You’re probably already experienced at your job and using AI to enhance that, or at least using that experience to keep the AI results clean. That’s something you or a company would want to pay for but it has to be a lot more than today’s prices to make it profitable. Companies want to get more out of you, or get a better price/performance ratio (an AI that delivers cheaper than the equivalent human).
But current gen AIs are like eternal juniors, never quite ready to operate independently, never learning to become the expert that you are, they are practically frozen in time to the capabilities gained during training. Yet these LLMs replaced the first few rungs of the ladder so human juniors have a canyon to jump if they want the same progression you had. I’m seeing inexperienced people just using AI like a magic 8 ball. “The AI said whatever”. [0] LLMs are smart and cheap enough to undercut human juniors, especially in the hands of a senior. But they’re too dumb to ever become a senior. Where’s the big money in that? What company wants to pay for the “eternal juniors” workforce and whatever they save on payroll goes to procuring external seniors which they’re no longer producing internally?
So I’m not too sure a generation of people who have to compete against the LLMs from day 1 will really be producing “so much more” of value later on. Maybe a select few will. Without a big jump in model quality we might see “always junior” LLMs without seniors to enhance. This is not sustainable.
And you enhancing your carpentry skills for your free time isn’t what pays for the datacenters and some CEO’s fat paycheck.
[0] I hire trainees/interns every year, and pore through hundreds of CVs and interviews for this. The quality of a significant portion of them has gone way down in the past years, coinciding with LLMs gaining popularity.