Comment by socializer
9 hours ago
I don't think it's that simple. I divide AI-impacted fields into three buckets:
1. Some present a unified line that the whole point of their craft is the human experience, and that automation is the antithesis of that. Marathon runners don't care that a car can get there faster, poets don't care that Poem Bot 2000 can write poems too. I think this is smart if you can credibly take this position. The difficulty is mostly convincing the buy side, which requires being very outspoken about your views.
2. Some appear to be undecided, with one faction taking the pro-human stance and another rushing to accelerate things with AI. A good example of this is mathematics, and I really wonder where they end up in the long haul. They have a very good claim on #1, because mathematics is pretty close to an art form and is robustly insulated from the pressures of the marketplace. But they can also choose option #3, below.
3. Some crafts prioritize results above all else, practitioners either rushing to extract as much money as possible before it all collapses, or believing that they can out-prompt everyone else forever and that their prompting skills are indispensable to their employers in the long haul. That's software engineering. I think this is going to be interesting to watch.
I don't think it's smart at all to position yourself in bucket 1.
There's a reason there are maybe a few hundred professional marathon runners in the world vs tens of thousands of professional mathematicians. Bucket 1 is basically an "amusement for the upper classes" type of deal. Any field that goes in that direction would have to shrink down massively.
It also devalues the field in my opinion from something really profound with actual impact in the world to a somewhat vain leisure activity. (basically going back to gentleman scientists) But I know other people would see it exactly the opposite way.
> There's a reason there are maybe a few hundred professional marathon runners in the world vs tens of thousands of professional mathematicians.
I don't buy this. I think there are other reasons why "professional marathon running" is a niche thing; it's probably just that it's not all that interesting to most people to practice in function of what it demands of your body, and not that interesting to patronize / watch.
Take woodworkers. There's probably more professional woodworkers than professional mathematicians. In terms of utility, everything a woodworker does, a machine can do more cheaply and more quickly. The main reason the craft survives is just that we attach intrinsic value to furniture made by humans the old-fashioned way. This is shared by craftsmen and those who buy.
And you could argue the same thing you did for marathon runners: custom furniture is just amusement for well-off people. Sure, but there's enough people with money to keep it afloat.
Ah but your buckets are based on your assumptions about the topic.
You say marathons are just for fun, but prior to the wheel it was the only way to get around. (Other than horses in some places)
So it’s not that running is immune to automation, it’s that we’re already post-automation and that only people doing it for fun are left.
I think your second bucket would need to be changed, as it's not really undecided for some and Tao in fact argues (in a way) that there is no need for the field to decide. There is a need for results, but there is also a need for humans to fully understand why the results are the way they are and how they were obtained. This doesn't replace the human in the loop it's more of a cooperative effort.
I'd end up with the buckets
a) Fully human
b) Hybrid human-AI
c) Fully AI
Extrapolating from the list, the "Fully AI" camp is going to push the pedal to the metal, investing time and effort into maximizing their fusion with this technology. Mentally enhanced and amplified 24/7, and likely physically too, fusing their biology with hardware and robotics. Within a few years, not even a generation, they will become unrecognizable to the "Fully Human" category.
Seems like neat buckets but you may want to find one example for the first which can actually be done by an llm as running is not its strong suit afaik
I gave two examples for #1 and one of them is something done by LLMs. Other examples include painting / drawing, songwriting & composing, etc. In all of these, gen AI output is pretty widely stigmatized.