- cross-posted to:
- futurology@futurology.today
- cross-posted to:
- futurology@futurology.today
Trust in AI technology and the companies that develop it is dropping, in both the U.S. and around the world, according to new data from Edelman shared first with Axios.
Why it matters: The move comes as regulators around the world are deciding what rules should apply to the fast-growing industry. “Trust is the currency of the AI era, yet, as it stands, our innovation account is dangerously overdrawn,” Edelman global technology chair Justin Westcott told Axios in an email. “Companies must move beyond the mere mechanics of AI to address its true cost and value — the ‘why’ and ‘for whom.’”
The current LLM version of AI is useful in some niche industries where finding specific patterns is useful but how it’s currently popularised is the exact opposite of where it’s useful. A very obvious example is how it’s accelerating search engines becoming useless, it’s already hard to find accurate info due the overwhelming amount of AI generated articles with false info.
Also how is it a good thing that most energy will go to AI?
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LLMs should absolutely not be used for things like customer support, that’s the easiest way to give customers wrong info and aggregate them. For reviewing documents LLMs have been abysmally bad.
For gammer it can be useful but what it actually is best for is for example biochemistry for things like molecular analysis and creating protein structures.
I work in an office job that has tried to incorporate AI but so far it has been a miserable failure except for analysing trends in statistics.
I agree about customer support, but in the end it’s going to come down to number of cases like this, how much they cost, versus the cost of a room of paid employees answering them.
It’s going to take actual laws forbidding it to make them stop.
Oh, yea, of course companies will take advantage of this to just replace a ton of people with a zero cost alternative. I’m just saying that’s not where it should be used as it’s terrible at those tasks.
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