In-person work has higher bandwidth and lower latency than remote work, so for certain roles it makes sense you wouldn't want to farm it out to remote workers. The quality of the work can degrade in subtle ways that some people find hard to work with.
Similarly, handing a task to a human versus an LLM probably comes with a context penalty that's hard to reason about upfront. You basically make your best guess at what kind of system prompt an LLM needs to do a task, as well as the ongoing context stream. But these are still relatively static unless you have some complex evaluation pipeline that can improve the context in production very quickly.
So I think human workers will probably be able to find new context much faster when tasks change, at least for the time being. Customer service seems to be the frontline example. Many customer service tasks can be handled by an LLM, but there are probably lots of edge cases at the margins where a human simply outperforms because they can gather context faster. This is my best guess as to why Klarna reversed their decision to go all-in on LLMs earlier this year.
Every time I see this argument made, there seems to be a level of complexity and/or operational cost above which people throw up their hands and say "well of course we can't do that".
I feel like we will see that again here as well. It really is similar to the self-driving problem.
I enjoy riding e-bikes, for the record. Going fast on an e-bike is like having happiness on tap. I think more people should own them so that we can collectively start to realize a different way of organizing transportation and commute.
Regarding safety, when it is a bike vs a car, I agree that having more speed is better and safer for the cyclist.
But the issue is when we have a bike vs a pedestrian. I've been a pedestrian next to groups of fast moving e-bikes. It can be pretty scary. Some cyclists can feel entitled to riding on the sidewalk, which at high speeds can really injure someone if they were to crash. E-bikes also weigh a lot more than a non-ebike (up to 120lb in some cases) so getting hit at top speed is a bigger deal than a normal bike.
My overall point is that I think cyclists need to start behaving more like vehicles, rather than fast-moving pedestrians. Obviously we need more investment in biking infrastructure for that to happen, but with how fun and useful e-bikes are, I am optimistic that will eventually happen. As e-bikes become more common, I expect this to become a bigger part of the conversation.
A mental analogy that I personally use for this is cabinets. A section of an app is kind of like a cabinet in a kitchen. Some people like opaque cabinet doors while others prefer glass. Other people go even further, and eschew cabinets for open shelves.
These differences in object and system visibility sometimes reflect specific use cases (e.g., a professional kitchen can operate faster with open shelving than with opaque cabinet doors). Other times, they simply reflect the personal preferences of the designer.
In-person work has higher bandwidth and lower latency than remote work, so for certain roles it makes sense you wouldn't want to farm it out to remote workers. The quality of the work can degrade in subtle ways that some people find hard to work with.
Similarly, handing a task to a human versus an LLM probably comes with a context penalty that's hard to reason about upfront. You basically make your best guess at what kind of system prompt an LLM needs to do a task, as well as the ongoing context stream. But these are still relatively static unless you have some complex evaluation pipeline that can improve the context in production very quickly.
So I think human workers will probably be able to find new context much faster when tasks change, at least for the time being. Customer service seems to be the frontline example. Many customer service tasks can be handled by an LLM, but there are probably lots of edge cases at the margins where a human simply outperforms because they can gather context faster. This is my best guess as to why Klarna reversed their decision to go all-in on LLMs earlier this year.