All these jobs being "replaced by AI" are simply being eliminated with the consequences of them being eliminated ignored. Customer service jobs aren't being replaced by AI, companies, like Klarna, are just giving up on customer service and using AI to increase their perceived value rather than reducing it.
- The AI assistant has had 2.3 million conversations, two-thirds of Klarna’s customer service chats
- It is doing the equivalent work of 700 full-time agents
- It is on par with human agents in regard to customer satisfaction score
- It is more accurate in errand resolution, leading to a 25% drop in repeat inquiries
- Customers now resolve their errands in less than 2 mins compared to 11 mins previously
- It’s available in 23 markets, 24/7 and communicates in more than 35 languages
- It’s estimated to drive a $40 million USD in profit improvement to Klarna in 2024
Apparently it affected a Call-Center's (Teleperformance) stock [1].
[0] https://www.klarna.com/international/press/klarna-ai-assista...
[1] https://live.euronext.com/en/product/equities/fr0000051807-x...
However, I've encountered some pretty weird interactions with customer support over the years, including reportedly "The iMac can't do anything except browse the internet" when the demo unit on display behind them was running Nanosaur (a game); "we only support Microsoft Internet Explorer" when the customer support team didn't have that installed on their computers; «You need a Windows PC and an Android phone» from the German PostIdent people despite it being obvious they could talk to us while we used a Mac and that they knew this because they raised the issue spontaneously; and "yes, we will get your internet connection running by the end of tomorrow" from BT (it took them a month or two, by which time I had already cancelled; apparently someone put the wires in back to front).
It only took me explaining it 3 times, then telling him to "get a fucking person on the phone that understands tech", which he did and it was processed in minutes.
There's poor training, then there's just plain stupid.
Clarification: I'd given him the Service Tag, so he knew what device it was. He was insisting that I run the diagnostics and report the results, which is even dumber, in the end.
Also known as IPoV (IP over voice).
If AI costs were reaching very high levels perhaps they would try to make non-AI flows for standard processes. But I think that is unlikely given how cheap AI is vs smart people wages.
The cost of using generative AI to answer questions is orders of magnitude more expensive than using flows. Plucking a company out of thin air - Landbot [1] offers both flow and generative chats. For $100 per month you can have 2,500 flow chats, or 30 "AI" chats. That's nearly a 100x difference in cost. The risks are much higher too - with the flow builders if there's a sudden policy change or whatever then someone can just go into the system and edit it - with AI you'd have to retrain the model somehow. There's also no risk of hallucination with a flow based builder.
I'm not saying that Gen AI customer service chatbots don't have a use - what I'm trying to say is that in the real world, business would probably be better served day-to-day with just setting up decent flows in rules based bots. That's unsexy though - it doesn't attract tech talent, it doesn't get people promoted and it doesn't get shouted about in the press. It is, however, probably much better for the environment and the company's P&L (but possibly not their valuation if they're trying to ride the hype train).
The technology is clearly flawed. Regardless, a lower cost option (AI) is replacing a higher priced option (human labor). Ten years ago these tasks would have been handled by human employees or specialists.
There is certainly a history of this in the corporate world, when expensive union labor in Detroit is replaced by lower cost workers in Mississippi, manufacturing experts are forced to train their replacements in lower-cost countries, or entire engineering and customer service departments are shifted overseas.
I’m not calling to check my balance or get directions. I’m calling because your system did something wrong and needs to be overridden
And the thing is, the more the risk the less likely an LLM is going to be trusted to just make a decision.
For example, do you think an insurance agency would want an LLM to decide, on it's own, claim approvals? Can you imagine the headache for the insurance agency if the LLM approves the wrong claims or denies the wrong claims?
Or for a doctors office, Imagine AI diagnostics without a human. Can you imagine the headache for a hospital when an AI misses cancer? Or diagnoses a false cancer? It's bad enough when humans get that wrong, but now you have to explain to your legal team "We just left up the practice to the stats gods!"
To be slightly pedantic, the Web killed travel agencies for individuals who were mostly interested in booking flights, cruises, and big city hotels once making those bookings became easy on an individual level.
Companies absolutely still use corporate travel sites, for reasons good and bad.
And there are various types of specialist tour operators, arrangers of private trips, etc. who have on-the-ground knowledge of specific locations--and often won't even book things like air travel for you.
(More broadly, the Web forced travel agents of various types to add value above and beyond what a travel portal or a random travel agent could do because they were gatekeepers to the needed systems.)
You say this, but I sometimes worry that these issues are hand-waved away by decision-makers with, "oh we'll just have another LLM doing frontline claim support to verify these issues." It's the whole XML/violence thing, where the solution to XML-induced pain often ends up being more XML.
(From time to time I have some trivial questions, but not enough hundred valued bills, to ask actual doctor)
I agree with your point though, before starting on chemotherapy I would definitely shell out some money for opinion of a live doctor.
Half of the jobs will be replaced with AI soon. Writers? No need to have huge team, one senior is enough. Developers? Lawyers? Illustrators? Lay off half and replace them with AI tools!
My experience, having grown up when all customer service reps were people, is exactly what I stated above: this is just giving up on customer service.
Anyone who has ever called automated support knows this. When you reduce 10 people to 2 people and some chatbots now you simply have to wait 5x as long for customer support.
I worked at startup a few years back that refused to scale customer support so they could be forced to "automate" the process. The result? Customers got completely screwed over, but those customers weren't investors so who cares.
I can't recall a single time in my life were automated customer support solved my problem, it just kept me busy so that the 5x wait doesn't seem as long since I'm trying to navigate the labyrinth of a customer support decision tree to get my problem solved.
Did it, or is it like the automated elevator? The automated elevator didn't reduce the number of elevator operators, it substantially increased the number of elevator operators.
I think the subtle point is that not all humans will replaced -- it's just that a human and AI will be able to do the work of a few humans. Same work, less people.
People think AI technologies improve in a linear fashion. But there is nothing restricting this area of technology from non-linear progress.
Consider the failing prophesies of AGI as a precient example of what’s happening:
- It was 2015, and I’m reading articles about AGI being here in 2050 at least.
- It’s 2018 and everyone is talking about a few new research papers but secure in their predictions but maybe feeling like it is skewing towards the bottom end of that range (except for a few inspired nerds — my people — who boldly claim 2035).
- It’s 2022 and suddenly an AI is blowing people’s minds and we have the fastest growing technical product in the history of the world. Predictions are now 2030 for an AGI.
- It’s 2024 and people are debating if AGI has already happened and debating about the definition and many people are calling for an “advanced level” AGI in the next 2-3 years.
My point is that predictions of this technology have been terrible. Just like the worst. People have been off on every prediction by orders of magnitude.
So now every major tech company is blowing all their money towards AI, realigning their business towards hardware and software solutions and we’re in the middle of an arms race the size of Jupiter towards AI technology, and it’s happening across the world but definitely in both China and the USA where the stock market is going crazy and 25% of the entire markets growth is just nvidia’s massive growth (and those gains are basically powered by the leading ai training solutions).
So, the idea that somehow the technology isn’t going to replace people is asinine. This is the biggest, fastest tech wave I have ever seen, it’s growing geometrically, it’s funded by insane amounts of money and has most of the western and eastern world’s technology research focused on it, and has been wildly ahead of predictions from its inception.
Let’s get real about this. This is a bomb going off in slow motion and is set to interrupt employment and radically reshape society in a time scale that almost no humans can physically comprehend.
But more importantly the trend is accelerating and like most parabolic markets that don’t have physical limitations holding them back (like input materials for a gold rush) it could accelerate to literally crazy levels. There’s no restriction but breakthroughs here.
I’m aware of the current reality of the software systems and I know what I’m saying is futurist, but from a trend perspective we are way, way ahead of where we thought we were going to be and the trends point to railgun speed acceleration from here.
While I'm really impressed with ChatGPT, and am one of the people who regards it as meeting my prior definition of AGI[0], I can still see its current flaws, and do wonder if this is a similar case, where the first 90% needed a major breakthrough but once that was invented anyone could do it and many wanted in on the economic opportunity… but the second 90% turned out to be just as hard, and so was the third, … and you need at least six nines[1] to really replace humans in these roles.
[0] All three letters mean different things to different people. To me: it's artificial, it's much too general to count as a narrow AI, and I count it as intelligent because the things it can do were the things I grew up thinking were signs of intelligence, like speak Latin, do algebra, and answer trivia questions, and also things I added later like 'write code' and 'pass medical and law exams'; even though it gets the answers wrong sometimes, I don't think my standard was ever "must be perfect" because nobody ever scored 100% on exams at school either.
At its best (and it's weird that it even has a best and a worst), the free version of ChatGPT has given me better code than one specific real human I've had to work with, more if you also add in the students. (And at its worst, it gives me stuff that doesn't compile and wouldn't do what I asked even if I fixed the compiler errors).
[1] Assuming a driver is making 1 decision per second that has a serious wrong answer, it would take eight nines to have just under one serious accident in a lifetime of 1-hour-each-way commutes, 5 days a week, 50 weeks a year for 40 years. I suspect the actual time between opportunities for serious mistakes is less than that, but probably at least once per minute even on an empty road.
For an LLM, I don't know exactly how good they'll really need to be, all I can guess at is that they're not going to have more than one opportunity to seriously mess up per token.
But the question I would ask you is whether you are any barrier to simply scaling up the tokens on the existing technology? I don’t. I see us at the beginning of a ladder where the only input is capacity just like when Intel was young.
While breakthroughs can change the path, the truth is we have a fairly predictable step-by-step to much more capable systems without one just by scaling the size of the hardware.
Consider this argument:
1) I mean at core the crux of our learning is that predicting the next word may be what human thinking is generally about, and how our brain works, because that’s largely the innovation here.
2) Becoming better at doing that is entirely predictable and we can scale profoundly from current levels with hardware that we are putting into production right now and that we have already invented.
3) Therefore the path to next generation capabilities is relatively (and that’s important I admit) linear.
So prior to breakthrough, we have a simple path forward to what would be at peast fairly advanced capabilities of language and media prediction and manipulation.
Now your argument about progress is right. Predicting material progress of technology breakthroughs tends to be unpredictable and inherently dangerous, but we are in an accelerating trend and most of the time (big statement here, right?) the appearance of an acceleration trend tends to extend to continuance of the trend in a certain timeframe. At least that’s been the case with the “waves” of technology breakthrough since the Industrial Revolution according. I mean to invoke Smihula's theory of waves in this argument, since I know you’ll understand that.
Those last two arguments are statistically supported and quite logical. How smart does it need to be and how statistically probable are excellent points.
As an aside…
For me, one of the areas I am focused on and thinking about a lot is self-organizing AI agents.
Having worked a lot with large scale networks, agents and task specialized networked AI systems get me excited. My brain considers it a blue ocean opportunity.
The parallels between human civilization density and current learning about density of population in demographics driving essential human progress makes me believe there will be parallels in AI. The more, the more they will self organize into network effects, and the outcome of this, like human civilization, will be high quality and rapid progress. I am not a believer in one gigantic AI, but networks of networks self organized in a way where they self-optimize around goals and outcomes, and we are really just at the beginning of exploring this direction of the technology.
The biggest limiting factor to AI technology at this point is human input and the need for human oversight.
While that oversight is definitely necessary, once AI becomes self organizing and self-creating, progress should be profound.
Anyone who doesn’t think that’s going to happen needs to understand the nature of intelligence and realize it’s just a matter of time. You can’t go down this path in a meaningful way and repress only certain aspects of digital intelligence in the long term.
> But the question I would ask you is whether you are any barrier to simply scaling up the tokens on the existing technology? I don’t. I see us at the beginning of a ladder where the only input is capacity just like when Intel was young.
My expectation is that we need algorithmic improvements rather than scaling; AI can read approximately all of the internet, but current models need to actually do so just to reach the level of intern or fresh graduate. While this makes them superhuman in the breadth of skills they can perform, they need something else to improve the maximum quality in any given skill — in some cases, we can already train them on synthetic data or self-play, e.g. chess, though I don't know how broad an impact that would have.
But I do expect such algorithmic improvements, so in effect we are in agreement, if not in the details of how.
When it comes to hardware improvements, I'm not sure how that particular landscape will change over the next decade. Transistors are close enough to atomic scale they can't go on much longer, and Dennard scaling has long since stopped, but that doesn't mean nobody cares or that nobody is working on the energy efficiency. And if — just if, it isn't necessarily true — if human level intelligence needs a network with as many free parameters as there are synapses in a human brain, we're around 3-4 orders of magnitude away from that at present.
> I mean to invoke Smihula's theory of waves in this argument, since I know you’ll understand that.
Thanks, I was unfamiliar with it: https://en.wikipedia.org/wiki/Smihula_waves
> Having worked a lot with large scale networks, agents and task specialized networked AI systems get me excited. My brain considers it a blue ocean opportunity.
I think you're correct. The current zeitgeist is do-everything models, and the only blue ocean opportunities are found when you zig when everyone else is zagging, and vice-versa.
Although, be quick; if my cursory reading of Smihula's theory of waves was correct, you don't have much time before the current market reaches saturation, and moves on to the next thing.
If AGI is achieved, it will almost certainly be a surprise rather than be intentional.