It was "Blockchain" in 2017. "NFT" in 2020. "AI" in 2023. In a few years, there will be a new buzzword that companies throw a bunch of money at in hopes of being on the leading edge of the 'next big thing.'
While I appreciate the sentiment I think the key difference here is that ML is actually helping people do their work either better or more easily. While Blockchain and NFTs mostly amounted to autofellatio. Meaning those technologies are only helpful if you are interested in using those technologies. Whereas ML has clearly been helpful for all kinds of professions not just Brogrammers
To me it looks like an over estimation of the capabilities for the tech. Same kind of thinking that led to lawyers submitting fake cases as support in court. The current tech can be useful but has to be verified and generally tweaked a bit to be good enough. It certainly has room for improvement in quality and just not lying. Real world use has some copyright questions with what the training data was. Applying it to something creative is questionable and more or less feels like uninspired remixes.
Also the whole graphic is kinda suspect to me when "Blockchain engineers" is a job category and it's produced by an org working on AI.
Ah yes, because programming and critical thinking do not go hand in hand. We are going to have so many software vulnerabilities in the coming years. Better learn to hack, ladies and lads.
There's one thing that people tend to neglect that I like to remember--it's going to be awhile yet before an AI can walk up to your door, knock, come in and find the specific nature of a plumbing/electrical/HVAC or whatever problem, and then diagnose and fix it. And then get safely home without getting hit by a truck or vandalized by bored teenagers or both.
That's such a complex suite of different "problems" that we're going to need nothing less than a general AI to navigate them all. Thus, one of the last jobs that'll be replaced is various kinds of repair professionals that do house calls. The constant novelty of the career, where every call is its own unique situation, is a nightmare for a current-method AI.
I kind of feel like it's a bit overwrought - and not supported by current tech anyway. I could predict where the tech will go, but I don't think that's possible to do in a reasonable way over a useful time-span for this.
Lets look at the proposed affected jobs(I'll leave out the ones I just don't have enough knowledge about to even hazard a guess):
Interpreters + Translators: I haven't tried GPT for this, but I imagine it's likely not too much more affecting than google translate. For people and situations where machine translation is good enough - this has been happening for quite a while. I have my doubts that this will change the trajectory of that field. Translation seems like something that you can't "edit after the fact" - you have to do the whole translation anyway to see if the machine translation is right or missing important non-literal parts.
Writers and Authors: I can see this speeding their work up, and enabling people who might have story ideas and be a decent editor but not a good first draft writer to become authors. However, writers have been dealing with both lowered standards for technical writing and content glut for many years - I don't think this changes that appreciably.
Public Relations Specialists: I feel like this is massively devaluing the psychology and experience in PR. It might well replace press release writing, but I just bet there's more there than is obvious to everyone.
Tax Preparers: If you're doing fine with TurboTax - you've been doing this for decades now. If you can't solve it with existing traditional tax software, it's often because you just aren't sure about vague tax rules, or complex tax rules. And you usually want someone else to take on some liability and ability to represent you if you're audited. I don't see how GPT changes this fundamentally.
Mathematicians: Really? It's horrible at math.
Proofreaders and Copy Markers: Also really? I feel like for a while at least there's going to be more proofreading of the output of GPT for factual content and style.
It's mostly BS. The only ones that really need to worry are jobs where doing things accurately don't really matter and where that work is very time consuming to do or there's an absolute ton of it (and also doesn't involve physically doing anything).
Types of jobs impacted would be tier one call center staff whose primary role is to function as a filter to tier two. Technically their job could be replaced with a pre-recorded message already, but people tend to ignore those so they're less effective than having a person just read a script to the caller. Other impacted jobs would be movie extras or very cheap actors where a wooden or slightly off performance could be ignored.
Lastly some jobs will be changed but not replaced. A lot of the initial work of things like concept artists, editors, certain kinds of script writers, and analysts will be generated and then they'll spend their time refining or fixing that initial copy. Ironically this will most likely lead to even more demand for those kinds of jobs as finding and fixing mistakes in generated content can be more time consuming than doing it right the first time.
The big elephant in the room of course is that it's going to be very expensive to run these systems, and you're going to need a whole group of high skill specialists to maintain and operate them. Just like self driving trucks you're just replacing a large group of low skill cheap workers with a medium sized group of high skill very expensive workers. Ultimately this will be far more expensive for companies, but for those that can afford it the increased volumes will offset the increased costs.
Re: proofreading this could maybe work for technical writing for ESL authors, but i won't trust chatGPT with technically confidential data. So we're back to square one
I think you’re underestimating the impact here. It obviously won’t replace all of the jobs in these fields, but even shortening or eliminating enough tasks will have impacts on employment levels. If fewer people can do the same amount of work, some of those people will be laid off.
One thing to note is that making an industry more efficient (like translating, which gpt is really good at, much better than google translate but not necessarily better than existing tools) comes with a decrease in the amount of jobs. Tech doesn't have to eliminate the human portion, but if it even makes one more human twice as efficient in their job, thats half the humans you need doing that job for the same amount of work output.
That being said this is not a great infographic for this topic.
I think the utility for technical papers and documents may be a bit overstated as well. There's usually templates for these documents if possible. If not, the topic is broad enough that I don't think you could provide a suitable prompt to generate meaningful text.
Course that's just my 2 cents as someone who's approaching this as highly skeptical. We should see how it performs in these areas and test it out. It's just premature to make employment or policy decisions, imo.
Because blockchain is useless and no one is investing in that space anymore because GPT is the new shiny object. Kind of hard to become a blockchain engineer when interest rates aren’t 0%, investors are doing due diligence, and the marketing buzzword train has left the station. Even clueless VCs and MBAs now know blockchain was all hype around selling libertarian fantasies to people who don’t read books.
You're going to have an unacceptably high failure rate as you attempt to trial-and-error your way through all the lower-probability problems. Meanwhile, independent research paths aiming at general AI, which absolutely could handle all these problems, is racing you.
An hvac company that is able to adopt AI for 1st call processing and scheduling will be able to eliminate a number of jobs and remain open 24x7. They will undercut their local competitors, and the hvac techs will find themselves out of a job or working for their competitor soon.
Small companies won’t be able to compete.
I’m all for this but we need to offset these immense productivity gains with economic safety nets. I don’t know how the next 100 year will look if we don’t adopt UBI, universal healthcare, and some amount of subsidized housing.
if we don’t adopt UBI, universal healthcare, and some amount of subsidized housing
This has been my stance for years. Automation is coming for all of us. The only reason LLMs are so controversial is that everyone in power assumed automation was coming for the blue collar jobs first, and now that it looks like white collar and creative jobs are on the chopping block, suddenly it's important to protect people's jobs from automation, put in safety nets, etc, etc.
This image/report itself doesn't make much sense – probably it was generated by chatGPT itself.
"What makes your job exposed to GPT?" – OK I expect a list of possible answers:
"Low wages": OK, having a low wage makes my job exposed to GPT.
"Manufacturing": OK, manufacturing makes my job exposed to GPT. ...No wait, what does that mean?? You mean if my job is about manufacturing, then it's exposed to GPT? OK but then shouldn't this be listed under the next question, "What jobs are exposed to GPT?"?
...
"Jobs requiring low formal education": what?! The question was "what makes your job exposed to GPT?". From this answer I get that "jobs requiring low formal education make my job exposed to GPT". Or I get that who/whatever wrote this knows no syntax or semantics. OK, sorry, you meant "If your job requires low formal education, then it's exposed to GPT". But then shouldn't this answer also be listed under the next question??
"What jobs are exposed to GPT?"
"Athletes". Well, "athletes" semantically speaking is not a job; maybe "athletics" is a job. But who gives a shirt about semantics? there's chatGPT today after all.
The same with the rest. "Stonemasonry" is a job, "stonemasons" are the people who do that job. At least the question could have been "Which job categories are exposed to GPT?".
"High exposure: Mathematicians". Mmm... wait, wait. Didn't you say that "Science skills" and "Critical thinking skills" were "Low Exposure", in the previous question?
I've seen GPT struggling with pretty basic maths and "abstract" tasks such as making the letters add up in an anagram. Math requires insight that a language model cannot posess. I don't really get why people like infographics so much. The format usually just distracts from the data presented, which is convenient given that the data is usually garbage too.
Math requires insight that a language model cannot posess
Amen to that! Good maths & science teachers have struggled for decades (if not centuries) so that students understand what they're doing and don't simply give answers based on some words or symbols they see in questions [there are also bad teachers who promote this instead]. Because on closer inspection such answers always collapse. And now comes chatGPT that does exactly that instead – and collapses in the same way – and gets glorified.
Amen to what you say on infographic content as well 😂
I think realistically, it’ll be decades before people comfortable with GPT enter the workforce and actually make most of those jobs redundant. It’s like when the internet blew up and older managers had no clue what to do with it. They hired web developers and eventually, the web developers wrote things like Wordpress so the staff could edit the web site themselves.
And guess what happened? The web devs didn’t get laid off. Staff kept sending the web developers changes in Word documents for like a decade before a generation of young people comfortable with posting text on the web entered the workforce and actually wanted to do it themselves. (Even then, the web developers didn’t disappear but, instead, were freed to build more complicated things.)
So, basically, I think the concepts there are fine but that it’ll take a generation for businesses to fully take advantage of the new tech. Some firms will embrace it quickly but these things almost always take longer than technology enthusiasts assume.