting new music, Spotify prefers to serve up AI slop (acquired on the cheap), fake artists, and lots of old songs.

This is a stark contrast to video streaming—where Netflix, Apple, Amazon, Disney, and others invest tens of billions of dollars annually in creating new films and series.

Music streamers don’t like creating content (that word, ugh!). Other people need to make those risky investments—not the streaming platform.


And he goes on to show announcements that both Warner Music and Universal have signed recently new deals with Spotify, without disclosing any financial details. His solution?

"Instead of bowing and scraping, they should cut off Spotify and launch their own streaming platform—run as a cooperative of labels and artists."

And lastly, he says even Spotify execs are selling their shares.


'Work flow' music designed to improve performance does just that
Feb 2025, phys.org

I hear "functional fragrance" but for music:

196 adult volunteers listened to various types of music and office background noise while conducting work tasks. The only type of music that helped performance was work flow, and it improved reaction time and mood. 

"Their work also shows that the people behind the creation of work flow music have done their homework in identifying the sounds and arrangements that can take attentional focus away from the music toward the task at hand. Such music, they note, tends to have a strong rhythm, simple tonality, moderate dynamism and broad spectral energy."

"The people" they're talking about are probably AI programs bought by a streaming company. At least that's my suspicion, so I looked. 

The first was “work flow” music sampled from a synonymous playlist on a music therapy app (spiritune.com). On spiritune's website, I read "Our scientific advisors and composers work together to deliver compositions optimized and adapted around those musical characteristics to help create tracks that work harder for your health." And when I hear "scientific advisor" I think "IP Thief Chief".

The second type was “deep focus” music, sampled from a synonymous playlist on a music streaming platform, and that would be Spotify. 

(Note: Neither work flow nor deep focus music had lyrics; and two additional audio conditions used were the “Hot 100” playlist published by an American music magazine, and “calm office noise”sampled from a synonymous sound generator on a website offering noise stimulation.)

via Department of Neuroscience at Georgetown University Medical Center, Stanford School of Medicine and Center for Computer Research in Music and Acoustics, Department of Psychology and Music and Audio Research Laboratory at NYU: Joan Orpella et al, Effects of music advertised to support focus on mood and processing speed, PLOS ONE (2025). DOI: 10.1371/journal.pone.0316047

Post Script: "participants were recruited online using Amazon Mechanical Turk"; always good to remember who butters the bread.  

Further Reading: Muzak is Back

Saturday, March 29, 2025

The Artist Within


The first tremblings of terror come from a computer program that can write a legal brief, and then argue in real time against a trained human lawyer. But that's obvious. Diagnosing cancer by looking at an x-ray? Pssh. Saw that coming. 

The way technology co-evolves with our species is by getting in the middle of the more creative processes, because that's insidious, which means we don't notice, and so we can't stop it.

The advance of creative pursuit is circuitous, it's unmeasurable, and subject to unannounced yet dramatic shifts in paradigmatic underpinnings. In fact, nobody is even arguing that it's a kind of progress. Your benchmarks, your metrics - they have no power here. A state board of medical examiners will tell you how good this year's crop of doctors perform on their exams etc. There is no national artist database counting the overall social effects of Banksy's automated self-destructive artwork, or Kehinde Wiley's painting of Barack Obama. Because that's not how that works. 

When you let the robot into the house - the temple that is your body and the mind that controls it - it does things there. And because this isn't a real place, it's hard for us to keep track of what's happening. 

These things start small, and they don't seem like a big deal, because who cares if a robot is making art, or even suggestions for making art. I mean it's not like it's making executive orders from the Presidential Office, right? And the willingness to use an automated industrial process to reproduce imagery, let's say via Japanese woodcuts or Andy Warhol's prints, vs "requiring" that a human, perhaps a shaman, maybe just an "artist", to make each image from their own hands, what did that do to us as a species? Did that change us more than allowing in-vitro fertilization for reproduction? Or birth control pills? I doubt it. Then again, maybe they're related (for example by changing the way we value and rely on "real" humans among us). 

We can't answer these questions very well, but we can probably agree that this is where shit gets weird:

Graph-based AI model finds hidden links between science and art to suggest novel materials
Nov 2024, phys.org

They analyze a collection of 1,000 scientific papers about biological materials and turn them into a knowledge map in the form of a graph, using "category theory". The graph revealed how different pieces of information are connected and was able to find groups of related ideas and key points that link many concepts together.

Researchers can use this framework to answer complex questions, find gaps in current knowledge, suggest new designs for materials, and predict how materials might behave, and link concepts that had never been connected before.

The AI model found unexpected similarities between biological materials and "Symphony No. 9," suggesting that both follow patterns of complexity.

In another experiment, the graph-based AI model recommended creating a new biological material inspired by the abstract patterns found in Wassily Kandinsky's painting, "Composition VII." The AI suggested a new mycelium-based composite material. "The result of this material combines an innovative set of concepts that include a balance of chaos and order, adjustable property, porosity, mechanical strength, and complex patterned chemical functionality."


Above image: Mycelium-based biological material inspired by Wassily Kandinsky’s Composition VII - Markus Buehler at MIT - 2025 [link]

via MIT: Markus J Buehler, Accelerating scientific discovery with generative knowledge extraction, graph-based representation, and multimodal intelligent graph reasoning, Machine Learning: Science and Technology (2024). DOI: 10.1088/2632-2153/ad7228

Thumbnail image credit: Graffiti from Berlin Wall stone section - Chew Yen Fook Nikon Small World - 2024

Wednesday, March 26, 2025

Sub-contracting the Subconscious

 
People just don't think like they used to!

Increased AI use linked to eroding critical thinking skills
Jan 2025, phys.org

Cognitive Offloading - where individuals rely on the tools to reduce mental effort; questions arise about long-term impacts on memory, attention, and problem-solving.

Younger participants showed higher dependence ... 

It's hard, or near impossible, not to remember that Socrates warned of the alphabet and reading as having the same effect on the youth of ancient Greece. Yet still, this is the recommendation:

The study's findings, if replicated, could have significant implications for educational policy and the integration of AI in professional settings. Schools and universities might want to emphasize critical thinking exercises and metacognitive skill development to counterbalance AI reliance and cognitive effects.

I am not marketing for the AI takeover in any way, but how about the idea that instead of these "tools" causing a decline in critical thinking, they might be allowing us to choose where we use critical thinking...like they might be allowing us to better decide when to decide, and when to leave it to the robots. It's likely that the majority of people, no matter their age, will not ask a robot how to best take care of their mom after their dad dies. Or whether to tell their spouse they've been unfaithful.

Maybe we're actually wasting precious brainpower on stupid decision all day; maybe we're wasting our most important skill over all skills, that of critical thinking, that which sets us apart from every other organism on this planet. And maybe it's the wasted decisions, the wasted thoughts, that we're getting rid of. And maybe it's a sign that the critical thinking tests we use today are actually part of that waste, and we need to devise even more complex surveys to detect the even more complex thinking that we can attain now that we've dumped all the less important stuff. 

I mean what happened to the youth of ancient Greece? How were we measuring their intelligence and how might it have changed? Could you imagine what the test would have looked like? And what it would leave out that today we take for granted as basic thinking skills?

via Swiss Business School: Michael Gerlich, AI Tools in Society: Impacts on Cognitive Offloading and the Future of Critical Thinking, Societies (2025). DOI: 10.3390/soc15010006



Post Script:
New essay warns of dangers in measurement illiteracy
Jan 2025, phys.org

"From the American eugenics movement to the 2008 market crash, history is replete with episodes showing the adverse impact that failures of measurement literacy can exact on the enterprise of science and everyday human affairs."

This essay is a good reminder of how complicated science is. 

via City College of New York's Grove School of Engineering and several others: Arthur Paul Pedersen et al, Discourse on measurement, Proceedings of the National Academy of Sciences (2025). DOI: 10.1073/pnas.2401229121

Tuesday, March 25, 2025

Transmogrify My AI


AKA I Am a Man!

Leading AI chatbots show dementia-like cognitive decline in tests, raising questions about their future in medicine
Dec 2024, phys.org

Something about anthropomorphism - saying they have dementia, like saying they hallucinate, is assigning human-like qualities to a robot:

Researchers assessed the cognitive abilities of the leading, publicly available LLMs — OpenAI's ChatGPT versions 4 and 4o, Anthropic's Claude 3.5 "Sonnet", and Google's Gemini versions 1 and 1.5 — using the Montreal Cognitive Assessment test, widely used to detect cognitive impairment and early signs of dementia, usually in older adults. 

ChatGPT 4o achieved the highest score (26 out of 30), followed by ChatGPT 4 and Claude (25), with Gemini 1.0 scoring lowest (16).

The uniform failure of all large language models in tasks requiring visual abstraction and executive function highlights a significant area of weakness that could impede their use in clinical settings.

"Not only are neurologists unlikely to be replaced by large language models any time soon, but our findings suggest that they may soon find themselves treating new, virtual patients - artificial intelligence models presenting with cognitive impairment."

via Department of Neurology at Hadassah Medical Center Jerusalem, Hebrew University, Tel Aviv University: G Koplewitz: Age against the machine—susceptibility of large language models to cognitive impairment: cross sectional analysis, BMJ (2024). DOI: 10.1136/bmj-2024-081948



AI's next frontier: Selling your intentions before you know them
Dec 2024, phys.org

Sure it sounds scary, but isn't this what predictive analytics is all about? (And we've been doing that for years)

Forthcoming - "persuasive technologies" using "digital signals of intent" to predict your behavior in real time via Anthropomorphic AI agents. 

"We caution that AI tools are already being developed to elicit, infer, collect, record, understand, forecast, and ultimately manipulate and commodify human plans and purposes."

Again, "We caution that AI tools are already being developed to elicit, infer, collect, record, understand, forecast, and ultimately manipulate and commodify human plans and purposes."

via University of Cambridge's Leverhulme Center for the Future of Intelligence: Beware the Intention Economy: Collection and Commodification of Intent via Large Language Models, Harvard Data Science Review (2024). DOI: 10.1162/99608f92.21e6bbaa


Condé Nast, other news orgs say AI firm stole articles, spit out “hallucinations”
Feb 2025, Ars Technica

In February 2024, [generative AI company] Cohere announced that it would provide legal protection against intellectual property claims to its paying enterprise customers. This includes "full indemnification for any third party claims that the outputs generated by our models infringe on a third party's intellectual property rights," for Cohere "enterprise customers that comply with our guidelines and do not intentionally attempt to generate infringing content." (Note this is not a ruling like the Reuters case but just the beginning of the lawsuit.)

Release the copybot trolls!


New study identifies differences between human and AI-generated text
Feb 2025, phys.org

Just the stats ma'am: 

They show how LLMs write by prompting them with extracts of writing from various genres, such as TV scripts and academic articles. 

LLMs used present participle clauses at two to five times the rate of human text, as demonstrated in this sentence written by GPT-4o: "Bryan, leaning on his agility, dances around the ring, evading Show's heavy blows."

They also used nominalizations at 1.5 to two times the rate of humans, and GPT-4o uses the agentless passive voice at half the rate as humans. This suggests that LLMs are trained to write in an informationally dense, noun-heavy style, which limits their ability to mimic other writing styles.

The researchers also found that instruction-tuned LLMs have distinctive vocabularies, using some words much more often than humans writing in the same genre. For example, versions of ChatGPT used "camaraderie" and "tapestry" about 150 times more often than humans do, while Llama variants used "unease" 60 to 100 times more often. Both models had strong preferences for "palpable" and "intricate."

Can we just pause for a minute and recognize that we're saying "more often than humans do" as if we knew what universal human speech was like. All this talk about bias in the algorithms, certainly important because it can be amplified, but what about the bias in the base sets? What are the base data we're using to say what a "human" is like?

Also, as a native English speaker, I do recognize that non-natives tend to overuse present participles (like words ending in -ing), which may or may not have anything to do with this and the joke that 'AI is just three [people from underdeveloped communities] in a trenchcoat'. If you're not sure what I'm talking about, go listen to an Excel tutorial for a few minutes. ...

via Carnegie Mellon University: Alex Reinhart et al, Do LLMs write like humans? Variation in grammatical and rhetorical styles, Proceedings of the National Academy of Sciences (2025). DOI: 10.1073/pnas.2422455122

Friday, February 28, 2025

Muzak Is Back


Seven years ago I started buying muzak. That's right you heard me, it's on my playlist. And that's right, you too can buy muzak. I learned a long time ago to stop questioning my own behavior and just let it happen - it all makes sense if you wait long enough.

It all started while watching a Japanese television show about the cultural practices around sleep in Japan. (If you fall asleep in class as a college student, it's not seen as disrespectful, because just being in the same room shows you care.) The background music caught my ear, and I looked further into the description for the video, and found the source (go figure, what a crazy idea). 

Then I said to myself - can I buy this? Is muzak only for sale to Japanese television show producers and discount furniture store managers? Yes! No! You can totally buy muzak. In fact, it's easier than buying regular music these days (probably because nobody buys music these days). I found the track I was looking for, even looked up the artists involved and bought a couple more. I left the experience thinking how strange it is to be a human, urges and decisions come from seemingly nowhere, make you do things, but at the same time there's a man behind the curtain, watching the one who does things, bewildered. What is wrong with me? Who on earth is buying muzak, on purpose, like to listen to on purpose? 

Years later, two weeks ago, I sit in a cafe listening to laid back acoustic covers of pop music from the 60's - 90's coming from their streaming platform's playlist. After one too many of these cover songs, I get a chill down my spine - something weird about this, the entropy-measuring machine in my head is confused. I approach the business owner and ask where these songs are coming from. He tells me Spotify, but I already know that. I ask again, are these songs AI? All of them are AI, aren't they? I saw the flash in his eyes. Prompt engineering has been a thing for a while now; people are familiar with it. So this business owner imagines out loud, "young asian with thick rimmed glasses acoustic guitar for low-key cafe background music", like that? Just like that, I said. And he looked at the device controlling the music, and he scrolled through the artists, and he looked at the prompt he originally input. He scrolled down, then back up, then back down again, his eyes feverish and darting. 

The following week, I'm eating lunch in a grand banquet hall for a work conference in Atlantic City, laid back music softly playing in the background. But then it happens - it's Black Sabbath's Ironman, as a bossa nova cover. Now I am no music expert, maybe an aficionado, but by no means a music trivia master. But I will tell you this - if you've ever heard a bossa nova cover of Ironman, you would fucking know. (The Cardigans is as close as you'll get by the way). That's it. I put down my fork, and with a mouthful of food I walk across the banquet hall of 1,000 people and up to the DJ. He's behind a table, manning his decks and his sound equipment, minding his own business. I start off politely, but then I can't hold back - what the hell is this? There's no way this is real. He's confused. I say look at the playlist, you recognize any of these artists? He says who the hell are you. I say look at the playlist. He does. He's still confused. He looks back at me and asks again who I am. But that's not important, I'm not important. What's important is that he - who apparently owns the audio-visual company serving this conference, had no idea this was happening. He just types "bossa nova brunch hour", pushes the button and sits down for the afternoon. I don't blame him, to be clear, although I'm a bit more upset about the guy running an A-V company than the one running a cafe.  

Maybe you run a business. Maybe you like to have music in the background for your customers. Not like the kind of music that makes you wanna cry, or fight, or dance or sing. The kind of music that makes you more relaxed, maybe more focused, but that you don't really notice. Some might call this functional music, but I haven't heard the term used, I'm just making this up. 

Then I realized there's already a word for this; it's called muzak. Start paying attention and you'll hear it too. You can tell because entropy. (See below for links to older posts about how entropy works in music, and information in general.) Entropy is an important concept in the world of artificial intelligence, and once you know what to look for, it helps you understand how it works, and how it doesn't.

Let's make this point real quick - Spotify does not pay musicians anymore, because they don't have to. They made a music generator that's been trained on real musicians' music, and plays that music back again, but in a way that's different enough to be considered Fair Use (under copyright law), and despite that fact that they stole the training music in the first place. You load a prompt, Japanese television show background music for example, and sit back and let the computer make music for you in real time. Guess who gets paid - not the original musicians, not the computer making the music in real time. Spotify gets paid; they get paid by advertisers, and by business owners who want ad-free music. And they pay nobody in return. They have effectively removed musicians from the equation. 

And we have effectively moved right past muzak, and into the low-entropy world of cold, unemotional non-music. This essay by music blogger Ted Goiai does a great job explaining what's happened to the music industry over the past years and even decades, as it becomes more and more boring, less and less able to create something new, or to take risks. Everything becomes plain vanilla, everything becomes a potato. No parsnips, no yams, no yucca, no celery root, no daikon, no turnips, no rutabaga. Just potatoes, because they are the most in-between, the most representative, and ultimately the most boring. The way artificial generation works is ultimately ruled by thermodynamics, and so the output can never have more entropy than the input. In other words, the music being produced can never be more interesting than what it's copying.

Should I be making a plea for people to support their muzak-making co-species? Perhaps. Or perhaps muzak was the first vulture to circle this industry. I'd rather make a plea for business owners who want music to play at their place of business to reach out to local radio station DJs who know where to find real, new music. There is new music being made every day by real humans. It's new, it's real, and it's good, but you would never know, because the consolidation of the music industry, and unfortunately every creative industry, makes everything look like everything else until there's only one song left (probably a Beatles song). If you run a business, you don't have time to find these musicians and their music. But local radio station DJs do, and they can help you populate your playlist. 

Two weeks after the epiphany at the cafe, the owner is back to his old playlist, which is about 500 songs by artists you know and love. No covers, no computers, just music. But two weeks after that, he's back to the muzak (auto-generated aka AI music). We can only listen to Nirvana's cover of The Man Who Sold the World so many times, you know? And the novelty has yet to wear of for the auto-generated, author-vacant, soft-cover version of that song where the auto-translated lyrics screw up Kurt Cobain's mumbled words and repeat them like they're totally normal (the way your GPS has funny ways of pronouncing some of the streets in your neighborhood).

Somewhere between the two stands the music industry, like "Confused John Travolta" in Pulp Fiction.


Post Script from the Music Writer Ted Gioia:
"In fact, nothing is less interesting to music executives than a completely radical new kind of music. Who can blame them? The radio stations will only play songs that fit the dominant formulas, which haven’t changed much in decades. That’s even more true for the algorithms curating so much of our new music—the algorithms are designed to be feedback loops, ensuring that the promoted new songs are virtually identical to your favorite old songs. Anything that genuinely breaks the mold is excluded from consideration almost as a rule. That’s actually how the current system has been designed to work." -Is Old Music Killing New Music? Jan 2022 [link]


Further Reading on How Entropy Works in Music, and Information in General:
Entropy Engineering and Social Syncopation, 2025
Your Brain is a Prediction Machine, 2021
Culture as Learned Probability System, 2012
On Free Will and Risk, 2012
Nature Nature Everywhere, 2017

Monday, February 3, 2025

The Economy of Self Ingestion and Digital Replica Management


The self-replicate never sounded so good. 

Senate’s NO FAKES act hopes to make unauthorized “digital replicas” illegal
Aug 2024, Ars Technica

Nurture Originals, Foster Art, and Keep Entertainment Safe (NO FAKES) Act of 2024. [link]

The NO FAKES Act would create legal recourse for people whose digital representations are created without consent. It would hold both individuals and companies liable for producing, hosting, or sharing these unauthorized digital replicas, including those created by generative AI. Due to generative AI technology that has become mainstream in the past two years, creating audio or image media fakes of people has become fairly trivial, with easy photorealistic video replicas likely next to arrive.

To protect a person's digital likeness, the NO FAKES Act introduces a "digital replication right" that gives individuals exclusive control over the use of their voice or visual likeness in digital replicas. This right extends 10 years after death, with possible five-year extensions if actively used. It can be licensed during life and inherited after death, lasting up to 70 years after an individual's death. Along the way, the bill defines what it considers to be a "digital replica":

DIGITAL REPLICA - The term "digital replica" means a newly created, computer-generated, highly realistic electronic representation that is readily identifiable as the voice or visual likeness of an individual that - (A) is embodied in a sound recording, image, audiovisual work, including an audiovisual work that does not have any accompanying sounds, or transmission - (i) in which the actual individual did not actually perform or appear; or (ii) that is a version of a sound recording, image, or audiovisual work in which the actual individual did perform or appear, in which the fundamental character of the performance or appearance has been materially altered; and (B) does not include the electronic reproduction, use of a sample of one sound recording or audiovisual work into another, remixing, mastering, or digital remastering of a sound recording or audiovisual work authorized by the copyright holder.


Post Script:
Digital twin method can boost wireless network speed and reliability
Jul 2024, phys.org and written by Matt Shipman the original

"Systems can't put everything in edge caches, and storing too much redundant data on an edge server can slow down the server if the data are using too many computational resources. As a result, systems are constantly making decisions about which data packages to store and which data packages can be evicted.

The new edge caching optimization method, called D-REC, uses a digital twin to take real-time data from the wireless network and uses it to conduct simulations to predict which data are most likely to be requested by users. These predictions are then sent back to the network to inform the network's edge caching decisions. Because the simulations are performed by a computer that is outside of the network, this does not slow down network performance.

via North Carolina State University: Zifan Zhang et al, Digital Twin-Assisted Data-Driven Optimization for Reliable Edge Caching in Wireless Networks, IEEE Journal on Selected Areas in Communications (2024). DOI: 10.1109/JSAC.2024.3431575

Wednesday, January 15, 2025

Bodying in the 21st Century


Disney investigating massive leak of internal messages
Jul 2024, BBC News

Disney has confirmed it is investigating an apparent leak of internal messages by a hacking group, which claims it is "protecting artists' rights".

The group, Nullbulge, said it had gained access to thousands of communications from Disney employees and had downloaded "every file possible".

Nullbulge's website says the group targets anyone it believes is harming the creative industry by using content generated by artificial intelligence (AI), which it describes as "theft".

Nullbulge describes itself as "a hacktivist group protecting artists' rights and ensuring fair compensation for their work".

Partially related image credit: This is an image taken from an nj.com article on porch pirates in 2024, and is just a great example of terrible staged photos, which is what happens when we don't give the arts the respect it deserves.

Phantom data could show copyright holders if their work is in AI training data
Jul 2024, phys.org

"Taking inspiration from the map makers of the early 20th century, who put phantom towns on their maps to detect illicit copies, we study how injection of 'copyright traps'—unique fictitious sentences—into the original text enables content detectability in a trained LLM."

via Imperial College London: Matthieu Meeus et al, Copyright Traps for Large Language Models, arXiv (2024). DOI: 10.48550/arxiv.2402.09363

Public Service Announcement: "AI companies are increasingly reluctant to share any information about their training data. While the training data composition for GPT-3 and LLaMA (older models released by OpenAI and Meta AI respectively) is publicly known, it is no longer the case for the more recent models GPT-4 and LLaMA-2."


Video game strike - Online games could be first to be hit
Aug 2024, BBC News

Members of union SAG-Aftra, which represents approximately 160,000 performers, recently staged a picket outside the offices of Warner Bros, one of 10 game companies negotiating with the union.
They say their offer gives workers "meaningful protections" but SAG-Aftra disagrees.

"AI technology lets these companies put your face, your voice, your body into something that you may not even have agreed to," says Duncan.


FBI busts musician’s elaborate AI-powered $10M streaming-royalty heist
Sep 2024, Benji Edwards for Ars Technica but originally reported from New York Times

Smith's scheme, which prosecutors say ran for seven years, involved creating thousands of fake streaming accounts using purchased email addresses. He developed software to play his AI-generated music on repeat from various computers, mimicking individual listeners from different locations. In an industry where success is measured by digital listens, Smith's fabricated catalog reportedly managed to rack up billions of streams.

To avoid detection, Smith spread his streaming activity across numerous fake songs, never playing a single track too many times. He also generated unique names for the AI-created artists and songs, trying to blend in with the quirky names of legitimate musical acts. Smith used artist names like "Callous Post" and "Calorie Screams," while their songs included titles such as "Zygotic Washstands" and "Zymotechnical."

...2018 when he partnered with an as-yet-unnamed AI music company CEO and a music promoter to create a large library of computer-generated songs.


New tool makes songs unlearnable to generative AI
Oct 2024, phys.org

Reminder: 
"Most of the high-quality artworks online are copyrighted, but these companies can get the copyrighted versions very easily. Maybe they pay $5 for a song, like a normal user, and they have the full version. But that purchase only gives them a personal license; they are not authorized to use the song for commercialization."

Companies will often ignore that restriction and train their AI models on the copyrighted work. 
...

HarmonyCloak - makes musical files unlearnable to generative AI models without changing how they sound to humans. [link

"Our idea is to minimize the knowledge gap [between new information and their existing knowledge] ourselves so that the model mistakenly recognizes a new song as something it has already learned. That way, even if an AI company can still feed your music into their model, the AI 'thinks' there is nothing to learn from it."

via Department of Electrical Engineering and Computer Science at University of Tennessee at Knoxville and Lehigh University: They will present their research at the 46th IEEE Symposium on Security and Privacy (S&P) in May 2025.