Architeuthis

AI Work Assistants Need a Lot of Handholding

Getting full value out of AI workplace assistants is turning out to require a heavy lift from enterprises. ‘It has been more work than anticipated,’ says one CIO.

aka we are currently in the process of realizing we are paying for the privilege of being the first to test an incomplete product.

Mandell said if she asks a question related to 2024 data, the AI tool might deliver an answer based on 2023 data. At Cargill, an AI tool failed to correctly answer a straightforward question about who is on the company’s executive team, the agricultural giant said. At Eli Lilly, a tool gave incorrect answers to questions about expense policies, said Diogo Rau, the pharmaceutical firm’s chief information and digital officer.

I mean, imagine all the non-obvious stuff it must be getting wrong at the same time.

He said the company is regularly updating and refining its data to ensure accurate results from AI tools accessing it. That process includes the organization’s data engineers validating and cleaning up incoming data, and curating it into a “golden record,” with no contradictory or duplicate information.

Please stop feeding the thing too much information, you're making it confused.

Some of the challenges with Copilot are related to the complicated art of prompting, Spataro said. Users might not understand how much context they actually need to give Copilot to get the right answer, he said, but he added that Copilot itself could also get better at asking for more context when it needs it.

Yeah, exactly like all the tech demos showed -- wait a minute!

[Google Cloud Chief Evangelist Richard Seroter said] “If you don’t have your data house in order, AI is going to be less valuable than it would be if it was,” he said. “You can’t just buy six units of AI and then magically change your business.”

Nevermind that that's exactly how we've been marketing it.

Oh well, I guess you'll just have to wait for chatgpt-6.66 that will surely fix everything, while voiced by charlize theron's non-union equivalent.

An AI company has been generating porn with gamers' idle GPU time in exchange for Fortnite skins and Roblox gift cards

"some workloads may generate images, text or video of a mature nature", and that any adult content generated is wiped from a users system as soon as the workload is completed.

However, one of Salad's clients is CivitAi, a platform for sharing AI generated images which has previously been investigated by 404 media. It found that the service hosts image generating AI models of specific people, whose image can then be combined with pornographic AI models to generate non-consensual sexual images.

Investigation link: https://www.404media.co/inside-the-ai-porn-marketplace-where-everything-and-everyone-is-for-sale/

For thursday's sentencing the us government indicated they would be happy with a 40-50 prison sentence, and in the list of reasons they cite there's this gem:

4. Bankman-Fried's effective altruism and own statements about risk suggest he would be likely to commit another fraud if he determined it had high enough "expected value". They point to Caroline Ellison's testimony in which she said that Bankman-Fried had expressed to her that he would "be happy to flip a coin, if it came up tails and the world was destroyed, as long as if it came up heads the world would be like more than twice as good". They also point to Bankman-Fried's "own 'calculations'" described in his sentencing memo, in which he says his life now has negative expected value. "Such a calculus will inevitably lead him to trying again," they write.

Turns out making it a point of pride that you have the morality of an anime villain does not endear you to prosecutors, who knew.

Bonus: SBF's lawyers' list of assertions for asking for a shorter sentence includes this hilarious bit reasoning:

They argue that Bankman-Fried would not reoffend, for reasons including that "he would sooner suffer than bring disrepute to any philanthropic movement."

rootclaim appears to be yet another group of people who, having stumbled upon the idea of the Bayes rule as a good enough alternative to critical thinking, decided to try their luck in becoming a Serious and Important Arbiter of Truth in a Post-Mainstream-Journalism World.

This includes a randiesque challenge that they'll take a $100K bet that you can't prove them wrong on a select group of topics they've done deep dives on, like if the 2020 election was stolen (91% nay) or if covid was man-made and leaked from a lab (89% yay).

Also their methodology yields results like 95% certainty on Usain Bolt never having used PEDs, so it's not entirely surprising that the first person to take their challenge appears to have wiped the floor with them.

Don't worry though, they have taken the results of the debate to heart and according to their postmortem blogpost they learned many important lessons, like how they need to (checks notes) gameplan against the rules of the debate better? What a way to spend 100K... Maybe once you've reached a conclusion using the Sacred Method changing your mind becomes difficult.

I've included the novel-length judges opinions in the links below, where a cursory look indicates they are notably less charitable towards rootclaim's views than their postmortem indicates, pointing at stuff like logical inconsistencies and the inclusion of data that on closer look appear basically irrelevant to the thing they are trying to model probabilities for.

There's also like 18 hours of video of the debate if anyone wants to really get into it, but I'll tap out here.

ssc reddit thread

quantian's short writeup on the birdsite, will post screens in comments

pdf of judge's opinion that isn't quite book length, 27 pages, judge is a microbiologist and immunologist PhD

pdf of other judge's opinion that's 87 pages, judge is an applied mathematician PhD with a background in mathematical virology -- despite the length this is better organized and generally way more readable, if you can spare the time.

rootclaim's post mortem blogpost, includes more links to debate material and judge's opinions.

edit: added additional details to the pdf descriptions.

edited to add tl;dr: Siskind seems ticked off because recent papers on the genetics of schizophrenia are increasingly pointing out that at current miniscule levels of prevalence, even with the commonly accepted 80% heritability, actually developing the disorder is all but impossible unless at least some of the environmental factors are also in play. This is understandably very worrisome, since it indicates that even high heritability issues might be solvable without immediately employing eugenics.

Also notable because I don't think it's very often that eugenics grievances breach the surface in such an obvious way in a public siskind post, including the claim that the whole thing is just HBD denialists spreading FUD:

People really hate the finding that most diseases are substantially (often primarily) genetic. There’s a whole toolbox that people in denial about this use to sow doubt. Usually it involves misunderstanding polygenicity/omnigenicity, or confusing GWAS’ current inability to detect a gene with the gene not existing. I hope most people are already wise to these tactics.

... while at the same time not really worth worrying about so we should be concentrating on unnamed alleged mid term risks.

EY tweets are probably the lowest effort sneerclub content possible but the birdsite threw this to my face this morning so it's only fair you suffer too. Transcript follows:

Andrew Ng wrote:

In AI, the ratio of attention on hypothetical, future, forms of harm to actual, current, realized forms of harm seems out of whack.

Many of the hypothetical forms of harm, like AI "taking over", are based on highly questionable hypotheses about what technology that does not currently exist might do.

Every field should examine both future and current problems. But is there any other engineering discipline where this much attention is on hypothetical problems rather than actual problems?

EY replied:

I think when the near-term harm is massive numbers of young men and women dropping out of the human dating market, and the mid-term harm is the utter extermination of humanity, it makes sense to focus on policies motivated by preventing mid-term harm, if there's even a trade-off.

Sam Altman, the recently fired (and rehired) chief executive of Open AI, was asked earlier this year by his fellow tech billionaire Patrick Collison what he thought of the risks of synthetic biology. ‘I would like to not have another synthetic pathogen cause a global pandemic. I think we can all agree that wasn’t a great experience,’ he replied. ‘Wasn’t that bad compared to what it could have been, but I’m surprised there has not been more global coordination and I think we should have more of that.’

original is here, but you aren't missing any context, that's the twit.

I could go on and on about the failings of Shakespear... but really I shouldn't need to: the Bayesian priors are pretty damning. About half the people born since 1600 have been born in the past 100 years, but it gets much worse that that. When Shakespear wrote almost all Europeans were busy farming, and very few people attended university; few people were even literate -- probably as low as ten million people. By contrast there are now upwards of a billion literate people in the Western sphere. What are the odds that the greatest writer would have been born in 1564? The Bayesian priors aren't very favorable.

edited to add this seems to be an excerpt from the fawning book the big short/moneyball guy wrote about him that was recently released.

Transcription:

Thinking about that guy who wants a global suprasovereign execution squad with authority to disable the math of encryption and bunker buster my gaming computer if they detect it has too many transistors because BonziBuddy might get smart enough to order custom RNA viruses online.