I quit my job in public accounting for many reasons, but the primary one was the forceful adoption of LLMs to replace associates.

I told the dimwits at the top that it was a mistake, because LLMs are incompetent even when the information fed to it was perfect, and that was rarely the case in practice.

Our ultra wealthy clients were notorious for giving us the most incomplete and asinine information, and it often took someone with decades of experience to decipher what the fuck their personal assistants are even talking about.

They went ahead anyway because of the high cost of wages, of course, and I made my exit because I did not wish to be complicit in such a monumental mistake.

Lmfao the LLM they laid associates off and paid half a million dollars for made up fake ledger accounts when accounts didn't reconcile, and none of the dumbasses left noticed in time because they hadn't done associate-level work in decades.

It also lied all the time, even when you asked it not to.

The damage was done and the biggest clients started leaving, so they begged us all to come back but I got obsessed with baking bread and I ain't about to neglect my sourdough starters to help a group of people who would lose a battle of wits against yeast.

I would not trust a text generator to do math, no. It's wholly the wrong tool for the job. Nor do I trust them to be up to date and compliant with tax code. And I really don't trust them to take legal responsibility for their output.

the only good thing i trust an LLM to do is build a official looking document from 5 or 6 bullet points i give it. Even then im going to proof read it a few times just to make sure it didn't add anything stupid.

Cooking the books AI style

Compounding tasks like accounting where operations sound easy but create a chain of counter entries and balances need to be organized by account is none of AIs business until they can prove that multiple sequential steps can have over 99% accuracy and the checksum of the accounts is balanced.

Multiple sequential steps with six operations where we assume 99 PCT of each, is right can equal 90% accuracy. This also reads at least 10% errors if they all six go wrong.

How many different entries are in a company over a month's closure?

Now this wouldn't be and issue if it can balance the statements of consolidated accounts and find where are we missing entries or misallocations. That sir is why we pay someone with experience.

Just after a message that stated how AI developed software deleted the main database and lied about it. Really builds trust and confidence into AI-based projects.

I do not believe that LLMs will ever be able to replace humans in tasks designed for humans. The reason is that human tasks require tacit knowledge (=job experience) and that stuff is not written down in training material.

However, we will start to have tasks for LLMs pretty soon. It was already observed that LLMs work better on stuff produced by other LLMs.