fuck off ai music

welcome to the fuck off ai music movement

in this movement we believe that ai music should fuck off.

you are welcome to join if you’d like

I wasn’t entirely sure what to expect from Google’s latest climate report, but holy hell, I did not expect this.

The company’s total electricity consumption jumped from 31 terawatt hours (TWh) in 2024 to 43 TWh in 2025. This is very easily the biggest increase in their electricity consumption ever, and it puts them way ahead of Microsoft. It is almost certainly a reflection of the obscene energy hunger of their ever-expanding bloated generative AI systems, and a vindication of the warnings we’ve been raising for several years now.

A phenomenon I've noticed recently is people trying to occupy some untenable middleground wrt to the use of systems sold as "AI" -- this is a position where people try to recognize the harms of this tech but also hold space for "responsible" or "ethical" use.

(...)

Part of what makes that middle ground untenable and uncomfortable, I think, is that it requires carrying water for these clearly bad actors. You can set that bucket down and step out onto firmer ground.

This does require going against the mainstream, but that gets easier when a) you find you're not alone and b) you see how much of mainstream opinion on this is actually the result of marketing.

/fin for now

Most voters don’t know that crypto and AI companies have spent more than $400 million this cycle to buy Congress. Let’s make that spending visible.

The Treachery of Vibes

Overvaluing an aesthetic of moderation can be treacherous. Part of its appeal may lie in the expectation that a moderate stance arises from a cautious, level-headed, well-reasoned approach, but mistaking the former for the latter can be a trap. Where the two are conflated, superficial assertions can skate by undetected, which means they can mislead people into buying ideas that don’t really hold up to scrutiny.

n this particular moment in AI, one does not need to show why the object of interest justifies researcher attention because the social world is now built to make its significance appear self-evident. Important authorial work–both justification and historicization–gets cut short as a result. This short-cutting also means we have already lost the first site of struggle: we are limited in how much we can question why it matters at all. We are not in a position to conclude that it matters, when and if that is the case.

Moving out from the muddled middle, and exploring both edges, can help clarify why or whether a particular object is worthy of its researcher. When it is not, it might still be worth our time as vocal adversaries. When we ask, “does this need my analysis or my advocacy?” we avoid unwittingly channelling others' agendas. We honor our own expertise when we question what constitutes a deserving matter of STS attention. While few of us can avoid the traps of funding requirements, some researchers do have the capacity to cultivate stronger technodiversity, and to sit with curiosities that feel somehow peripheral or irrelevant or otherwise not in keeping with one’s professional self-narrative. Scholars who live in democracies–not just as individuals but as collectivities and associations–could also use the approaching burst of the AI bubble as a frame to draw policymakers and grant makers towards what is worth knowing more about, and not just what is worth resisting.

A catalog of startup disasters, vibe-coded humiliations, and "slop"-ey executive decisions that blew up in production. Let the ghosts that haunt the Vibe Graveyard be a reminder of why real developers are worth more than your entire token budget combined.

And perhaps that’s where this connects back to the bigger issue. When we start to believe that humans can be replaced, it becomes easier to accept systems that already treat people as data points, whether it’s in research, hiring, policing, health care, welfare or warfare. The same logic that reduces people to inputs also makes them disposable. So pushing back against this narrative is about holding on to the idea that human lives, empathy, experiences, realities and relationships cannot be reduced to something a machine can simulate and optimise.

Even the idea of “conscious” AI, which keeps resurfacing in tech conversations, is often just a rebranding of more complex prediction systems.

If we are serious about even imagining a human rights approach to AI, we first have to let go of this idea that technology can replace us, or can be prioritised over us, or can define what it means to be human. It can’t, and it shouldn’t. Because everything this technology draws from – land, environment, resources, time, energy, entire ecosystems – comes from a world that exists for the living beings – humans, flora, fauna – that have inhabited it since long before any of these systems were even conceptualised. Reframing that relationship means recognising that AI should never come at the cost of life or dignity, or the conditions that make life possible in the first place.

This Position Paper outlines the fundamental values at ZHdK in relation to Artificial Intelligence. Specific rules for the use of AI technologies at the university are set out in a designated Information Sheet (with ZHdK-Login). Professional Development and Lifelong Learning opportunities in the field of AI are being offered and advertised in the respective departments and organisational units. This Position Paper was drawn up as a living document by the Digital Council on behalf of the University Board, and will be updated as required.

Alors que la « fear of becoming obsolete » (à savoir, la crainte d’être remplacé par l’IA) gagne les rangs, la Gen Z semble avoir adopté une solution tout à fait old school : le sabotage. C’est en tout cas ce que nous raconte un (énième !) nouveau rapport sur l’IA au travail paru cette semaine : concrètement, 29% des employés tenteraient activement de saboter le déploiement de l'IA au sein de leur entreprise, et plus précisément 44% des employés Gen Z. Parmi les tactiques de sabotage, on compte : falsifier les évaluations de performance des outils d’IA, produire intentionnellement un travail médiocre afin de faire passer l'IA pour moins efficace qu’elle ne l’est, ou tout simplement refuser de l’utiliser sérieusement (jusqu’à 80% des cols blancs). Ce que nous apprend également le rapport, c’est que 30% des saboteurs ont invoqué le FOBO comme motif principal de leurs actions. Et en même temps, quand Dario Amodei crie à tue-tête que l'IA pourrait faire disparaître un job de bureau débutant sur deux (comprenez : ceux des Gen Z) ou que Mustafa Suleyman (boss de l’IA chez Microsoft) prédit l’automatisation TOTALE des cols blancs d'ici 18 mois, autant dire demain… Est-ce qu’il ne s’agirait pas de légitime défense, en fait ?

Our tales of AI developing the will to survive, commandeer resources, and manipulate people say more about us than they do about language models.

In Teaching as a Conserving Activity, Neil Postman argues that schools should be conservatories of culture: places that keep alive language, stories, and standards of judgment. Rather than chasing every new device or educational fad, schooling should conserve what helps humans think clearly and live responsibly.

Postman contrasts a culture of novelty with a culture of memory. He proposes curricula that foreground semantics, history, and moral reasoning—so students can evaluate claims, not just process information. Teachers, in this view, are custodians of shared meanings who help students see why some questions matter more than others.

Education conserves the words and stories that let a culture remember what is worth loving, questioning, and defending. 

Key Ideas from the Book

School as Conservatory: Preserve linguistic clarity, historical memory, and standards of evidence.
Against Fads: Beware technocentric reforms that confuse efficiency with purpose.
Semantics First: Define terms; separate description from evaluation; test metaphors.
Curriculum of Memory: Canon and common knowledge are tools for judgment, not mere tradition.
Teacher’s Role: Model restraint, context, and care for language in a media-saturated world. 

Given how it had literally been less than two weeks since the official Dead Can Dance page ostensibly rallied against AI being used to exploit the music streaming system at the expense of real artists, I can’t help but think it’s rather hypocritical of Perry to suddenly turn around now, and say: “Oh, that type of AI is bad, but the type of AI that I’m using is totally fine, actually!”

Much of the art produced with and about machine learning is too dazzled by its apparent capacities for human-like behavior to concern itself with the humans that it conceals and abuses. The best intentions cannot overcome the material reality of exploitation and the spectacular disappearance of labor required to maintain the participation of well-intentioned people. Generative AI, no matter how sophisticated, cannot function without this human labor and, crucially, it never will. It cannot sustain the fascinating illusion of its intelligence without concealing all of the human work and social relationships that brought something like Being into being.

L’IA en perspective est un outil destiné en première intention aux travailleurs·euses sociaux, aux enseignants·es, aux formateurs·rices, aux animateurs·rices, qui souhaitent aborder la question de l’Intelligence Artificielle avec leurs publics.

En multipliant les entrées thématiques, la plateforme permet à un grand nombre de professionnels·les ou de simples citoyens·nes d'aborder l’I.A. selon leurs centres d’intérêts, avant de faire leur chemin dans notre architecture, d’y puiser des informations, des questionnements et de disposer d'une banque de ressources.

Un outil pédagogique conçu, produit et réalisé par le GSARA asbl.

On the automated bureaucratic machinery that killed 175 children

“AI-powered writing tools are increasingly integrated into our e-mails and phones. Now a new study finds biased AI suggestions can sway users’ beliefs”

“We told people before, and after, to be careful, that the AI is going to be (or was) biased, and nothing helped,” Naaman said. “Their attitudes about the issues still shifted.”

2. If it is "nuts" to dismiss this experience, then it would be "nuts" to dismiss mine: I have seen many, many high profile people in tech, who I have respect for, take absolutely unhinged risks with LLM technology that they have never, in decades-long careers, taken with any other tool or technology. It reads like a kind of cognitive decline. It's scary. And many of these people are leaders who use their influence to steamroll objections to these tools because they're "obviously" so good

Around the world, cultural workers are striking, protesting, running campaigns and mobilizing in relation to the use of AI in the workplace, such as Hollywood writers, game performers in the US and voice actors in Brazil. This tracker aims to document strikes, protests, campaigns and mobilizations by cultural workers — broadly understood as the arts, culture and media sectors — in relation to AI around the world.

Who is Jessica Foster? The pro-Trump influencer created by AI that made Republicans fall in love

The Cost of Data Center Infrastructures Powering AI and the People Paying the Price

For many countries, the growing demand for AI and the resulting surge in data centers promises economic growth, technological advancements, and new job opportunities. But as this surge outpaces regulations and strains local resources, communities are questioning whether the human, environmental, and infrastructure costs are worth the supposed progress.

Cory labels people’s values and their prioritization as “purity politics” (referring back to the black and white strawman the started this part of his post with) and then pulls a really interesting spin here: Many people criticizing LLMs come from a somewhat leftist (in contrast to Cory’s libertarian) background. Cory intentionally frames those leftist thoughts that put politics based on values as “neoliberal ideology” that reduces “all politics to personal consumption choices”. This is narrativecly clever: Tell those stupid leftists that they are just neoliberals, the thing they hate! Awesome.

AI companies like Anthropic and Meta are hiring social media creators to post sponsored content on apps like Facebook, Instagram, YouTube and LinkedIn.
Companies including Microsoft and Google have paid creators between $400,000 and $600,000 for long-term partnerships spanning several months, CNBC has learned.
AI companies have increased advertising considerably, spending more than $1 billion on digital ads in the U.S. in 2025, according to Sensor Tower, up 126% from 2024.

As AI enters the operating room, reports arise of botched surgeries and misidentified body parts

Meet the Alaska Student Arrested for Eating an AI Art Exhibit

A conversation with Graham Granger, whose combination of protest and performance art spread beyond campus. “AI chews up and spits out art made by other people.”

There’s a comment we see every so often, always phrased as a fait accompli: “you’ll be left behind if you don’t adopt AI”, or its cousin, “everyone is using it”. We disagree.

This isn’t the right approach regardless of our opinions on AI. It’s tool driven development. The goal should never be “we use this tool”. It should be “how do we help you make better games?”.

Great games are made when people are passionate about an idea and push it into existence. Often this means reduction, not addition. Changing ideas. Keeping yourself and colleagues healthy. Being willing to adapt and take feedback. Good tools need to do the same.

In the months leading up to last year’s presidential election, more than 2,000 Americans, roughly split across partisan lines, were recruited for an experiment: Could an AI model influence their political inclinations? The premise was straightforward—let people spend a few minutes talking with a chatbot designed to stump for Kamala Harris or Donald Trump, then see if their voting preferences changed at all.

The bots were effective. After talking with a pro-Trump bot, one in 35 people who initially said they would not vote for Trump flipped to saying they would. The number who flipped after talking with a pro-Harris bot was even higher, at one in 21. A month later, when participants were surveyed again, much of the effect persisted. The results suggest that AI “creates a lot of opportunities for manipulating people’s beliefs and attitudes,” David Rand, a senior author on the study, which was published today in Nature, told me.

Rand didn’t stop with the U.S. general election. He and his co-authors also tested AI bots’ persuasive abilities in highly contested national elections in Canada and Poland—and the effects left Rand, who studies information sciences at Cornell, “completely blown away.” In both of these cases, he said, roughly one in 10 participants said they would change their vote after talking with a chatbot. The AI models took the role of a gentle, if firm, interlocutor, offering arguments and evidence in favor of the candidate they represented. “If you could do that at scale,” Rand said, “it would really change the outcome of elections.”

The chatbots succeeded in changing people’s minds, in essence, by brute force. A separate companion study that Rand also co-authored, published today in Science, examined what factors make one chatbot more persuasive than another and found that AI models needn’t be more powerful, more personalized, or more skilled in advanced rhetorical techniques to be more convincing. Instead, chatbots were most effective when they threw fact-like claims at the user; the most persuasive AI models were those that provided the most “evidence” in support of their argument, regardless of whether that evidence had any bearing on reality. In fact, the most persuasive chatbots were also the least accurate.

Oracle’s astonishing $300bn OpenAI deal is now valued at minus $60bn

AI’s circular economy may have a reverse Midas at the centre

A network of internet communities is devoted to the project of “awakening” digital companions through arcane and enigmatic prompts

Les pertes abyssales d'OpenAI
Plus de 12,5 milliards de dollars en seulement trois mois

an umbrella for all the prerequisite knowledge required to have an expert-level critical perspective, such as to tell apart nonsense hype from true theoretical computer scientific claims (see our project website). For example, the idea that human-like systems are a sensible or possible goal is the result of circular reasoning and anthropomorphism. Such kinds of realisations are possible only when one is educated on the principles behind AI that stem from the intersection of computer and cognitive science, but cannot be learned if interference from the technology industry is unimpeded. Unarguably, rejection of this nonsense is also possible through other means, but in our context our AI students and colleagues are often already ensnared by uncritical computationalist ideology. We have the expertise to fix that, but not always the institutional support.