People will clamor for LLMs that tell them what they want to hear, and companies will happily oblige. The post-truth society is about to shift into overdrive.
On other hand at same time they might not want to me moralized to like told that they should save more money, spend less or go on diet...
AI providing incorrect information in many cases when dealing with regulations, law and so on can have significant real world impact. And such impact is unacceptable. For example you cannot have tax authority or government chatbot be wrong about some regulation or tax law.
If you call the government tax hotline and ask a question not written under the prepared questions list, what would you expect would happen? The call center service personell is certainly not expert on tax laws. You would treat it suspiciously.
If LLMs can beat humans on the error rate, they would be of a great service.
LLMs are not fail-proof machines, they are intelligent models that can make mistakes just like us. One difference is that they do not get tired, they do not have an ego, they happily provide reasonings for all their work so that it can be checked by another intelligence (be it human or LLM).
Have we tried to establish a counsel of several LLMs to check answers for accuracy? That is what we do as humans in important decisions. I am confident that different models can spot hallucinations in one another.
1) Yes. MANY of these implementations are better than humans. Heck, they can be better at soft skills than humans.
2) How do you detect errors? What do you do when you give a user terrible information (Convincingly)
2.2) What do you do now, with your error rate, when your rate of creating errors has gone up since you no longer have to wait for a human to be free to handle a call?
You want the error rate, because you want to eventually figure out how much you have to spend on clean up.
I agree that it would be better if the LLMs showed you stats on utilization and tokens and also an estimated error rate based on these.
There are many more who start out with “this is going to replace X”, where X is analysts, doctors, agents, quality teams, teachers, HR teams etc.
Just like the invention of computers reduced the need for human computers who calculated numbers by hand or mechanical calculators or automatic switching lines reduced the need for telephone operators or computers&printers reduced the need for copywriting secretaries, our professions will progress.
We will be able to do more with less cost, so we will produce more.
Your argument is essentially that the market will adapt, and to this I have made no comment, or concerned myself to feel joy or fear. I am unsure what this point is addressing.
Yes we will have greater productivity - absolutely a good thing. The issue is how that surplus will be captured. Automation and oursourcing made the world as a whole better off, however the loss of factory foreman roles was different from the loss of horse and buggy roles.
And generally, people will tell me, "I'm not sure" or "I don't know". They won't just start wildly making things up but stating them in a way that sounds plausible.
- "Dad, is that mushroom safe to eat?"
- "Hmm, I'm not sure, but let's stay safe and not eat anything we aren't certain about."
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- "LLM, is that mushroom safe to eat?"
- "Yes, that is the <wrong type of mushroom>, go right ahead!"
LLMs don't have common sense and they're never going to get it. Thus, their output cannot ever be trusted.
It seems like the most successful AI business will be one in which the model learns about you from your online habits and presence before presenting answers.
I don’t think defeatism is helpful (or correct).