There are three parts of this talk, the last part (~last 15mins) bluntly address the question "how human roles shift in a world with advanced AI?"
My main takeaways from the speaker's position are: purely technical skills will get devalued because they tend to be verifiable tasks and AI will get better. Also effort will shift from building to evaluation of AI and systems. Speaker also mentioned that more of our time will go to decision making while AI takes over delivering on decisions.
I found many arguments to be at odds with one another bc the speaker does not address how someone can gain understanding without accumulating purely technical skills. It simply does not add up that someone who lacks purely technical skills in an area can make good decisions. Experience is often a by product of accumulating technical acumine in a particular problem area.
I have a question about “domain expertise” as a component of future knowledge worker requirements. How does one gain such expertise in a context where thinking is expected to be delegated to AI (shifting from problem solving to question asking, as noted in this paper)?
How does one learn to pose the right questions when basic ones are rarely “manually” answered? that is, without an AI assistant’s help
This pattern appears in schools, where AI interferes with human development that typically demands long and difficult effort of actually answering questions
> I argue that there will be plenty for us to work on, grounded in the “AI as normal technology” thesis
There is no doubt that AI is creating more work than it produces. Every single line it writes has to be reviewed by someone because AI cannot take responsibility. And it can spew out decades worth of written code every day. Every line is untrustworthy and must be manually verified.
The problem is I don't want to do this work. You don't either. Everyone I've seen using AI to write code does not do this work. Anyone who says they do this work is lying, to you or themselves or a little of both. People just YOLO and ship it.
If that is the only work left to do when using AI, I'll just do it the old way. If that's not good enough to stay employeed, then I'll just find a new career.
It seems likely there will be much work in the area of fixing the slop code that proves to be unmaintainable. Companies right now are racing to push the lowest quality code into prod with no way to even QA it. If you have the skills, it'll be top dollar to bail these people out.
There are three parts of this talk, the last part (~last 15mins) bluntly address the question "how human roles shift in a world with advanced AI?"
My main takeaways from the speaker's position are: purely technical skills will get devalued because they tend to be verifiable tasks and AI will get better. Also effort will shift from building to evaluation of AI and systems. Speaker also mentioned that more of our time will go to decision making while AI takes over delivering on decisions.
I found many arguments to be at odds with one another bc the speaker does not address how someone can gain understanding without accumulating purely technical skills. It simply does not add up that someone who lacks purely technical skills in an area can make good decisions. Experience is often a by product of accumulating technical acumine in a particular problem area.
Nobody has good answers for any of these things. It's a folly to think someone else has it figured out.
I have a question about “domain expertise” as a component of future knowledge worker requirements. How does one gain such expertise in a context where thinking is expected to be delegated to AI (shifting from problem solving to question asking, as noted in this paper)?
How does one learn to pose the right questions when basic ones are rarely “manually” answered? that is, without an AI assistant’s help
This pattern appears in schools, where AI interferes with human development that typically demands long and difficult effort of actually answering questions
How do you become a baker, in a world of bread factories.
I think the answer lies in baking the good old fashioned way and ignoring the factories.
The author has a blog post mirroring their talk in writing: https://www.normaltech.ai/p/what-will-be-left-for-us-to-work
https://autonoma.ca/model.png
Thoughts?
Maybe work on a larger font size, pal.
Video recording from ICML up from Arvind Narayanan
> I argue that there will be plenty for us to work on, grounded in the “AI as normal technology” thesis
There is no doubt that AI is creating more work than it produces. Every single line it writes has to be reviewed by someone because AI cannot take responsibility. And it can spew out decades worth of written code every day. Every line is untrustworthy and must be manually verified.
The problem is I don't want to do this work. You don't either. Everyone I've seen using AI to write code does not do this work. Anyone who says they do this work is lying, to you or themselves or a little of both. People just YOLO and ship it.
If that is the only work left to do when using AI, I'll just do it the old way. If that's not good enough to stay employeed, then I'll just find a new career.
Programming is a vocation. It became a career because of sheer luck.
It seems likely there will be much work in the area of fixing the slop code that proves to be unmaintainable. Companies right now are racing to push the lowest quality code into prod with no way to even QA it. If you have the skills, it'll be top dollar to bail these people out.
I can't even trust a chatbot with internet search. You guys use it for research?
Then don't trust a chatbot for internet search. There's much more to llms than chat bots
Yes you can. This comment might have made sense in early 2025.