Reed MidekeSomewhat surprised Cohen's #ChatGPTLawyer escapade didn't result in sanctions for him or his lawyers, though they do seem avoided the sort of cover-up attempts that doomed some of the others
https://arstechnica.com/tech-policy/2024/03/michael-cohen-and-lawyer-avoid-sanctions-for-citing-fake-cases-invented-by-ai/?utm_brand=arstechnica&utm_social-type=owned&utm_source=mastodon&utm_medium=social
Epic Zitron rant "Sam Altman desperately needs you to believe that generative AI will be essential, inevitable and intractable, because if you don't, you'll suddenly realize that trillions of dollars of market capitalization and revenue are being blown on something remarkably mediocre" https://www.wheresyoured.at/peakai/
Have We Reached Peak AI?
Last week, the Wall Street Journal published a 10-minute-long interview with OpenAI CTO Mira Murati, with journalist Joanna Stern asking a series of thoughtful yet straightforward questions that Murati failed to satisfactorily answer. When asked about what data was used to train Sora, OpenAI's app for generating video with AI,
Can we fucking not? "In a 2019 War on the Rocks article, “America Needs a ‘Dead Hand’,” we proposed the development of an artificial intelligence-enabled nuclear command, control, and communications system to partially address this concern… We can only conclude that America needs a dead hand system more than ever" https://warontherocks.com/2024/03/america-needs-a-dead-hand-more-than-ever/
The authors offer a lot of vague-to-meaningless handwaving "All forms of artificial intelligence are premised on mathematical algorithms, which are defined as “a set of instructions to be followed in calculations or other operations.” Essentially, algorithms are programming that tells the model how to learn on its own"
Uh… OK?
"America is no stranger to “fail-fatal” systems either"
Uh yeah, but *some* of us poor simple minded bleeding heart peaceniks may consider "fail-fatal for the entire fucking planet" to be entirely different class of system which raises some unique concerns
"Keep in mind, where artificial intelligence tools are embedded in a specific system, each function is performed by multiple algorithms of differing design that must all agree on their assessment for the data to be transmitted forward. If there is disagreement, human interaction is required"
Well as long as long as both ChatGPT *and* Claude have to sign off on the global thermonuclear war, it's hard to see how anything could go wrong
Well as long as long as both ChatGPT *and* Claude have to sign off on the global thermonuclear war, it's hard to see how anything could go wrong
I don't think these guys have much chance of gaining traction in the US, but it would be unfortunate if other nuclear states decided they were at risk of an AI dead hand gap
Today's #AIIsGoingGreat brought to you by #NYC, who deployed spicy autocomplete to provide advice "on topics such as compliance with codes and regulations, available business incentives, and best practices to avoid violations and fines"
(spoiler: one great way to avoid violations and fines is to not get your legal advice from spicy autocomplete)
https://themarkup.org/news/2024/03/29/nycs-ai-chatbot-tells-businesses-to-break-the-law
One potentially informative thing reporters following up on that #NYC #AI #Chatbot story could do is #FOIA (or whatever the NY equivalent is) communications related to the acquisition and deployment. Who pushed for this in the first place? What did #Microsoft promise? What sort of quality / acceptance testing was done? Did anyone, anywhere along the line raise concerns that it would give out bad, potentially illegal advice?
I'd be pretty surprised if there isn't an email chain somewhere with a technical person going "WTF are you even thinking"
Bonus #AIIsGoingGreat "Your phone now needs more than 8 GB of RAM to run autocomplete" (and presumably, battery cost somewhat on a par with heavy GPU rendering) https://arstechnica.com/gadgets/2024/03/google-says-the-pixel-8-will-get-its-new-ai-model-but-ram-usage-is-a-concern/
Today's #AIIsGoingGreat (HT @pluralistic https://mastodon.social/@pluralistic@mamot.fr/112196496077034192)
Tired: Typo squatting
Wired: Hallucination squatting
https://www.theregister.com/2024/03/28/ai_bots_hallucinate_software_packages/
Seems like you could put your thumb on scale for which (non existent) libraries show up with #LLM training set poisoning attacks (previously https://mastodon.social/@reedmideke/110850376856613599)
Set up a site that, when it detects known AI scrapers, serves up code or documentation that references a non-existent library, along text associating with whatever kind of code and industry you want to target
OTOH, this would leave much more of trail than just observing bogus ones that show up naturally
In which the gang discovers Amazon Fresh "Just walk out" checkout was powered by Type II #AI https://gizmodo.com/amazon-reportedly-ditches-just-walk-out-grocery-stores-1851381116
"If you think about the major journeys within a [fast food] restaurant that can be AI-powered, we believe it’s endless"
Sir this a fucking Wendy's and people come here to buy a fucking burger, not "take major journeys" https://arstechnica.com/information-technology/2024/04/ai-hype-invades-taco-bell-and-pizza-hut/
Also uh, can't imagine anything that could possibly go wrong with this: "This enhancement would allow team members to ask the [AI chatbot] app questions like "How should I set this oven temperature?" directly instead of asking a human being"
Some scientists theorized that after over 30 years of continuous development, it was physically impossible to make Adobe Reader worse, but once again, Adobe engineers have found a way
I actually kinda wanted to see it summarize the spurious scholar (https://tylervigen.com/spurious-scholar) paper I was reading when it popped up, but… not enough to log in
Today's #AIIsGoingGreat brought to you by #Ivanti: 'Among the details is the company's promise to improve search abilities in Ivanti's security resources and documentation portal, "powered by AI," and an "Interactive Voice Response system" … also "AI-powered"'
Ah yes, hard to think of any better way to fix a pattern of catastrophic security failures than *checks notes* filtering highly technical, security critical information through a hyper-confident BS machine
Today's #AIIsGoingGreat brought to you by the artist formerly known as Twitter https://mashable.com/article/elon-musk-x-twitter-ai-chatbot-grok-fake-news-trending-explore
Here's a helpful #AI chatbot to assist you with thing that requires domain specific knowledge and has significant real-world consequences for errors… oh, by the way, you'll need to already have that same domain specific knowledge to confirm whether the answers are correct or complete BS
Who thinks this is a good idea?🤔
Texas Education Agency talks a lot about the supposed safeguards in the don't-call-it-#AI "automated scoring engine" but no mention of any testing to determine whether it is fit for purpose (they do mention training it on 3K manually scored questions). Maybe they did and it just didn't get mentioned, but seems like a very good #FOIA target
https://www.texastribune.org/2024/04/09/staar-artificial-intelligence-computer-grading-texas/
https://www.texastribune.org/2024/04/09/staar-artificial-intelligence-computer-grading-texas/
OpenAI argues that “factual accuracy in large language models remains an area of active research”
…in the sense that Bigfoot and Nessie remain areas of active research?
https://noyb.eu/en/chatgpt-provides-false-information-about-people-and-openai-cant-correct-it
A+ BLUF from @benjedwards: "Air-gapping GPT-4 model on secure network won't prevent it from potentially making things up"
https://arstechnica.com/information-technology/2024/05/microsoft-launches-ai-chatbot-for-spies/
Oh hey, remember #AdVon, the definitely-not-an-ai-company caught publishing #AI dreck in Sports Illustrated? (previously https://mastodon.social/@reedmideke/111486230567895424)
Futurism has another update, and it's a doozy
https://futurism.com/advon-ai-content
Futurism has another update, and it's a doozy
https://futurism.com/advon-ai-content
Google+ comparison is very apt, but also that opening example really hits the problem I've been yelling about since the #LLM hype cycle started: The fundamental mismatch between a system that randomly makes shit up and the uses it's being hyped for https://www.computerworld.com/article/2117752/google-gemini-ai.html
This, right here: "Erm, right. So you can rely on these systems for information - but then you need to go search somewhere else and see if they’re making something up? In that case, wouldn’t it be faster and more effective to, I don’t know, simply look it up yourself in the first place?"
Google's current #AIIsGoingGreat moment really checks all the bad #AI boxes. Starting with the dismissive "examples we've seen are generally very uncommon queries and aren’t representative of most people’s experiences" - Sure *sometimes* the answers are complete BS and possibly dangerous, but what about the times they aren't? Checkmate, Luddites!
And as always, they insist they are fixing it: "We conducted extensive testing before launching this new experience and will use these isolated examples as we continue to refine our systems overall" - with *zero* indication they have a technical or even theoretical path to solving the general problem that #LLMs don't have any concept of truth
And then, the whole thing is made worse by positioning it as a replacement for search, in the top spot with google branding. The "eat rocks" article ranks high in the regular organic search results the same query, but users have a lot more clues that it was a joke
Why am I so sure #AI companies have no serious technical or theoretical solution to the underlying problem that #LLMs have no concept of truth? The fact their approach so far is manually band-aiding results that go viral or put them in legal jeopardy is a pretty big hint! https://www.theverge.com/2024/5/24/24164119/google-ai-overview-mistakes-search-race-openai
👉 "Gary Marcus, an AI expert and an emeritus professor of neural science at New York University, told The Verge that a lot of AI companies are “selling dreams” that this tech will go from 80 percent correct to 100 percent. Achieving the initial 80 percent is relatively straightforward since it involves approximating a large amount of human data, Marcus said, but the final 20 percent is extremely challenging. In fact, Marcus thinks that last 20 percent might be the hardest thing of all"
What they're doing now seems like selling a calculator, and when a screenshot of it saying 2+2=5 goes viral on social media, they add a statement like "if x=2 and y=2 return 4" at the top of the program and say "see, we fixed it!"
Straight from Google CEO Sundar Pichai's mouth: 'these "hallucinations" are an "inherent feature" of AI large language models (LLM), which is what drives AI Overviews, and this feature "is still an unsolved problem"'
but they're gonna keep band-aiding until it's good, promise! ""Are we making progress? Yes, we are … We have definitely made progress when we look at metrics on factuality year on year. We are all making it better, but it’s not solved""
Just occurred to me Mitchell and Webb predicted our current pizza-gluing, gasoline spaghetti #AIIsGoingGreat moment 16 years ago https://www.youtube.com/watch?v=B_m17HK97M8
Mitchell & Webb: Cheesoid
Today's #AIIsGoingGreat - Meta's chatbot helpfully "confirms" a scammers number is a legitimate facebook support number
(of course, #LLMs just predict likely sequences of text, and for a question like this, "yes" is one of the high probability answers. There's no indication any of the companies hyping LLMs as a source of information have any serious solution for this kind of thing)
https://www.cbc.ca/news/canada/manitoba/facebook-customer-support-scam-1.7219581
Kyle Orland hammers on my off-repeated complaint (https://mastodon.social/@reedmideke/110063208987793683) that filtering your information through an #LLM *removes* useful context: "When Google's AI Overview synthesizes a new summary of the web's top results, on the other hand, all of this personal reliability and relevance context is lost. The Reddit troll gets mixed in with the serious cooking expert"
https://arstechnica.com/ai/2024/06/googles-ai-overviews-misunderstand-why-people-use-google/
On the same note, today's #AIIsGoingGreat courtesy of @ppossej, observing Microsoft copilot helpfully "summarizing" a phishing email. Even leaving aside obvious problem here, what exactly is supposed to be the value having an already short email filtered through spicy autocomplete? https://mastodon.social/@[email protected]ocial/112555512126646188
I initially dismissed today's #AIIsGoingGreat (HT @zhuowei) as a joke, but no* : "aiBIOS leverages an LLM to integrate AI capabilities into Insyde Software’s flagship firmware solution, InsydeH2O® UEFI BIOS. It provides the ability to interpret the PC user’s request, analyze their specific hardware, and parse through the LLM’s extensive knowledge base of BIOS and computer terminology to make the appropriate changes to the BIOS Setup"
* not an intentional one, anyway
https://www.insyde.com/press_news/press-releases/insyde%C2%AE-software-brings-higher-intelligence-pcs-aibios%E2%84%A2-technology-be
* not an intentional one, anyway
https://www.insyde.com/press_news/press-releases/insyde%C2%AE-software-brings-higher-intelligence-pcs-aibios%E2%84%A2-technology-be
Today's #AIIsGoingGreat features Zoom CEO Eric Yuan blazed out of his mind on his own supply: "Today for this session, ideally, I do not need to join. I can send a digital version of myself to join so I can go to the beach. Or I do not need to check my emails; the digital version of myself can read most of the emails. Maybe one or two emails will tell me, “Eric, it’s hard for the digital version to reply. Can you do that?”"
"I truly hate reading email every morning, and ideally, my AI version for myself reads most of the emails. We are not there yet"
OK, points for recognizing we're "not there yet", in roughly the same sense the legend of Icarus foresaw intercontinental jet travel but was "not there yet"
Actually interesting thing in that Eric Yuan interview "every day, I personally spend a lot of time on talking with our customer’s prospects. Guess what? First question they all always ask me now is “What’s your AI strategy? What do you do to embrace AI?…”"
- even if exaggerated, seems like a good indicator of how deeply C-suite types have bought into the hype, which in turn means they all need an "AI strategy" no matter how ludicrous
- even if exaggerated, seems like a good indicator of how deeply C-suite types have bought into the hype, which in turn means they all need an "AI strategy" no matter how ludicrous
and the thing is, in terms of their personal incentives, they're probably not wrong. The analysts and shareholders and trade press want the new shiny thing, and if their current business gets caught on the wrong side of the bubble, they keep whatever bonuses they got in the interim and it probably won't hurt their future career prospects much
Bonus #AIIsGoingGreat from NYT with a deep look at (now defunct) skeevy news out BNN Breaking: "employees were asked to put articles from other news sites into the [#LLM] tool so that it could paraphrase them, and then to manually “validate” the results by checking them for errors… Employees did not want their bylines on stories generated purely by A.I., but Mr. Chahal insisted on this. Soon, the tool randomly assigned their names to stories"
https://www.nytimes.com/2024/06/06/technology/bnn-breaking-ai-generated-news.html?u2g=i&unlocked_article_code=1.x00.zn0r.s2tFDDFWR0fo&smid=url-share
#GiftArticle #GiftLink #BNN
https://www.nytimes.com/2024/06/06/technology/bnn-breaking-ai-generated-news.html?u2g=i&unlocked_article_code=1.x00.zn0r.s2tFDDFWR0fo&smid=url-share
#GiftArticle #GiftLink #BNN
#BNN founder Gurbaksh Chahal seems to be an all-around charming fellow "In 2013, he attacked his girlfriend at the time, and was accused of hitting and kicking her more than 100 times, generating significant media attention because it was recorded by a video camera he had installed in the bedroom … After an arrest involving another domestic violence incident with a different partner in 2016, he served six months in jail"
Some might argue that making the #AI acronym do double duty with "Apple Intelligence" is a recipe for confusion, but after all the hype I find it refreshingly honest to position the product as "about as smart as a piece of fruit"
That "#ChatGPT is bullshit" paper I boosted earlier does a nice job of laying out why the "hallucination" terminology is harmful "what occurs in the case of an #LLM delivering false utterances is not an unusual or deviant form of the process it usually goes through… The very same process occurs when its outputs happen to be true"
https://link.springer.com/article/10.1007/s10676-024-09775-5
ChatGPT is bullshit - Ethics and Information Technology
Recently, there has been considerable interest in large language models: machine learning systems which produce human-like text and dialogue. Applications of these systems have been plagued by persistent inaccuracies in their output; these are often called “AI hallucinations”. We argue that these falsehoods, and the overall activity of large language models, is better understood as bullshit in the sense explored by Frankfurt (On Bullshit, Princeton, 2005): the models are in an important way indifferent to the truth of their outputs. We distinguish two ways in which the models can be said to be bullshitters, and argue that they clearly meet at least one of these definitions. We further argue that describing AI misrepresentations as bullshit is both a more useful and more accurate way of predicting and discussing the behaviour of these systems.
The authors rightly object to "confabulation" for similar reasons "This term also suggests that there is something exceptional occurring when the LLM makes a false utterance, i.e., that in these occasions - and only these occasions - it “fills in” a gap in memory with something false. This too is misleading. Even when the ChatGPT does give us correct answers, its process is one of predicting the next token"
They are far from the first to make the connection between #LLMs and Frankfurtian bullshit, but humor aside, they do make a compelling case that the terminology matters https://link.springer.com/article/10.1007/s10676-024-09775-5#Sec12
ChatGPT is bullshit - Ethics and Information Technology
Recently, there has been considerable interest in large language models: machine learning systems which produce human-like text and dialogue. Applications of these systems have been plagued by persistent inaccuracies in their output; these are often called “AI hallucinations”. We argue that these falsehoods, and the overall activity of large language models, is better understood as bullshit in the sense explored by Frankfurt (On Bullshit, Princeton, 2005): the models are in an important way indifferent to the truth of their outputs. We distinguish two ways in which the models can be said to be bullshitters, and argue that they clearly meet at least one of these definitions. We further argue that describing AI misrepresentations as bullshit is both a more useful and more accurate way of predicting and discussing the behaviour of these systems.
"Calling their mistakes ‘hallucinations’ isn’t harmless: it lends itself to the confusion that the machines are in some way misperceiving but are nonetheless trying to convey something that they believe or have perceived. This, as we’ve argued, is the wrong metaphor. The machines are not trying to communicate something they believe or perceive. Their inaccuracy is not due to misperception or hallucination … they are not trying to convey information at all. They are bullshitting"
Today's #AIIsGoingGreat:
1) Spammers flood web with content farms using #LLMs (based on tech pioneered by Google)
2) Google (reportedly) de-lists sites for having too much spammy LLM content
3) People paying freelancers to write real content run it through unreliable "#AI detectors" to avoid #2
4) Human writers get fired for false positives in #3
https://gizmodo.com/ai-detectors-inaccurate-freelance-writers-fired-1851529820
Much like the #AI industry, the AI detector industry tries to have it both ways, hyping the purported value while covering their ass with disclaimers:
Jonathan Gillham, CEO of Originality.AI says "we advise against the tool being used within academia, and strongly recommend against being used for disciplinary action" while their marketing materials claim the product is “essential” in the classroom https://gizmodo.com/ai-detectors-inaccurate-freelance-writers-fired-1851529820
Jonathan Gillham, CEO of Originality.AI says "we advise against the tool being used within academia, and strongly recommend against being used for disciplinary action" while their marketing materials claim the product is “essential” in the classroom https://gizmodo.com/ai-detectors-inaccurate-freelance-writers-fired-1851529820
"Seriously, what’s the business model here? To offer ChatGPT and its entire featureset to people, for free, inside of Apple devices, in the hopes that OpenAI can upsell them?" - Hmm, an alternative is OpenAI believes it will be so popular/essential that they can upsell *Apple* when the contract renewal or V2 comes around. Burning VC billions to corner the market and then jacking up the price is a time-honored Valley tradition
Let Tim Cook
Last week, Apple announced “Apple Intelligence,” a suite of features coming to iOS 18 (the next version of the iPhone’s software) in a presentation that FastCompany called “uninspired,” Futurism called “boring,” and Axios claimed “failed to excite investors.” The presentation, given at Apple’s Worldwide Developers conference (usually referred
I very much doubt that will happen, but OpenAI are deep enough into their "AGI is just around the corner" kool-aid they might well believe it
In today's #AIIsGoingGreat, we learn that "This technology is proven to have some of the most comprehensive capabilities in the industry, fast and accurate in some of the most demanding conditions" is IBM marketing-speak for "not able to hold down a job at McDonalds" https://www.bbc.com/news/articles/c722gne7qngo
Another great example how #LMM #AI produces extremely confident BS when presented with something (in this case, a rare name) not represented in the training data https://kansasreflector.com/2024/06/22/artificial-intelligence-has-spread-lies-about-my-good-name-and-im-here-to-settle-the-score/
In today's #AIIsGoingGreat: Adobe apparently adds the AI mark of shame to images that have been touched by its "AI" based tools, no matter how minor the effect. And then Meta uses that mark to (sometimes?) flag the image as "Made with AI"
Arguably correct, but also almost entirely useless… it's not like an image is more or less fake if you generative fill to cover up a spot rather than the regular old clone tool or airbrush
https://www.theverge.com/2024/6/24/24184795/meta-instagram-incorrect-made-by-ai-photo-labels
But where do you draw the line, and how to capture that in metadata?
Today's #AIIsGoingGreat features @MozillaAI "To avoid confirmation bias and subjective interpretation, we decided to leverage language models for a more objective analysis of the data"
Aside from the obvious [citation f-ing needed] on LLMs providing "more objective analysis" what exactly was the input? Oh … "After each conversation, we wrote up summary notes" … definitely no room for bias and subjective interpretation to be introduced there
They go on provide the output of three models, which seem fairly generic and bland with the occasional grammatical oddity, but without the input, we have no way to judge how accurate or insightful they were. We just get @MozillaAI's subjective "They identified the majority of trends and patterns among the 35 organizations we studied… This exercise showcased how well local language models can extract valuable insights from large text datasets"
They also give us this, which, I dunno, all seem pretty obvious and not at all surprising?
Michael Gisiger 
@reedmideke Yes—and no. Yes, 'hallucination' is a misleading term. But 'bullshitting' is also misleading, because it implies a kind of volition that LLMs definitely don't have. All they do is apply statistics. Both terms are a fatal consequence of our tendency to anthropomorphise.
Stuck HereWas coming to say this. You have to be a thinking entity to deceive, hallucinate, or bullshit. LLM as you say is just fancy statistics and a whirring of algorithms to regurgitate information.
It's useful when trained on specific, time consuming tasks like reading medical images or pulling together patterns in information.
But don't go asking it to teach me something I can read for myself. It doesn't have the smarts to know when a reddit user made a joke or is racist.
@MyWoolyMastadon @reedmideke Exactly, you can label the output as bullshit (which it often is), but you can't say, a LLM is bullshitting, because it lacks the necessary agency to do so.
@gisiger @MyWoolyMastadon Maybe you should read the paper ¯\_(ツ)_/¯ (I agree "bullshit" in the colloquial sense is a loaded term, but they do have an extensive discussion of this very topic) https://link.springer.com/article/10.1007/s10676-024-09775-5#Sec12
ChatGPT is bullshit - Ethics and Information Technology
Recently, there has been considerable interest in large language models: machine learning systems which produce human-like text and dialogue. Applications of these systems have been plagued by persistent inaccuracies in their output; these are often called “AI hallucinations”. We argue that these falsehoods, and the overall activity of large language models, is better understood as bullshit in the sense explored by Frankfurt (On Bullshit, Princeton, 2005): the models are in an important way indifferent to the truth of their outputs. We distinguish two ways in which the models can be said to be bullshitters, and argue that they clearly meet at least one of these definitions. We further argue that describing AI misrepresentations as bullshit is both a more useful and more accurate way of predicting and discussing the behaviour of these systems.
@reedmideke @MyWoolyMastadon Well, I did read it, that's exactly why I wrote my comment. I don't think, that the paper's position to "adopt the intentional stance" is sound at all. Again, you can call the output bullshit, you can call LLMs "bullshit machines", you can even call the people behind it "hard bullshitters". But not the thing itself. Machines can't be--and possibly will never be--moral agents. That is, to my humble knowledge, the consensus.
emmatonkinThe LLM itself is just applying stats, as you say, but post designer and marketer, service providers frankly appear to be trying pretty hard to persuade users that LLM-powered services are a whole lot more than they actually are, sounding-like-ScarJo and all. Though the volition is that of the engineer, not the LLM, it seems fair to say that in aggregate, the service (and really, the provider) is bullshitting the user.
Antonio Patriarca@reedmideke I somewhat agree, but I still like the terminology as it makes for the perfect response to a lot of AI bullshit: "Would you give that task to someone under acid? Because your AI will hallucinate the same."
THIS ACCOUNT HAS MOVED@reedmideke exactly this. Wrong is wrong.
Murray@reedmideke As an Australian and somewhat of an amateur bullshitter myself I take umbrage at this characterisation.
colourlesspony@reedmideke I like "Confidently wrong".
Medea Vanamonde🏳️⚧️ ♀@reedmideke Racters gonna Racter
K. N. Brindle (they/them)@reedmideke Even "bullshitting" implies intent. There's no intent there.
I prefer the term “spewing”
Michael@reedmideke Agreed. I've felt for a long time that anthropomorphizing these machines is bad.
WikiParty@reedmideke Even saying they are bullshitting implies sentience. It's all *maths*, people. Arranging tokens in statistically optimal ways.
Katharsisdrill
Gustavo@reedmideke That also applies to non-artificial brains, no? I hate when my brain hallucinates people out of plain air... Better, bullshits them. Or magic illusions.
@qgustavor Huh? A main point of that quote and the paper is that it doesn't: In humans, we generally define hallucinations as a failure of normal perception, or at least a distinct, exceptional state. Whereas an LLM "hallucination" is just completely normal operation, stringing together words that probabilistically sound good together without regard to truth https://link.springer.com/article/10.1007/s10676-024-09775-5#Sec12
ChatGPT is bullshit - Ethics and Information Technology
Recently, there has been considerable interest in large language models: machine learning systems which produce human-like text and dialogue. Applications of these systems have been plagued by persistent inaccuracies in their output; these are often called “AI hallucinations”. We argue that these falsehoods, and the overall activity of large language models, is better understood as bullshit in the sense explored by Frankfurt (On Bullshit, Princeton, 2005): the models are in an important way indifferent to the truth of their outputs. We distinguish two ways in which the models can be said to be bullshitters, and argue that they clearly meet at least one of these definitions. We further argue that describing AI misrepresentations as bullshit is both a more useful and more accurate way of predicting and discussing the behaviour of these systems.
@reedmideke At this point we are discussing linguistics and how tables don't have feet but it have supports yet some humans prefer to use feet because they like to antromorphise things, from Pablo the rock to the greatest bullshit AI that ever existed.
J. Blake@reedmideke ‘Hallucinations’ is simply marketing. It seems to have worked.
Tanith the Gay@reedmideke 're hallucinations "unusual or deviant forms" of normal perception tho?
Ben Brockert@reedmideke Seems like a safe bet that they won’t include biology AI like a Drosophila fly neural network into the Apple program, because everyone knows fruit flies like a banana.