Everything I read was well worded and well reasoned. However, it seems like either my ADD got the better of me, or that was the article that has no end. I didn't really realize before that my attention has a word count, but I now know that it is less than this article.
I just hired an employee who managed things as I was on a leave of absence and things went fine without me. Getting a little pushback from MY boss now because you know, this cheaper employee just did my job.
Of course, he did it for a portion of the year after I managed to complete 3 major projects early so he didn't have to deal with them and I left a month-by-month explanation of how to do everything he had to do. And the one problem that popped up went unresolved until I returned.
That is basically the situation with AI too. You still need someone knowledgeable in the loop to describe the things it needs to do, and handle exceptions.
"You're 100% right, you should promote me so I can train more people to be able to run things. Things falling apart whenever someone goes away is a key sign of a bad leader, not a good one. I think I've demonstrated that I've managed this department into where it can function smoothly without me needing to put full time into it and I'd do well with an opportunity to move some other things in the company forward."
"Hey, unrelated question, what's your boss's contact info?"
This is going to be like the self checkout lanes at the store but for creative jobs.
At the end of the day, a company will be able to produce the same output with fewer people. Some stuff will be of lower quality, just like sometimes people spend time on Lemmy and then phone in some crappy work.
This has been my general worry: the tech is not good enough, but it looks convincing to people with no time. People don’t understand you need at least an expert to process the output, and likely a pretty smart person for the inputs. It’s “trust but verify”, like working with a really smart parrot.
Loads of good points in that video, thanks for posting. The only argument I don't really agree with is about bias. She's implying here that a human decision maker would be less biased than the AI model. I'm not convinced by that because the training data is just a statistical record of human bias. So as long as the training data is well selected for your problem, it should be a good predictior for the likelihood of bias in your human decision maker.
I think with a human operator, we can be proactive. A person can be informed of bias, learn to recognize it, and even attempt to compensate for their own.
An AI model is working off of aggregate past data that we already know is biased. There is currently no proactive anti bias training that can be done to a AI model without massively altering the dataset, which, at some level of alteration, loses its value as true to life data.
Secondly, AI is a black box. we can’t see inner the workings of the model and determine what types of associations it is making to come to its result. So we don’t even know what part of the dataset would need to be altered to address the bias.
Lastly, the default assumption by end users will be, unless there are glaring defects, that any individual result is correct and unbiased, because “AI was made by smart people and data, and data doesn’t lie.” And because interrogating and validating the result defeats the whole purpose of using AI to cut out those steps of the process.
Don't get this mistaken with the fact that a lot of people know their job is bullshit. People like to sit there thinking 'an AI can't take my job' while at the same time thinking 'a monkey can do this job it's such a waste of time'
they've already trained on stack overflow, if you want an AI that recommends a complete change of technology stack in preference to solving the problem at hand
No kidding huh. I'm glad we're finally having the discussion about AI and what that means for employment and things like UBI, but this is far from actual AI.