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The rise of 'pseudo-AI': how tech firms quietly use humans to do bots' work

theguardian.com

101–110 of 145 posts

Re: The rise of 'pseudo-AI': how tech firms quietly use humans to do bots' work

#101
post #93

Am glad this is highlighted now. Back in 2015, when we wanted to build an meeting scheduling bot, we naively thought we could use only machines to get the job done. 3 months later we realized that was no way feasible, not then not in the next 10 years. So the common feedback we got was to just use low cost labor in India/Phillipines to get the job done. To us, that was a no-go because we kept privacy as the top crite…

It's great that you stuck to your guns, but there's another ethical path forward: transparency. Many companies already pay third party employees to look at their schedule, so it's not a non-starter. And there are a few VCs out there that understand training costs for AI and are willing to engage with a journey that includes them - as long as the cards are on the table.

What we need is a set of accounting metrics about the cost of training and the rate of improvement, so that VCs can get comfy with how to make projections rather than choosing between buying snake oil and nit participating in the AI Dev cycle.

PS - emphatically not taking aim here at your specific decision, OP. Startups have different opportunities and interests, and these decisions are tough. I'm sure you know better than I do whether the ethical wizard-of-oz model above is relevant to you in particular.

Re: The rise of 'pseudo-AI': how tech firms quietly use humans to do bots' work

#102
Sounds a bit like the stripe (or is it square) story where every bank trnsaction was humanly done before they got the rights to automate it. I'm not surprised and i find it considerably smart considering all the money pouring into everything with a a machine learning buzzword attached to it.

Re: The rise of 'pseudo-AI': how tech firms quietly use humans to do bots' work

#103
A lot of this comes from the availability of cheap hype-driven capital. The way it's supposed to work is that AI lets you replace expensive human labor with cheap computers so that a job that might've cost $10 in wages instead costs $0.0001 in server time. The way it actually works is that you tell a bunch of investors that you've got an AI that reduces the cost of X by a factor of 10,000, they give you $100M in capital, and now you have 10,000x the amount of money available, so you can pay the original $10 in wages and worry about how to actually reduce the cost of X by 10,000 later, usually once it's clear that no more funding is forthcoming.

This is not really a healthy state for the economy, but seems to be how every technology wave happens. The real innovation will come when the cheap money dries up.

Re: The rise of 'pseudo-AI': how tech firms quietly use humans to do bots' work

#104
post #99

Earlier quoted context omitted.

Well the idea is that all emerging ideas with broad appeal go through the Hype Cycle. I don’t know that AI is different or dangerous in that regard.

I'm not of the opinion that it is dangerous as an idea, but rather that the intentional deception I see on the AI topic is dangerous (not to mention unethical). I can't think of a single example of an "AI" company I talked with who did not know that they were explicitly exaggerating their claims and capabilities for the express purpose of attracting funding and fueling the hype fire. The solid tech startups I've seen…

Not to mention that AI as we define it does not actually exist yet. Anyone who uses that term is doing so dishonestly. Show me any intelligent code and I'll shut up. Until then I call BS on anything that's claims to be powered by AI.

Re: The rise of 'pseudo-AI': how tech firms quietly use humans to do bots' work

#105
post #12
post #9

AI is nonsense. Dijkstra was right. I'm not saying that silicon/mechanical intelligence isn't possible. I'm unaware of any physical law that precludes it. But what we currently call "AI" is just the pathetic fallacy run wild. All that said, multidimensional data-driven linear recognizers are pretty impressive.

> AI is nonsense. Dijkstra was right. Define AI first. One of the first few lines on Wikipedia about AI: The scope of AI is disputed: as machines become increasingly capable, tasks considered as requiring "intelligence" are often removed from the definition, a phenomenon known as the AI effect, leading to the quip, "AI is whatever hasn't been done yet."

I think the key concept here is Moravec’s Paradox. People believing in the "AI is whatever hasn't been done yet" quip are moving the goalpost in the definition.

Consider speech recognition. Obviously an AI problem solved, right? Except, the AI problem and what the current solutions are solving are two different things. The AI problem is understanding and appropriately reacting to spoken words, as if a human was on the other end. Current implementations are glorified pattern matchers run over clever hashes of sound recordings. There is no understanding happening, there are no concepts forming within the machine (and the understanding is not back-fed into pattern matcher to correct the sensory input on the fly). The difficult parts, the ones that make speech an AI problem, have been entirely sidestepped with mathematical tricks. It sort of works, but its scope is nowhere near the original AI problem.

Similar analysis can be made for anything that is mentioned with the "no longer AI" quip. Can a DNN recognize a hot dog? Sort of, for some definition of "hot dog", only if input images are clear and similar enough to the training set. It's a cute trick, and you can make a business out of it if you control enough of the environment around the system, but it's still nowhere near what we mean when thinking about AI recognizing objects.

Re: The rise of 'pseudo-AI': how tech firms quietly use humans to do bots' work

#106

A lot of this comes from the availability of cheap hype-driven capital. The way it's supposed to work is that AI lets you replace expensive human labor with cheap computers so that a job that might've cost $10 in wages instead costs $0.0001 in server time. The way it actually works is that you tell a bunch of investors that you've got an AI that reduces the cost of X by a factor of 10,000, they give you $100M in capi…

What they do could be a viable thing to do, if getting your customers to spend their own money to switch from a manual system with spreadsheet files sent over whatsapp to using your API will enable you to be the only player who has a huge dataset with real customer data, which you can use to understand which subset can actually be automated using existing technology, and automate only that using deep learning or whatever (for which you want the biggest dataset you can get), and keep doing the other stuff manually. You win by making people switch to your API, getting network effects, etc.

If you don't cut corners in the way you do the manual tasks and you charge enough to cover your costs, and enough tasks can be automated so that using your service is not more expensive than not using your service, you're ok. But you probably don't have the margins the VCs want.

Re: The rise of 'pseudo-AI': how tech firms quietly use humans to do bots' work

#107
post #17

Earlier quoted context omitted.

There is a difference between labeling training data and just using humans to do the work. Some things cannot be achieved yet even with lots of labeled training data but companies are pretending they have solved hard ML problems at a high level of performance when the technology and research aren't there yet.

But why should it matter for customers who does the job? I mean, if you don't tell anybody, and pretend it's 100% AI then it's bad, but if it "will eventually become AI", and your investors and everybody interested in the technical details know how it's actually done, then what's wrong? A true "AI" should be able to pass a Turing test, so for the customer, it should be indistinguishable, and shouldn't matter. Of cour…

Ask yourself the reverse question - if they already have a working, useful service that's human-powered, why are they lying by saying it's done by AI? Answer: because they're trying to get things they're not entitled to - like better funding, better sales, more attention. In other words, they're trying to cheat other people out of their money or time.

Re: The rise of 'pseudo-AI': how tech firms quietly use humans to do bots' work

#108
Some colleagues of mine talk about the prevalence of companies doing this man behind the curtain thing all the time while claiming that there solution is AI/cognitive. When we come across examples of this happening we just refer to that Seinfeld Moviefone episode and say 'Why don't you just tell me [foo]' - or whatever the "AI" is trying to solve.

https://www.youtube.com/watch?v=gSQ6q_rGpI8

It never fails to get a good laugh.

Anyway, I think that human interaction for the training aspects of AI to prepare data, label examples, test models, etc. is really hard to automate entirely and should be considered part of the development process. The execution side of an application component that is marketed as AI/cognitive however is not true AI unless it is totally free of human interaction.

Re: The rise of 'pseudo-AI': how tech firms quietly use humans to do bots' work

#109
post #93

Am glad this is highlighted now. Back in 2015, when we wanted to build an meeting scheduling bot, we naively thought we could use only machines to get the job done. 3 months later we realized that was no way feasible, not then not in the next 10 years. So the common feedback we got was to just use low cost labor in India/Phillipines to get the job done. To us, that was a no-go because we kept privacy as the top crite…

It's great that you stuck to your guns, but there's another ethical path forward: transparency. Many companies already pay third party employees to look at their schedule, so it's not a non-starter. And there are a few VCs out there that understand training costs for AI and are willing to engage with a journey that includes them - as long as the cards are on the table. What we need is a set of accounting metrics abou…

Thank you. The latter point about accounting metrics that you mention is very valid. I will think on these lines. I am very much interested in reaching out to VCs who are supportive and understand training costs for AI. If you know of any please do point out.

Re: The rise of 'pseudo-AI': how tech firms quietly use humans to do bots' work

#110
post #108

Some colleagues of mine talk about the prevalence of companies doing this man behind the curtain thing all the time while claiming that there solution is AI/cognitive. When we come across examples of this happening we just refer to that Seinfeld Moviefone episode and say 'Why don't you just tell me [foo]' - or whatever the "AI" is trying to solve. https://www.youtube.com/watch?v=gSQ6q_rGpI8 It never fails to get a go…

Even if the program was totally "free of human interaction", it shouldn't be marketed as "cognitive"—an exceptional word that requires exceptional evidence, when used in context of software.

Otherwise, it's all bovine manure.

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