As always, I use the term “AI” loosely. I’m referring to these scary LLMs coming for our jobs.
It’s important to state that I find LLMs to be helpful in very specific use cases, but overall, this is clearly a bubble, and the promises of advance have not appeared despite hundreds of billions of VC thrown at the industry.
So as not to go full-on polemic, we’ll skip the knock-on effects in terms of power-grid and water stresses.
No, what I want to talk about is the idea of software in its current form needing to be as competent as the user.
Simply put: How many of your coworkers have been right 100% of the time over the course of your career? If N>0, say “Hi” to Jesus for me.
I started working in high school, as most of us do, and a 60% success rate was considered fine. At the professional level, I’ve seen even lower with tenure, given how much things turn to internal politics past a certain level.
So what these companies are offering is not parity with senior staff (Ph.D.-level, my ass), but rather the new blood who hasn’t had that one fuckup that doesn’t leave their mind for weeks.
That crucible is important.
These tools are meant to replace inexperience with incompetence, and the beancounters at some clients are likely satisfied those words look similar enough to pass muster.
We are, after all, at this point, the “good enough” country. LLM marketing is on brand.
Who, exactly, pays for this “cheaper”? And what of the wages for people who have to spend their time verifying LLM output? Yeah, my point is it doesn’t have to be perfect, but in the examples cited, there’s a fair amount of oversight.
At least, there used to be.
I meant it doesn’t need to be perfect. It only needs to just barely as good as the people it replaces and appear cheaper on a balance sheet/cash flow statement for the quarter. Otherwise every service company wouldn’t be buying crap ‘AI’ chat bots for all customer facing duties.
Alternatively, self driving vehicles are probably already better than the bottom 50% of drivers in 50% of situations. I.e. driving on a road. We still want flawed human oversight of that.