Should AI generated posts be banned or otherwise regulated?

@hilde45 One thing I’ll keep turning over: namely that LLM users weren’t just equivalent to the control group on condition identification -- they were measurably worse. Unless I’m confused, that finding alone seems like the sharpest challenge to the "skilled users will figure it out" interpretation, and I’m not sure the thread has fully reckoned with it. But it’s time for a walk.

We should look at the big picture—i.e., 95% accuracy by LLMs alone versus 34% when used by end users for condition identification. This suggests that AI is highly sensitive to how people ask questions and to the quality of those questions.

There’s nothing wrong with trying to rationalize why Google/web search by end users (42%) slightly outperforms LLM use by end users (34%). One possible reason could be, when performing web searches, people tend to refine their queries and compare or cross-reference multiple sources, which may improve accuracy relative to relying on a single synthesized answer from an LLM.

That said, we’re looking at results that, although statistically significant, are only marginally better (42% vs. 34%). Compared to the 95% accuracy achieved by LLMs alone, however, this represents a substantial (and disappointing) drop-off. It’s important to keep the big picture in perspective.

No.

Up until very recently I was reluctant to use AI but, after reading some AI generated responses in this forum, decided to give it a try. In Chat GPT I plugged in my rooms' asymmetrical dimensions, loudspeaker and subwoofer models and positions in the room to determine the best positions for my two subs. I was pleasantly surprised with the results. After several refinements it suggested one sub between the speakers and one about half way along (and out from) the right wall to mitigate the room modes. I am no longer a skeptic.The integration and low frequency sound/weight are far better than I had before with symmetrical sub positions. I am somewhat blown away but the sound is really good now so I guess you can teach and old dinosaur new tricks......Thanks folks!

@ghdprentice I have helped and seen many clerks and stock people go from $35K jobs doing mundane work to making well over $100K by being early adopters and then teaching and implementing new tech.

@devinplombier Employee with paycheck makes $100K a year! You don't say!! Now that's an American success story if I ever seen one. Move over, Elon.

@devinplombier  For clerks, stock workers, and people working in Mom-and-Pop stores living paycheck to paycheck, $100K nowadays is significantly higher than the average worker’s income.  Pay raise could never be able to catch up with inflation either especially over the past few years.  Look also at teachers’ wages, which are about $55K–$60K per year on average in the U.S., and around $70K–$75K in retirement.

If you don’t think it’s a big deal, do as @ghdprentice does and help out. It won’t cost you an arm or a leg.

@lanx0003 I know. But in reality, "clerks and stock people" do not go from $35K to $100K in the same job solely by virtue of adopting AI early.

If @ghdprentice saw potential in $35K clerks, mentored them through college, and motivated then to get degrees that led to $100K jobs, of course my hat's off to him. But that's a different narrative altogether, and one that has little to do with AI.

I mentored them through an implementation of enterprise software. They stepped up to the plate, became experts in the use and configuration of the software, joined the international software implementation team and then went on to either join corporate IT or software consultants. Giving folks opportunities to implement new technology can enable folks.