Industrial machinery is only making workers weak, lazy and prone to replacement.
Jokes aside, as any tool, it depends on how you use it. I think the problem is not AI assistance but the ever existing urgency and lack of patience of nowadays, which leads to everything to be done as fast as possible with no toleration to any waiting time. This plus language models is a really band combination that would lead to a disaster way before AGI or anything like that is remotely close.
Agreed. If your identity is your ability to bang away on a keyboard writing instructions to a computer in Python (or any other "language"), you're in for a bad time.
If your identity is solving difficult, domain-specific software-based problems, efficiently and securely, it doesn't matter if your instructions are written in English, French or... Python.
One point where, I think, the analogy fails is context.
If one wants to modify a code base, it's necessary to be able to, sort of, load the program into ones head and then work off a mental model. The "slowness" of traditional development and the tooling around it gave people enough time to do this and over time, get really good at a navigating and changing a code base.
With LLMs being able to generate huge amounts of code in a short time, this is missing. The LLM doesn't fully know what it generated and the nuances. The developer doesn't have the time to absorb all that so at the end of the day, you have something running which nobody (including the original AI author) really understands. That's risky.
Of course, there are ways to mitigate and handle this I don't know if the original analogy is missing this.
Comments
Industrial machinery is only making workers weak, lazy and prone to replacement.
Jokes aside, as any tool, it depends on how you use it. I think the problem is not AI assistance but the ever existing urgency and lack of patience of nowadays, which leads to everything to be done as fast as possible with no toleration to any waiting time. This plus language models is a really band combination that would lead to a disaster way before AGI or anything like that is remotely close.
Agreed. If your identity is your ability to bang away on a keyboard writing instructions to a computer in Python (or any other "language"), you're in for a bad time.
If your identity is solving difficult, domain-specific software-based problems, efficiently and securely, it doesn't matter if your instructions are written in English, French or... Python.
One point where, I think, the analogy fails is context.
If one wants to modify a code base, it's necessary to be able to, sort of, load the program into ones head and then work off a mental model. The "slowness" of traditional development and the tooling around it gave people enough time to do this and over time, get really good at a navigating and changing a code base.
With LLMs being able to generate huge amounts of code in a short time, this is missing. The LLM doesn't fully know what it generated and the nuances. The developer doesn't have the time to absorb all that so at the end of the day, you have something running which nobody (including the original AI author) really understands. That's risky.
Of course, there are ways to mitigate and handle this I don't know if the original analogy is missing this.