A larger number of people dying from an unrelated cause in another country doesn’t make these deaths insignificant. By that logic, virtually no problem deserves attention because you can always find something that kills more people.
The "trolley problem" is literally never a valid argument for anything because it purports to create an analogy for a real world problem but does so by creating a scenario that cannot exist, hence any argument based on it is nonapplicable to "real" problems.
So you’re being pedantic? Future forecasts and estimates can’t mesh with the trolly problem? If that’s your stance sure, you are correct. I do feel like you missed the whole point of the exercise though, and are hiding behind an absolute that is never achievable.
Look, nobody brings up the trolley problem because they're concerned about what they're going to do when a train car goes out of control.
They use it as a metaphor to attempt to make an argument about a different, actually real, situation. My argument is this is pointless because no real world situation will ever meaningfully resemble the trolley problem.
The correct answer to the trolley problem is STOP THE TROLLEY. "You can't do that!" "Why not?" "because magic" "well how do I know this magic is there?" "more magic!" etc etc.
What do you do if the dragon demands a sacrifice or it attacks the town? You fight the dragon.
The idea that "stop the trolley" or "slay the dragon" is cost-free is a wish. You've merely added a third horn to the dilemma. "Someone brave attempts to jump onto the moving trolley, risking their own neck" might well be the preferred choice; the expected outcome may marginally improve; the shape of the problem remains.
I hope you're arguing out of perversity, not conviction - such is valuable, and i did have to think for a minute. I agree that lateral thinking can be productive.
At no point did I say anything was "cost-free" or even make any reference to cost. It's extremely rare for the cost of an action to be at all relevant to its morality.
> Someone brave attempts to jump onto the moving trolley, risking their own neck
This is a completely different problem. The whole point of the trolley problem is to attempt to justify the sacrifice of the few for the good of the many.
The entire framing is about other people dying, not whether or not you would sacrifice yourself.
Personally, I believe that the supposed productivity gains of LLMs will turn out to be much like outsourcing to India around the turn of the century: managers think it's a great idea to cut costs, but it will also make quality plummet, and there will be a correction back towards sanity. That doesn't mean that everything is all roses - even if the market will get over the AI insanity someday, that's cold comfort if you're out of a job right now. But I do think that it's not going to be "if you aren't on board, then gg" in the long run.
I have already seen multiple CLs from people who are both senior and junior where I know they did not look at the code. I thought, at first, they worked and upon review it looked good but when I synced these changes I found either big bugs that a human would never make or a test would never catch or lots of code repetition.
One example was an engineer who was refactoring some code that ended up doing this:
def execute(jobs):
for job in jobs:
asyncio.create_task(compute(job))
yield await compute(job)
This is very simplified, it as actually broken up into two separate loops and hidden behind multiple nested calls but at some point there literally was a `asyncio.create_task` where the result was not being used.
I looked at this code because we were hitting some quota limits very early for some reason and it turned out we ran 2x the reads we needed to. I refactored this code, 1/2ed the execution time, fixed the quota issues, and took it from ~300 lines to 80 lines.
This was code from a *senior software engineer* with 15 years in the industry. What is very interesting is I see similar bugs from juniors who do or don't use AI.
I am not saying AI can't be useful. On weeks I have had clear tasks set out, while the rest of my team was OOO, I tackled probably 5x the work our team normally accomplishes (this was after all the work was identified, just working). My skip actually said "Wow, we had a very productive week!" so multiple layers noticed the productivity. I think what made this possible was:
1. I fully understood the **entire** task and the end-user needs.
2. The code base was structured "fine" with enough decoupling between components that I wasn't hitting merge conflicts with myself.
3. I self-reviewed all the work before sending anything to other people (opened all the changes in my IDE, read all the tests).
4. If something seemed too complicated I refactored it manually.
5. I left the AI chugging for long periods of time on objectively measurable tasks.
I don't think the practice of engineering software is dead. The architecture of your software now has measurable impact on productivity. I don't think thinking about performance is outdated. If you're running code no one has reviewed but is functional you wasting cycles / money. Having domain knowledge still improves your velocity.
Because of these reasons I think there is still marginal value to programmers. Companies which maintain internal talent pools and build tooling to scale the impact of people will probably beat out smaller companies that just vibe code.
Do the booming companies pay the same as the ones who did layoffs? If you're laid off from Meta or other top tier paying company (the behemoths doing layoffs) you might have a tough time matching your compensation.
But do they need to? If a <role X> job at a top tier company making $600k is eliminated and two <role X> jobs at a "more average" company making $300k replace it; is that really a bad thing? Clearly, there's some details being glossed over, but "one job paying more than a person really needs" being replaced by "two jobs, each paying more than a person really needs" might just be good for society as a whole.
It doesn't seem too bad when you cherry pick an outlier example, but what about when the person making $100k now makes $50k?
I'm sure the retort of the AI optimist will be that AI will make the things that person buys cheaper, and there may be truth to that when it comes to things that people buy with disposable income...
But how likely is AI to make actual essentials like housing and food cheaper?
I think this is assuming that the labor market knows how to identify the dirct value of devs. This already seems to be a problem across the board regardless of job role.
True enough, but do you think the usual level of disparity is so vast that it ends up on the front page of international press outlets? I'm thinking the $100m pay offers etc
Happens with professional sports teams all of the time. I guess the difference is with professional sports the criteria for receiving the monster pay packages is a bit more objective.
