Microsoft research: Use AI chatbots and turn yourself into a dumbass
You might think using a chatbot to think for you just makes you dumber — or that chatbots are especially favored by people who never liked thinking in the first place. It turns out the bot users re…
While browsing the references of the paper, I found such a perfect evisceration of GenAI.
We have confused what we can write down with what we usefully know and compounded the error by supposing that because computers can help us write down more they can obviously help us know more.
The marks are on the knowledge worker - Kidd, Alison
That's from 1994 folks, they were talking about the wonder of relational databases.
Big Data was never exactly my fave, but I still liked them better than Genai after he went solo. Some people just never learn that it's never about the size, but how you use it.
Whoops, I dropped my monster Hadoop that I use for my magnum datalake.
Qualitatively, GenAI shifts the nature of critical thinking toward information verification, response integration, and task stewardship.
Information verification is super important and probably just as important as raw critical thinking. However, when a person is stuck only validating shit output from genai, I could see that as a negative.
and as the paper details, they don't do that either
I get forced to do more critical thinking than I want to faster than I normally would, since im getting the fast responses, its tiring, if I do something myself I go at my own pace, with ai theres always more stuff to check and do and think about, so I burn out
It's not stupid people, just people rightfully not giving a fuck IMO.
read the paper, they're very stupid also
It was already known that “users with access to GenAI tools produce a less diverse set of outcomes for the same task.”
Why is this portrayed as a bad thing? Correct answers are correct answers. The only thing LLMs typically are bad at, are things that are seldom discussed or have some ambiguity behind them. So long as users understand the limitations of AI and understand when and where to trust them - then why is their diversity in output a bad thing?
Regularly we seek uniformity in output in order to better handle its output in tasks further down. I don't see this as a bad thing at all.
The only thing LLMs typically are bad at, are things that are seldom discussed or have some ambiguity behind them.
yeah no wonder you're a racist cunt
why don't you look at the paper then and find out
Correct answers are correct answers.
you should be so lucky
So long as users understand the limitations of AI
this isn't those people
others have said the bits that matter already, but for my part: what in the fuck kind of post is this
Correct answers are correct answers. The only thing LLMs typically are bad at, are things that are seldom discussed or have some ambiguity behind them.
Lol what, how many questions you ask in your life are entirely unambiguous and devoid of nuance? That sounds like a you issue.
