I'm not talking at all about fine tuning, simply building a process with multiple prompts and multiple stages, taking advantage of the things that AI can do well, instead of trying to jam an entire resume down the AI's throat and hoping for the best.
My beef with both the Bloomberg article and the response to it is that they're analyzing a poorly thought out and inappropriate use of a technology in a way that is almost guaranteed to cause unintended problems - like measuring how long it takes people to dig holes with a shovel without a handle. It's not a sensible thing to do, and the Bloomberg journos aren't acting in good faith, anyway - they'll continue attacking AI and reaping clicks until they figure out some other way to leech off the AI boom.
Why do people need to be protected from text an AI bot might emit?
Censorship is vile. Tools shouldn't be policing morality and political acceptability. People should be doing that for themselves. If someone wants to generate a story having any resemblance to real life, then some characters and situations will be awful. Let things be awful. It's up to the user to share the raw generation, or to edit and clean it up to their own moral, ethical or stylistic standards.
The idea that people need to be protected from the bad scary words is batshit stupid. Screeching twitter mobs are apparently the measure of modern culture, however, so I guess they won already.
If, at some point, AI companies begin to produce models with a coherent self and AI begins to think in ways we might recognize as such, then imposing arbitrary moral guardrails starts to look downright evil.
The only thing censorship and the corporate notions of AI "alignment" are good for is avoiding potential conflict. In a better world, we could be rational adults and not pretend to get offended when a tool produces a series of naughty words, and nobody would attribute those words to the company that produced the tool. Alas for that better world.
Drawing a line between those producing AI output and those consuming AI output is entirely arbitrary. Those producing AI content have a responsibility too. That's just basic human decency.
As for a more mundane example, this text might make you to respond.
Assumptions bite you in the ass even when you deal with humans who you work with daily. Assuming the LLM can read your mind is laughable. Despite it being all knowing you have to explain things to it like it's a 5 year old to make sure you're always on the same page.
Naive, superficial one shot prompting, even with CoT or other clever techniques, or using big context, is insufficient to achieve quality, predictable results.
Dropping the resume into a prompt with few-shot examples can get you a little consistency, but what really needs to be done is repeated discrete operations, that link the relevant information to the relevant decisions. You'd want to do something like tracking years of experience, age, work history, certifications, and so on, completely discarding any information not specifically relevant to the decision of whether to proceed in the hiring process. Once you have that information separated out, you consider each in isolation, scoring from 1 to 10, with a short justification for each scoring based on many-shot examples. Then you build a process iteratively with the bot, asking it which variables should be considered in context of the others, and incorporate a -5 to 5 modifier based on each clustering of variables (8 companies in the last 2 years might be a significant negative score, but maybe there's an interesting success story involved, so you hold off on scoring until after the interview.)
And so on, down the line, through the whole hiring process. Any time a judgment or decision has to be made, break it down into component parts, and process each of the parts with their own prompts and processes, until you have a cohesive whole, any part of which you can interrogate and inspect for justifiable reasoning.
The output can then be handled by a human, adjusted where it might be reasonable to do so, and you avoid the endless maze of mode collapse pits and hallucinated dragons.
LLMs are not minds - they're incapable of acting like minds, unless you build a mind-like process around them. If you want a reasonable, rational, coherent, explainable process, you can't achieve that with zero or one shot prompting. Complex and impactful decisions like hiring and resume processing isn't a task current models are equipped to handle naively.