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

theguardian.com

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

#51

Post by nradov »

tzahola wrote: post #50
nradov wrote: post #24

This is a good way to quickly build an MVP to gauge customer demand before incurring the time and expense of building a real scalable product.

So, deceiving your customers about how their data is being handled is a “good MVP”. With this much cynicism you must be an “enterpreneur”.

Where is the deception? Why should the customers care how the service is implemented on the back end? Unless the service lies and claims the data will never be seen by humans then they're not doing anything unethical. All that matters is whether customers are getting value from it.

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

#53

Post by shawn »

See also: the front page of HN. You didn’t think that was an algorithm choosing which stories you see, did you? :)

It works well. And considering how much effect HN has on our daily lives, it’s neat that the algorithm reduces to “this human has good taste.”

I see no reason why HN won’t be around for decades. And that’s exciting. It’s the only newspaper that feels like a community.

This used to feel strange — if you think about the position of influence and power HN commands, it’s hard to feel ok about ceding control to a handful of people, no matter how benevolent. And on certain topics this has indeed been an issue —- if a certain behavior or conversation isn’t tolerated on HN, it’s easy to feel like you’re a misfit who doesn’t belong in tech, or even that you don’t identify with the tech community.

One way to become comfortable with this situation is to trust incentives, not people. The only way HN wins is if HN stays fascinating. It’s why most of us keep coming back: to monitor the pulse of the tech scene, or to learn physics factoids[1], or to spot a new tool that saves you hours.

And that’s why HN can’t be fully automated. Which stories fascinate you? If you could write an algorithm to generate an endless stream of interesting content, you’d have invented an AI with good taste. And for the moment, that’s beyond our capabilities.[2]

[1] As the earth orbits the sun, the area swept out by the triangle formed by the sun->earth->earth3WeeksLater is equal to the area of the triangle during the next three weeks, and the next three weeks after that, and so on. Equal time periods = equal areas. That’s why the earth moves faster when it’s closer to the sun: it has to cover a greater distance in order to sweep out the same area as during the previous 3 weeks. This gives you an intuition about how gravity behaves. And with a slight tweak it also holds true for e.g. an ice skater twirling around. If you stick your leg out while spinning, your leg sweeps out more area than when it’s near your body. That’s why you spin more slowly: if you’re sweeping out more area per time period, your rotation must slow down proportionally. (This is conservation of angular momentum, dressed up in intuitive clothing.)

[2] This is in contrast with sites like YouTube, which give an endless stream of interesting videos. Part of HN’s strength is it’s unified front page. We all see the same thing. And that’s why writing an algorithm to make the front page interesting is much harder than creating a personalized neural network trained to show you all the interesting things you haven’t seen yet.

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

#54

Post by lordnacho »

nradov wrote: post #51
tzahola wrote: post #50

Earlier quoted context omitted.

So, deceiving your customers about how their data is being handled is a “good MVP”. With this much cynicism you must be an “enterpreneur”.

Where is the deception? Why should the customers care how the service is implemented on the back end? Unless the service lies and claims the data will never be seen by humans then they're not doing anything unethical. All that matters is whether customers are getting value from it.

Sure, if you present it that way, it's fine. As in "I'll do xyz for you, somehow".

If you say you're taking people from A to B in a motor-powered cab but you actually come to pick them up in a rickshaw, that's wrong. People will naturally form expectations about the ride based on what you say.

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

#55

Post by googlemike »

raverbashing wrote: post #18
xamuel wrote: post #7

Absolutely unsurprising given the current state of hype. How to get rich: (A) Start a page that applies photoshop effects to user-uploaded pictures. (B) Secretly accomplish A using low-paid grunts. (C) Claim it's done with AI, obtain a billion dollars of VC money

You don't even need to do it secretly, just say it's the next step. See: Uber

But Uber has what seems to be world class Machine Learning (If that's not the heart of AI, what is?) lab. I am not well versed enough to compare it to Google's, or openAI, but is surely seems like they are at least trying to push the research envelope?

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

#56

Post by ekianjo »

bocklund wrote: post #49
davnn wrote: post #12

Earlier quoted context omitted.

> 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 heard a good set of definitions. Data science: observing trends in data Machine learning: humans develop models that are fit to data to make predictions AI: Computers make modeling decisions entirely autonomously. No human input. Dump data, get predictions.

So would you consider unsupervised classifiers to be AI?

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

#57

Post by ekianjo »

edanm wrote: post #46
ekianjo wrote: post #40

Earlier quoted context omitted.

> "AI is whatever hasn't been done yet." If you can't replicate what a human do, it's not AI. The fact that we can only beat humans for very, very narrow applications/games and that we don't have a generalized model for learning is a clear failure of the AI hype.

It's totally valid to define AI this way. But just keep in mind, when most people talk about AI, they're knowingly talking of something much more limited. So you're going to constantly have communication failures with people who are defining AI differently than you. (Many people nowadays use the term AGI [Artificial General Intelligence] to mean what you think of as AI, btw).

Yeah I know about AGI but I dont like that term because it implies that the classifiers we have nowadays are good enough to be called "intelligence". They are just statistical models with great number of layers, nothing else.

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

#58

Post by tzahola »

nradov wrote: post #51
tzahola wrote: post #50

Earlier quoted context omitted.

So, deceiving your customers about how their data is being handled is a “good MVP”. With this much cynicism you must be an “enterpreneur”.

Where is the deception? Why should the customers care how the service is implemented on the back end? Unless the service lies and claims the data will never be seen by humans then they're not doing anything unethical. All that matters is whether customers are getting value from it.

Because if a service offers to automatically tag my photos, I don’t expect random people looking at them. In fact, I don’t want anyone looking at my family photos other than those whom I explicitly gave permission to do so.

Same applies to my voice recordings. Same applies to my receipts. Same applies to my health data.

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

#59

Post by davnn »

ekianjo wrote: post #57
edanm wrote: post #46

Earlier quoted context omitted.

It's totally valid to define AI this way. But just keep in mind, when most people talk about AI, they're knowingly talking of something much more limited. So you're going to constantly have communication failures with people who are defining AI differently than you. (Many people nowadays use the term AGI [Artificial General Intelligence] to mean what you think of as AI, btw).

Yeah I know about AGI but I dont like that term because it implies that the classifiers we have nowadays are good enough to be called "intelligence". They are just statistical models with great number of layers, nothing else.

Maybe you want to read: https://en.m.wikipedia.org/wiki/Model-dependent_realism

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

#60

Post by YeGoblynQueenne »

faeyanpiraat wrote: post #44
davnn wrote: post #34

Earlier quoted context omitted.

That's called transfer learning in ML and we are not very good at it, yet.

I’m not sure about the quality of my linked article but it seems like that humans becoming good at chess does not noticeably improve their other skills. They will simply be better at chess. So our expectations might bee too high against AI getting vastly better only by doing better transfer learning. http://theconversation.com/does-playing-chess-make-you-smart...

Learning chess will make you better at other board games, even if it doesn't improve, say, your maths or language skills. For instance, chess may teach you lessons about sacrificing assets to earn a reward later on, or lessons about material advantage, tempo, controlling the board and so on, that can be applied to many different games. That counts as transfer learning and it is something that statistical machine learning cannot do at all, basically (i.e. a new model has to be trained from scratch for each different game).

As an aside- you might argue that there are common elements of board games' design that make it easier to reuse knowledge. However, statistical machine learning systems can still not transfer knowledge of one game to others, even given the common design elements that should make it easier.

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