alt Hacker NewsThe argument is dialectical. In other words both sides are right.
There is a really important question that is been lost between the anti and pro AI camps which is really answering what AI is good at and what AI is bad at, and what is the root cause of the weaknesses. Is it intrinsic to the models that LLM's use, or the way thy have been trained. In this knowledge is where the gold mine is for the next start up.
For example AI is very good at answering well defined questions, but suffers from premature closure. It will not know if it has all the information to answer the question. So whilst AI will score better than a doctor or a lawyer on a domain question it will not necessarily gather all the evidence needed to answer the question properly. Knowing this whilst using a LLM is a super power.
There is also a large gap Usability issue in that often the LLM does not really know the humans context, in other words a context collapse. It does not know if you specilised in your domain or just asking for fun.
We should be exploring and debating these gaps.
> There is a really important question that is been lost between the anti and pro AI camps which is really answering what AI is good at and what AI is bad at, ...
I think some of this pro/anti AI discussion is really a proxy for something else though. There is another unstated, societal disagreement about personal responsibility and the behaviors of the AI tool users.
It isn't entirely new, as people have always been blaming abstractions which lack agency (society, bureaucracy, "the machine", "the process", "the game", etc.) to conduct themselves in an ethically or logically flawed manner and then shirk responsibility. But, I think it is accelerating dramatically with the way AI agent usage is being adopted. I don't see how this can possibly continue to be normalized without leading to a catastrophic outcome.
Right now, AI tool usage is being applied in ways that would have been considered misconduct, negligence, or fraud if the actors were doing the same thing via traditional outsourcing. People who have a contractual and ethical responsibility to apply analysis, judgement, and oversight are rapidly turning into dumb pipes who just relay content. They essentially phone it in, trying to take credit for apparently moving KPIs "up and to the right". They pretend to themselves and others that they are reviewers and still in control, but when things go wrong they expect forgiveness and for others to lean in and clean up their rapidly spreading mess.
In software circles, many of us are appalled by this slop that is poisoning the well for our existing organizations. It seems like a massive, toxic externality. To us, people aiming their AI agents into our existing collaborations are pretty much flipping a switch to "roll coal", or worse.