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.
So, if you structure your data in such a way that using AI is completely unneeded, it’s the perfect system to use AI on.
Wait, this is just a wiki with extra steps!
and extra bills
I wonder why no business types/economists (*) types don’t just stand up and go ‘this is all a scam’. It started with just needing a website (with some added idea that it might reduce advertisement costs, replace some secretaries who used to handle information requests). Fine, you can buy those and maintenance and running costs is cheap. And then you need an ecommerce site, so you need a team of devs, admins, security people, but it brings in some revenue. But then every five years there is something else, and then you are running a huge team of STEM people who all are working on the pivot to Apps/AI/Quantum resistant whatever/NFTs/Cryptocurrencies/GDPR/continuous development/checking if none of the daily updates of all your huge dependencies break something/microservices/huge cloud bills/training of these tech people/moderation of your sites for pedophiles, racists, other extremists, and random satanic scare style worries. Bottom line somebody must have discovered something like 'wait why are we spending this much money on all this crap? We sell pet food for fucks sake, Ecommerce didn’t reduce our costs as now we need to hire an maintain delivery people and cars.
*: I know why, because their jobs are also in on the scam.