I'm guessing LLM decision is rather average, but that the LLM has no easy way of spending the extra time to gather information around said high stakes decisions like a human would.

Just like like LLMs, some humans are better tuned than others for specific tasks, as well as in general.

With high-stakes decisions, you're surrendering the decision-making power to the AI because you don't understand the output well enough to verify it.

Basically, and AI can give ideas but not advise.

Room to grow.

*observations from the recent karpathy llm talk.

Where are the dates in whole foods? (A: with nuts, not fruits and veggies)

How can I steam bao without a steamer basket? (A: saucepan, 1" water, balled up aluminum foil, plate, baos, lid)

Any guess as to when this photo was taken? It looks like anywhere from the 70s to the 90s. (A: the photo paper has a logo that postdates a 2003 company merger)

I had to buy some spare tools where I cared more about price than quality and it helped me choose some suitable brands

As mentioned, you can tell it a bit about a person (and feed in their wishlist if they have one) and it'll help you pick something they'll probably like

Finding something to do to spend an afternoon in a city while traveling

In general, anything where there is no objective best answer (meaning I can ask it to generate multiple possibilities and filter out the bad ideas) and where I value speed over correctness.

I've been going ham with this. Pay for ChatGPT Plus for work, so GPT-4's been helping me design encounters, plan sessions, and brainstorm ideas for one-shots. It gives me a sort of bland, vanilla idea for something, I suggest a twist on it, it goes, "oh great idea, here that is with your changes:" and I iterate with it from there.

Likewise I love theming characters, plotlines, and settings after songs, bands and albums, so I'll dump in a bunch of lyrics and ask ChatGPT to help me intertwine subtle references into descriptions, names, and plot points.