3- Whataboutism. This is used to brush off concerns about the externtalities of these systems. You eat meat, you fly on airplanes, etc, etc, how dare you talk about the impacts of data centers?
>>
4- Tone policing. People who are trying to occupy that uncomfortable, untenable space will claim that clear statements of harms/strong principles against use of these systems will "turn others away" as if the centrists are the ones actually pushing for more ethical practice.
But this "other people won't listen" remark I think is really a way of saying "This makes me uncomfortable" while trying to claim to be on the right side of history at the same time.
>>
5- Wishcasting. Some folks will point to scientific results from fields outside their own (usually media coverage thereof) that are marketed as having been done with "AI" and ask: How could you take a hardline against "AI" when it has provided XYZ?
>>
6- Exceptionalism. "I know this can be dangerous for people in general, but I know how to use it carefully."/"I know how to verify every output, and I am not deskilling myself." How do you know? Also, if you acknowledge the dangers to others, what example are you setting by talking about/talking up your use?
>>
So what is the best way out of that uncomfortable, untenable space? I think one key step is disaggregating the (non-coherent) set of technologies sold as "AI". If you don't call the stuff you work with "AI", you aren't saddled with trying to defend any of the rest of it.
>>
The most recent iteration of this conversation I was involved in turned in part on a strange, over-expansive definition of "genAI" which included, for ex, optical character recognition (OCR).
>>
OCR can be a useful tool for many research projects! OCR is also the kind of technology that gets better with better language models, i.e. more fine-grained models of which word(parts) go where. That has been true since before "genAI" and will be true after.
Just because you can use the synthetic media extruding machines to approximate the task of OCR, however, doesn't mean that that task can or should be used to justify the use of "genAI" in research.
>>
I think another important step is a values examination. What is important to you? How are those values supported or not by entering the discourse in a way that holds space for OpenAI/Anthropic/Google/Meta and all the other actors in this massive push to shove "AI" into every part of our lives as "not all bad"?
What are your research goals, what do you value about participating in scholarship, how can you meet those goals/act in accordance with those values and what obstacles are in your way?
>>
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
@emilymbender good thread. very good thread. many thanks for it. we do see this tension play out a lot, it's helpful to have positive advice for people in the middle of it.
Human beings have a genius for mean-spirited subtle insults.
In a recent meeting, a coworker was profusely praised for using CoPilot to summarize some very dry & voluminous documentation. It was kind of over the top.
Soon my puzzled coworker clued that they were obliquely putting her down. They were implying she was lazy and insufficiently bright enough to accomplish the task without a crutch like AI.
What's concerning was Copilot praising her in a similar fashion
@ireneista @emilymbender problem is: the whole world is crazy. It's difficult to stay sane. The fight against AI is the fight against capitalism. Thats difficult when one is employed in a capitalist society.
@emilymbender Good thread, not sure if I am in alignment with every detail, but certainly with the overall philosophy.
@emilymbender
Good thread!
@emilymbender Heard an interview today with two of the execs from Anthropic. The way they describe their products is maddening. They use words like thinking, intuition, and understanding. None of that is going on. I was screaming at the podcast.
@xvf17 @emilymbender Eh, don't get worked up. There's lots of bad stuff out there, no use wasting time on hate.
Denounce it, work against it, but hate is way too much effort only to the detriment of your well being.
I'd see hate being useful to stir to action at a rally but the podcast is pretty much ether.
@emilymbender @cohentheblue Not hate, just frustration. The people building this stuff should understand it, is my view.
@xvf17 @emilymbender Oh, don't you worry, they understand. Games inside games, hands washing hands etc.
Jun 24, 2026, 11:22 AM@cohentheblue @xvf17 @emilymbender You do the fascists' job for them friend, but you can stop at any time.
@pip @xvf17 @emilymbender You wot? By advising people not to wind themselves up where nothing other than damaging themselves is the result, I do the job of fascists? What are you on about...
Jun 24, 2026, 6:42 PM@cohentheblue @xvf17 @emilymbender
The result of not using AI is protecting yourself, your family, and your community. The result of not using AI is harm reduction, battling against the devastating social, political, and environmental costs of AI. The result of not using AI, is making it easier for others to refuse to use it as well.
So please, stop using AI.
@pip @xvf17 @emilymbender Where did you get that any of us uses AI?
Have you even glanced at our profiles for that matter?
You come across as an LLM yourself.
Nothing more frustrating than being misunderstood deliberately and repeatedly.
@xvf17 @emilymbender THIS IS SO UPSETTING. I am one of those folks advocating for using certain types of machine learning responsibly, like "identify the patients with cancer" which ML tools can do better than humans, and which were trained using ethical data sources.
But the LLM field is just a cesspool. I can *see* use cases for it, but holy shit fruit of the corrupt root system with that training data.
@SomeVeganCheeseIsOk
Oh no dude. This prof thinks you are an asshole then.
Read what she wrote again. She is full of fallacies herself.
@xvf17 @emilymbender
@Noisecolor @xvf17 @emilymbender I don't see that, really. She asks us to make certain specific things more clear in our speech, which is GOOD because "AI" as a term is so overused and awful, and you can't make good decisions on bad information. LLMs *are* a nightmare and *are* heavily overused and *do* have horrendous ethical issues. But machine learning is not always "AI", and I like people being asked to make the distinction because it's an important step.
@SomeVeganCheeseIsOk
Nightmare, heavily, horrendous... I don't think those are words that make anything clear.
I don't know what ai is when you put it in quotes.
I guess the good ai is the one you like and the bad ai is what bad people use or something?
@xvf17 @emilymbender
@SomeVeganCheeseIsOk @emilymbender @Noisecolor LLMs of today are not AI, in the traditional sense. The ChatGPT folks coopted the term. People (like me) who put it in quotes are doing it as a form of protest.
@xvf17
As far as I know AI was coined as simulated intelligence. I think LLMs are exactly that.
Ai is a term that we used to describe a bunch of systems. Chess engines, opponents in video games,... Now LLMs. Perhaps someday when we have even better systems we will call them ai, but for now ai seems to fit LLMs completely.
@SomeVeganCheeseIsOk @emilymbender @Noisecolor they are not simulated intelligence. That’s precisely my point.
@xvf17
Really? 😀
How is it not a simulation of intelligence?
@SomeVeganCheeseIsOk @emilymbender
@SomeVeganCheeseIsOk @emilymbender @Noisecolor it doesn’t reason. It doesn’t understand. It can’t explain its thinking. It has no intelligence. Stop believing the hype. For crying out loud.
@SomeVeganCheeseIsOk @emilymbender @Noisecolor @xvf17 don’t look at the apparent successes. Look at the failures. They are moronic nonsensical spews of gibberish. Their failure modes are entirely inconsistent with intelligence.
@xvf17
Thats great for you then. Because if they are so bad, no one will use them, right?
Not like hundreds of millions of people would use such a bad tool daily, creating any kind of pollution or if it.
@SomeVeganCheeseIsOk @emilymbender
@xvf17
Yes, a simulated intelligence exactly. I wish someone invented a term that describes that. Oh, wait,...
@SomeVeganCheeseIsOk @emilymbender
@Noisecolor @xvf17 @SomeVeganCheeseIsOk @emilymbender AI is literally the abbreviation of *artificial* intelligence. Not simulated intelligence. That feels like a real "moving the goalposts" moment.
AI as it has historically/originally been used is referencing a legitimate, non-organic intelligence. LLMs are smoke and mirrors, when it comes to intelligence. There is no cognition, no understand.
Personally, I prefer GenAI over scare quotes, but both are more accurate than LLM = AI
@theadhocracy
Not at all. You can freely browse the web or ask a chat who coined the term and why. It will be an interesting read I can assure you and you will understand that ai is not meant to refer to a specific human level intelligence like you mean. It wouldn't make sense at that time anyway.
@Noisecolor @xvf17 @SomeVeganCheeseIsOk @emilymbender Okay, literally my first reult:
"The term "artificial intelligence" was coined in 1956 at Dartmouth College by John McCarthy and colleagues to describe the new field of creating machines that could think and learn like humans."
So, it *means* "artificial", not "simulated". It covers inorganic "machines". And it references *thinking* and *learning*.
We can argue semantics on learning, but an LLM ticks 0 of those boxes.
@Noisecolor @xvf17 @SomeVeganCheeseIsOk @emilymbender And just to head off "learning", yes genAI has roots on "machine learning". But the output, the LLM, does not learn "like a human". Some may have reinforcement algorithms, but all that's fundamentally doing is a loop: take the new data, run your previous "training" algorithm, update your output.
Humans learn through understanding and cognition. An LLM does not. Otherwise they'd be able to do simple calculus before they could write essays.
@theadhocracy
"Doesn't learn like a human": True. Doesn't matter. Learning is adapting based on data. LLMs do that. That's the definition.
"Just a loop": Human brains are also "just" electrical impulses. Mechanism doesn't negate capability.
"Calculus vs. Essays": Outdated. Modern models handle both. Training order is not intelligence limit.
@theadhocracy
Quite the opposite LLMs tick all boxes: They are inorganic ("artificial"), they adjust weights based on data ("learn"), and they synthesize information to solve problems ("think"). Rejecting this is semantic gatekeeping, not historical accuracy.
@xvf17 @SomeVeganCheeseIsOk @emilymbender
@Noisecolor @xvf17 @SomeVeganCheeseIsOk @emilymbender No it's goalposts shifting, you're just changing the meaning of words 😂
And I'm not even sure why? Why do you **want** LLMs to be "AI"? If we actually get true AI, it'll be so much more than a statistical averaging model. Shouldn't we reserve the term for when it's applicable, and use terms relevant to the tools we have (like LLM)?
@Noisecolor @xvf17 @emilymbender talk to me about what you mean by the term simulated. Because I can see a use case where it means "fake, but enough to fool a human" and a use case for it just being a synonym for artificial. One of those is the traditional use, the other is a marketing use.
@SomeVeganCheeseIsOk
It's not a marketing term. We have always used this term. There was no marketing team involved.
Humans need words to describe certain stuff.
When we do choose those words those words are assigned that meaning. It's linguistics, it has nothing to do with who you think is a good or bad guy or what a certain group might like or not.
In certain times words can change or the meaning of words can change. But in this case it's pretty clear I think.
@Noisecolor @xvf17 @emilymbender AI as a linguistics term began in the science fiction community a long time ago to describe machine intelligence equivalent to or better than human intelligence. AI *as it is used today* is a marketing term to describe any one of a dozen machine learning tools, none of which have cognition or reasoning capabilities. Or, also as frequently, much cheaper decision tree bots with preprogrammed responses. The "human level" goalposts have moved to the term AGI.
@SomeVeganCheeseIsOk
You have 4 major fallacies there. 1.Etymology (ignoring how terms evolve)
2.No True Scotsman (only human-level counts)
3. False Dichotomy is bots vs. humans but ignores the middle
4 the marketing claim is completely false. Everyone used the term before any marketing.
LLMs fit the established AI definition by capability.
@xvf17 @emilymbender
@Noisecolor @xvf17 @emilymbender Can you explain how I am ignoring how terms evolve in meaning? From re-reading my own comment, it's entirely dedicated to the evolution of term usage.
@Noisecolor @xvf17 @emilymbender Can you explain how to describe intelligence without using humanity as a reference point?
@Noisecolor @xvf17 @emilymbender
I genuinely think you need to re-read my comment. It feels to me a bit like you're treating everyone in this thread like an antagonist to be fought. I am genuinely trying to have a conversation here.
@Noisecolor @xvf17 @emilymbender
Let me clarify: "AI" is an unbounded marketing term with wildly ambitious, ambiguous definitions. No machine performs contextual reasoning like a human at this time, but that's the implication of "AI" to most folks. Machine Learning is a bounded, defined, useful term which talks about compute systems with specific capabilities.
@Noisecolor @xvf17 @emilymbender Large Language Models are a form of machine learning that was built on stolen data by companies who, in part, design it to capture and hold attention for as long as possible, much like social media, to extract paid tokens from users. LLMs are the 1-900 numbers of this age. But worse, because they are simultaneously somehow a social disaster undermining human skills, an ecological disaster, and an economic disaster.
@Noisecolor @xvf17 @emilymbender How you do things matters. What you do with things matters. And everything counts in large amounts.
@SomeVeganCheeseIsOk
But that's not precise nor clear at all. You are mixing tech itself with I don't know what that is, some kind of preaching? It sure sounds like you found your external enemy you can pin everything on and hate together with a group. Like a mob or a cult
@SomeVeganCheeseIsOk
It's not a marketing term. It's an old term that people have been using for a while. And I don't think it's ever been used to describe a machine person that's alive. It was always used as simulated intelligence. Which LLMs are. It's a very good description.
@xvf17 @emilymbender The tools do it too and claim they are "thinking" when asking users to wait for their output.
Jun 23, 2026, 8:51 PM@emilymbender Great thread.
Jun 23, 2026, 9:22 PM@emilymbender great thread, I think at different points I've run into each of the points you laid out (especially when I was trying to be more amenable to LLM users). since, I've grown to taking a much more hard-line anti-big-tech-LLM, neutral-to-meh academic/open-model LLM, and recommending searching out all alternatives before turning to the tech as a solution.
thank you for your work in this area, as you and @alex have helped shaped my opinions/knowledge on the subject.
Jun 23, 2026, 10:02 PMi despise AI because of its energy waste, its abuse of source material it rips off without attribution, and how it concentrates power with these amoral techbros who can use it for all sorts of malicious goals
but i always wondered if AI could be a standalone thing, something you ran yourself, at home, so there is no exposure to manipulative outside agendas, if i would have the same objections. assuming sane power usage and respect for creators. and assuming complete privacy
@benroyce @emilymbender
Yes, you can use Ollama and free LLMs from hugging face.
It's slow but it stays private on your own machine. You don't even need a GPU to do it.
Jun 23, 2026, 10:32 PM@hackersquirrel @emilymbender and people don't do it because it's not as powerful? I'm certain that will change. But then the big tech offerings will be more powerful too. Bht if the private AI does enough, good enough, then I suppose we can talk about the evils of corporate AI alone, what we just call "AI" today