>... mandates removing illegal content, restricting access to harmful material, and implementing age verification, with Ofcom enforcing compliance. Violations can result in massive fines of up to 10% of global turnover or £18 million.
I guess some people either figure it's easier to block the UK or do so on principle as a protest against the thing.
This is part 9 of a 10-part series. The author has posted every chapter to Hacker News every day for the past 9 days. Every time four of the first five or so comments are:
Someone noting it is unavailable in the UK.
Someone posting an archive.is link.
Someone asking why the above posted an archive link to a static site.
An answer that it is because the content is otherwise unavailable in the UK.
Do we really need to see this every single time?
I realize I am also not adding to the real discussion now as well, but Jesus Christ, this is irritating. Can we get a new rule that an author posting their own content, knowing it is unavailable in the UK, has to post their own archive link and explain why they're doing so as part of the submission?
I think that this is an interesting attempt at taxonomy, but it's a bit on the magical thinking end (and I say this as somebody that does a good amount of what's described as the incanter role). It's a combination of the author's previous witchy aesthetic (see his excellent "<x>ing the technical interview" series) and progressive labor politics (which are asymptotically doomed in the current automation push).
The biggest failure of imagination, I think, is the assumption we'd use humans for most (or *any) of these jobs--for example, the work of the haruspex is better left to an LLM that can process the myriad of internal states (this is the mechanical interpretation field).
I am personally of the opinion that ML will end up being 'normal technology', albeit incredibly transformative.
I think you can combine 'Incanters' and 'Process Engineers' into one - 'Users'. Jobs that encompass a role that requires accountability will be directing, providing context, and verifying the output of agents, almost like how millions of workers know basic computer skills and Microsoft Office.
In my opinion, how at-risk a job is in the LLM era comes down to:
1: How easy is it to construct RL loops to hillclimb on performance?
2: How easy is it to construct a LLM harness to perform the tasks?
3: How much of the job is a structured set of tasks vs. taking accountability? What's the consequence of a mistake? How much of it comes down to human relationships?
Hence why I've been quite bullish on software engineering (but not coding). You can easy set up 1) and 2) on contrived or sandboxed coding tasks but then 3) expands and dominates the rest of the role.
On Model Trainers -- I'm not so convinced that RLHF puts the professional experts out of work, for a few reasons. Firstly, nearly all human data companies produce data that is somewhat contrived, by definition of having people grade outputs on a contracting platform; plus there's a seemingly unlimited bound on how much data we can harvest in the world. Secondly, as I mentioned before, the bottleneck is both accountability and the ability for the model to find fresh context without error.
> I think you can combine 'Incanters' and 'Process Engineers' into one - 'Users'
I wanted to talk about this more but couldn't quite figure out how to phrase it, so I cut a fair bit: with "incanters" I'm trying to point at a sort of ... intuitive, more informal practitioner knowledge / metis, and contrast it with a more statistically rigorous approach in "statistical/process engineers". I expect a lot of people will fuse the two, but I'm trying to stake out some tentpoles here. Users integrate a continuum of approaches, including individual intuition, folklore, formal and informal texts, scientific papers, and rigorously designed harnesses & in-house experiments. Like farming--there's deep, intuitive knowledge of local climate and landraces, but also big industrial practice, and also research plots, and those different approaches inform (and override) each other in complex ways.
> How much of the job is a structured set of tasks vs. taking accountability?
More accurately, how many jobs are probabilistically mechanical. That is, how many jobs are really the execution of a serious Bayesian decisions with a strong prior. LLMs are really great at displacing such jobs.
As an engineer, I'm never more excited about this job.
My implementation speed and bug fixing my typed code to be the bottleneck - now I just think about an implementation and it then exist - As long as I thought about the structure/input/output/testability and logic flow correctly and made sure I included all that information, it just works, nicely, with tests.
Unix philosophy works well with LLM too - you can have software that does one thing well and only one thing well, that fit in their context and do not lead to haphazard behavior.
Now my day essentially revolves around delivering/improving on delivering concentrated engineering thinking, which in my opinion is the pure part about engineer profession itself. I like it quite a lot.
Yes I'm much more productive than before, and I'm convinced we can't get rid of engineers altogether... But how long until my team of 5 gets replaced by a single engineer? Am I going to be the one to keep my job or one of the 4 to be let go?
The problem with AI is that it isn't like any previous technology. There may be temporary jobs to fill in the gaps but they won't be careers. The AI will do the process engineering and self optimization. The prompt witchcraft is a good example because today its totally unnecessary and doesn't actually increase performance, and they'll continue to make it easier to direct/steer the models.
We're literally trying to build an intelligence to replace us.
Assuming we get smarter than human AI but keep control of the guidance and off switches we will be in the position of a king or rich person with servants smarter than themselves of which we have many historical examples. I figure it will go kind of like that but with more equality amongst the humans than historically as we'll be able to vote in some sort of socialist like set up with all humans having fun which has not been possible in the past as you need someone/something to do the work to keep things going.
Loved that section about "meat shields". LLMs cannot be held accountable. Someone needs to be involved in decision making, with real stakes if those decisions are bad.
This is the aspect of AI I ponder the most. I wonder if we’ll get to the point where it prompts a real hard think about what “accountability” really is, and what value it provides (and to whom), particularly in the standard employment situation where an employee generally can’t “make their employer whole” in the event of a mistake and can really only be “punished” for it.
>Someone needs to be involved in decision making, with real stakes if those decisions are bad.
Why though? I imagine things could also go the "google way" as well. The automated system makes the decision; and you just.. deal with the consequences if that decision is bad. We could just have an extended version of this dynamic as well: 3-4 entities with enough compute owning everything with no responsibilities; and when something goes bad, oh well. It's not like you can go to their competition, who also works the same way.
I think we saw many times that after a certain scale (after becoming, say, too big to fail), there is no bad decision you can't afford.
Humans will be held accountable, not machines, whatever is the technology used. The jobs you suggest are based on the state of LLM right now, this could change rapidly, considering the state of progress. These are just activities that are already done by people that work with these instruments, because they want to optimize and obtain the best/safest output from these machines.
All plausible, but not very transformative. Like imagining that the new jobs enabled for the automobile include automobile maintenance, tire shops, and so on. Traveling nurses, motel operators, military tanks, doordash, suburban life, beer sales at NASCAR, those were all enabled by the car (and its larger sibling the truck).
Still missing are the jobs snd industries enabled by "AI" that are not themselves "AI".
I don't understand the title. It doesn't seem exactly clickbait but also doesn't seem to be what the article is about?
Anyway: The new job types might seem overspecialized now but history shows us this is indeed what happens as new industries open up. I think these predictions look quite solid.
I think the reason AI isn't going to replace CEOs, or anyone in the C suite, is pretty obvious. They see themselves as the company. Everyone else is a resource. AI is here to replace resources, just like investing in a brand new lawn mower. For them, replacing an executive with AI is like saying you're going to marry a broom.
The CEOs can be appointed or fired by the owners of the business, regardless of how they see themselves. At the moment we don't have human level AGI so owners are better with humans doing the job but it could change down the line.
I think, long term, there will be only one job comprising all these aspects. The only absolutely-minimum-required skill will be critical thinking, possibly along with data / statistical literacy for grounding.
"Specialization is for insects." (Or for someone pushing the boundaries of human knowledge.)
jobs that have liability coverage are the last ones to get automated. even if its not doing anything all day long in terms or "work". but someone needs to go to jail when shit goes wrong as mandate by law quite often. the "oops the computer did it" isn't a sufficient excuse in some situations, accountability is a thing. so while we mechanically could replace also CEOs with machines and arguably at times would be even better than a few humans out there, some body that can be dragged to court is mandatory no matter how good the tech gets.
> I think a part of the reason is that these roles are not just about sending emails and looking at graphs, but also about dangling a warm body over the maws of the legal system and public opinion.
Spoilers for "How I Met Your Mother" ... but there's a character who has that kind of job, as a legal meat-shield. Now, ~10 years after airing, this funny clip feels like it would only need slight adjustments.
AI writes the code, humans pretend to work, and middle management stares at green Slack dots all day. Meanwhile, we just live in terror of the Slack ping. The future is incredibly stupid.
Somehow ended up after reading OP earlier this morning on a trail that lead to "Alexander of Abonoteichus – The False Prophet of 2nd Century Greece" [1]. A certain Lucian of Samorsata [2] wrote up the only known bio on the man [3] and it makes for interesting reading.
Now this guy was charging 1 drachma and 6 obols (apparently ~$100-150) per oracle. So that was his 'token rate'. And his clients the "fat-heads" (Lucian's phrasing not mine /g) were so taken by the scam that this guy earned up to 80,000 drachma per year! That's over 10 million bucks. For spewing b.s.
As to why all this is remotely related to OP's article, his mention of lawyers getting into trouble because of using LLM output instead of their brains ...
"By way of impressing the people still more, he announced that he would induce the God to speak, and give his responses without an intermediary ... These oracles were called autophones, and were not vouchsafed casually to any one, but reserved for officials, the rich, and the lavish.
"It was an autophone which was given to Severiann [4] regarding the invasion of Armenia. He encouraged him with these lines:
'Armenia, Parthia, cowed by thy fierce spear,
To Rome, and Tiber's shining waves, thou com'st,
Thy brow with leaves and radiant gold encircled!'
"Then when the foolish Gaul took his advice and invaded, to the total destruction of himself and his army by Othryades, the adviser expunged that oracle from his archives [!!!] and substituted the following:
"'Vex not th' Armenian land; it shall not thrive;
One in soft raiment clad shall from his bow Launch death,
and cut thee off from life and light.'"
42 comments
[ 1.8 ms ] story [ 59.8 ms ] thread>... mandates removing illegal content, restricting access to harmful material, and implementing age verification, with Ofcom enforcing compliance. Violations can result in massive fines of up to 10% of global turnover or £18 million.
I guess some people either figure it's easier to block the UK or do so on principle as a protest against the thing.
Someone noting it is unavailable in the UK.
Someone posting an archive.is link.
Someone asking why the above posted an archive link to a static site.
An answer that it is because the content is otherwise unavailable in the UK.
Do we really need to see this every single time?
I realize I am also not adding to the real discussion now as well, but Jesus Christ, this is irritating. Can we get a new rule that an author posting their own content, knowing it is unavailable in the UK, has to post their own archive link and explain why they're doing so as part of the submission?
The biggest failure of imagination, I think, is the assumption we'd use humans for most (or *any) of these jobs--for example, the work of the haruspex is better left to an LLM that can process the myriad of internal states (this is the mechanical interpretation field).
I think you can combine 'Incanters' and 'Process Engineers' into one - 'Users'. Jobs that encompass a role that requires accountability will be directing, providing context, and verifying the output of agents, almost like how millions of workers know basic computer skills and Microsoft Office.
In my opinion, how at-risk a job is in the LLM era comes down to:
1: How easy is it to construct RL loops to hillclimb on performance?
2: How easy is it to construct a LLM harness to perform the tasks?
3: How much of the job is a structured set of tasks vs. taking accountability? What's the consequence of a mistake? How much of it comes down to human relationships?
Hence why I've been quite bullish on software engineering (but not coding). You can easy set up 1) and 2) on contrived or sandboxed coding tasks but then 3) expands and dominates the rest of the role.
On Model Trainers -- I'm not so convinced that RLHF puts the professional experts out of work, for a few reasons. Firstly, nearly all human data companies produce data that is somewhat contrived, by definition of having people grade outputs on a contracting platform; plus there's a seemingly unlimited bound on how much data we can harvest in the world. Secondly, as I mentioned before, the bottleneck is both accountability and the ability for the model to find fresh context without error.
I wanted to talk about this more but couldn't quite figure out how to phrase it, so I cut a fair bit: with "incanters" I'm trying to point at a sort of ... intuitive, more informal practitioner knowledge / metis, and contrast it with a more statistically rigorous approach in "statistical/process engineers". I expect a lot of people will fuse the two, but I'm trying to stake out some tentpoles here. Users integrate a continuum of approaches, including individual intuition, folklore, formal and informal texts, scientific papers, and rigorously designed harnesses & in-house experiments. Like farming--there's deep, intuitive knowledge of local climate and landraces, but also big industrial practice, and also research plots, and those different approaches inform (and override) each other in complex ways.
More accurately, how many jobs are probabilistically mechanical. That is, how many jobs are really the execution of a serious Bayesian decisions with a strong prior. LLMs are really great at displacing such jobs.
My implementation speed and bug fixing my typed code to be the bottleneck - now I just think about an implementation and it then exist - As long as I thought about the structure/input/output/testability and logic flow correctly and made sure I included all that information, it just works, nicely, with tests.
Unix philosophy works well with LLM too - you can have software that does one thing well and only one thing well, that fit in their context and do not lead to haphazard behavior.
Now my day essentially revolves around delivering/improving on delivering concentrated engineering thinking, which in my opinion is the pure part about engineer profession itself. I like it quite a lot.
Yes I'm much more productive than before, and I'm convinced we can't get rid of engineers altogether... But how long until my team of 5 gets replaced by a single engineer? Am I going to be the one to keep my job or one of the 4 to be let go?
We're literally trying to build an intelligence to replace us.
"Meat shields" has a nice physicality to it, though
Why though? I imagine things could also go the "google way" as well. The automated system makes the decision; and you just.. deal with the consequences if that decision is bad. We could just have an extended version of this dynamic as well: 3-4 entities with enough compute owning everything with no responsibilities; and when something goes bad, oh well. It's not like you can go to their competition, who also works the same way.
I think we saw many times that after a certain scale (after becoming, say, too big to fail), there is no bad decision you can't afford.
Anyway: The new job types might seem overspecialized now but history shows us this is indeed what happens as new industries open up. I think these predictions look quite solid.
If you go fast, you are bound to come across AI bugs later. Then you ultimately slow down to fix them. Which takes more time.
That black box will keep evolving. The AI interpreter will have to keep catching up with it.
"Specialization is for insects." (Or for someone pushing the boundaries of human knowledge.)
Spoilers for "How I Met Your Mother" ... but there's a character who has that kind of job, as a legal meat-shield. Now, ~10 years after airing, this funny clip feels like it would only need slight adjustments.
https://www.youtube.com/watch?v=8u62HptZ6TE
Now this guy was charging 1 drachma and 6 obols (apparently ~$100-150) per oracle. So that was his 'token rate'. And his clients the "fat-heads" (Lucian's phrasing not mine /g) were so taken by the scam that this guy earned up to 80,000 drachma per year! That's over 10 million bucks. For spewing b.s.
As to why all this is remotely related to OP's article, his mention of lawyers getting into trouble because of using LLM output instead of their brains ...
"By way of impressing the people still more, he announced that he would induce the God to speak, and give his responses without an intermediary ... These oracles were called autophones, and were not vouchsafed casually to any one, but reserved for officials, the rich, and the lavish.
"It was an autophone which was given to Severiann [4] regarding the invasion of Armenia. He encouraged him with these lines:
'Armenia, Parthia, cowed by thy fierce spear, To Rome, and Tiber's shining waves, thou com'st, Thy brow with leaves and radiant gold encircled!'
"Then when the foolish Gaul took his advice and invaded, to the total destruction of himself and his army by Othryades, the adviser expunged that oracle from his archives [!!!] and substituted the following:
"'Vex not th' Armenian land; it shall not thrive; One in soft raiment clad shall from his bow Launch death, and cut thee off from life and light.'"
[1]: https://en.wikipedia.org/wiki/Alexander_of_Abonoteichus
[2]: https://en.wikipedia.org/wiki/Lucian_of_Samosata
[3]: https://topostext.org/work/337
[4]: https://en.wikipedia.org/wiki/Marcus_Sedatius_Severianus