Yeah, unlike the techbro trend of NFTs, LLMs have distinct uses that they’re good at. The problem I have with the AI craze is that they’re trying to pretend like it can do fucking everything and they’re chasing these stupid dreams of general AI by putting a dumb fuck autocorrect algorithm in everything and trying to say it’s intelligent. Oh, also the AI label itself ruins the reputation of various machine learning applications that have historically done great work in various fields.
The company I work for uses it to transcribe meetings. Every time I’ve reviewed its notes on a meeting where I’ve spoken, the transcription is reasonably accurate, but the summary is always wrong. Sometimes it’s just a little wrong like it rounds off a number in a way that I wouldn’t have, but sometimes it writes down that I said the literal opposite of what I actually said. Not great for someone working in finance.
I make note of it in my performance reviews, anticipating that someone in management will rely on one of those summaries to make a horrible business decision and then blame me for what the summary said. I’m positive it’s going to happen eventually.
My work has group chats. When a lot of messages pile up, an AI auto-generates a summary. Sometimes the summary misses the mark, highlighting details that don’t actually matter. Sometimes it calls people by their last name, which is weird because we don’t usually call each other by our last names.
There is no opt-out. However, it does ask for a thumbs up/down. Since it won’t allow for any more precise feedback or an ability to disable it, I express my distaste by giving it a thumbs-down every single time.
Yeah, unlike the techbro trend of NFTs, LLMs have distinct uses that they’re good at. The problem I have with the AI craze is that they’re trying to pretend like it can do fucking everything and they’re chasing these stupid dreams of general AI by putting a dumb fuck autocorrect algorithm in everything and trying to say it’s intelligent. Oh, also the AI label itself ruins the reputation of various machine learning applications that have historically done great work in various fields.
The company I work for uses it to transcribe meetings. Every time I’ve reviewed its notes on a meeting where I’ve spoken, the transcription is reasonably accurate, but the summary is always wrong. Sometimes it’s just a little wrong like it rounds off a number in a way that I wouldn’t have, but sometimes it writes down that I said the literal opposite of what I actually said. Not great for someone working in finance.
I make note of it in my performance reviews, anticipating that someone in management will rely on one of those summaries to make a horrible business decision and then blame me for what the summary said. I’m positive it’s going to happen eventually.
My work has group chats. When a lot of messages pile up, an AI auto-generates a summary. Sometimes the summary misses the mark, highlighting details that don’t actually matter. Sometimes it calls people by their last name, which is weird because we don’t usually call each other by our last names.
There is no opt-out. However, it does ask for a thumbs up/down. Since it won’t allow for any more precise feedback or an ability to disable it, I express my distaste by giving it a thumbs-down every single time.