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ML is not that good at predicting consumers' choices

statmodeling.stat.columbia.edu

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Re: ML is not that good at predicting consumers' choices

#201

Post by gwbas1c »

mgraczyk wrote: post #70
gwbas1c wrote: post #68

Earlier quoted context omitted.

> Always interesting to see outsiders writing papers about this, using anecdote and unrelated data (mostly political and real world purchase data in this case) to argue that ML doesn't make useful predictions. Meanwhile I look at randomized controlled trial data showing millions of dollars in revenue uplift directly attributable to ML vs non-ML backed conversion pipelines, offsetting the cost of doing the ML by >10x.…

The key insight missed by this paper (and people from the marketing field in general) is that cases like that are extremely rare compared to easy to predict cases. They don't matter right now at all for most products, from the perspective of marketing ROI. Also ML can predict that, BTW. Facebook knows you are connected to your parents. If the pillow seller tells Facebook that your parents bought the pillow, then Face…

> Also ML can predict that, BTW. Facebook knows you are connected to your parents. If the pillow seller tells Facebook that your parents bought the pillow, then Facebook knows and may choose to show you an ad for that pillow.

I think you're letting your imagination run away, and I think you're trying to exceed the limits of the kind of information that you can collect and act upon.

What you're trying to do is mind reading, and computers physically cannot do that. (Nor can people)

Re: ML is not that good at predicting consumers' choices

#202

Post by dreamcompiler »

wumpus wrote: post #185
stackbutterflow wrote: post #179

Earlier quoted context omitted.

You don't even that to go as high as 10,000. Imagine someone suddenly doing the job of 10 persons, that's entire teams being decimated. Go to a job board and imagine 9 of out 10 job postings not existing. How much harder it'll be to seek another job.

Decimated means 1/10 killed. I know people don't use it properly, but it's worth knowing.

I learned it in the context of signal processing, where it means the inverse of the Roman connotation (keep every tenth vs. destroy every tenth).

Re: ML is not that good at predicting consumers' choices

#203

Post by dreamcompiler »

Slackwise wrote: post #10
cj wrote: post #3

While not exactly aligned to the research, I've been surprised how poor Nest Thermostat's learning feature is. The main selling point for Nest is having a "learning thermostat". Perhaps my schedule is just not predictable enough, but the auto-generated temperature schedules it generates after its "learning" period is not even close to what I would manually set up on a normal thermostat. Maybe I'm just an "edge case"…

"Why am I sweating right now? Oh, the Nest set the temperature too high again!" And then after a few instances, I just turn off all the automation and set up a schedule like normal. Same with the "away from home" which seems to randomly think I'm away and I have no idea why. Oh, and the app doesn't show me filter reminders, only the actual device, which I never touch all the way downstairs. There's not even any statu…

I bought one back before Google bought the company, because it seemed like a well-designed product with a good UI. In addition to the problems you mentioned, it was constantly updating its firmware. That sometimes bricked the device temporarily and sometimes it changed the UI so I had to relearn how to use the device. One update removed the ability to manually set "away" mode. I finally wised up and reset the thing so it couldn't attach to my wifi any more. Which made the app useless of course.

Then it became clear the thermostat wasn't getting enough power from my 2-wire thermostat transformer and that made it even flakier. I finally threw it away and replaced it with a $20 dumb thermostat, which will still be working fine after the zombie apocalypse. No more Nest products for me.

Re: ML is not that good at predicting consumers' choices

#204

Post by dreamcompiler »

fshbbdssbbgdd wrote: post #51
cj wrote: post #3

While not exactly aligned to the research, I've been surprised how poor Nest Thermostat's learning feature is. The main selling point for Nest is having a "learning thermostat". Perhaps my schedule is just not predictable enough, but the auto-generated temperature schedules it generates after its "learning" period is not even close to what I would manually set up on a normal thermostat. Maybe I'm just an "edge case"…

Not only does the Nest ignore my preferences, I think it actually lies about the current temperature. Example: Setting is 72, reading is 73. AC is not on, I guess the thermostat is trying to save energy. I lower setting to 71, reading instantly drops to 72! I don’t think it’s a coincidence, this has happened several times.

> Setting is 72, reading is 73. AC is not on, I guess the thermostat is trying to save energy.

This can be explained by hysteresis [0], which all thermostats use to avoid cycling the A/C too fast.

But the second part where the reading drops instantly is strange. Sounds like some kind of software heuristic where they're trying to make the user feel more comfortable about the hysteresis interval. Or something.

[0] https://en.m.wikipedia.org/wiki/Hysteresis

Re: ML is not that good at predicting consumers' choices

#205

Post by dahfizz »

jsjohnst wrote: post #148
kristopolous wrote: post #141

Earlier quoted context omitted.

Which is an extremely trivial check to add - if you got assigned that ticket, you'd probably point it at like 2 or so hours. However, they've been like this for over a decade so it's likely there intentionally. here's one way that could be possible: There could be some popular third party service that's integrated on many e-commerce sites that sells this information and doesn't actually give a damn if you bought the…

> Which is an extremely trivial check to add - if you got assigned that ticket, you'd probably point it at like 2 or so hours. Yep, totally a 2hr task for an engineer who works on homedepot.com to “check” that you bought a fridge from lowes.com after you first price shopped the other site. Also a two hour task for a Google engineer to know you bought one in person at Best Buy after researching online first. Yes, ther…

Amazon consistently shows me ads for products I bought on Amazon. Don't bother talking about edge cases when the simple case doesn't work at all.

Re: ML is not that good at predicting consumers' choices

#206

Post by incone123 »

sandworm101 wrote: post #195
incone123 wrote: post #182

Earlier quoted context omitted.

If that's so, why is the luggage weight allowance applied cumulatively across multiple bags for one passenger? And why is it different between airlines and between ticket classes?

Because first class baggage is labelled and treated differently so it never gets bumped. The lower/higher numbers are also uses to force the penalty payments, something first class travellers don't want to deal with at check-in.

This seems unrelated to your original point about safety of baggage handling workers. The purpose of a max single bag weight is to facilitate handling. The purpose of a per passenger baggage allowance surely is to manage total plane load, hence high excess charges.

Even first class passengers can't turn up with unlimited luggage but, in my experience relating to families flying between London and the middle East, have household staff who make arrangements and coordinate with carriers.

Re: ML is not that good at predicting consumers' choices

#207

Post by kristopolous »

jsjohnst wrote: post #148
kristopolous wrote: post #141

Earlier quoted context omitted.

Which is an extremely trivial check to add - if you got assigned that ticket, you'd probably point it at like 2 or so hours. However, they've been like this for over a decade so it's likely there intentionally. here's one way that could be possible: There could be some popular third party service that's integrated on many e-commerce sites that sells this information and doesn't actually give a damn if you bought the…

> Which is an extremely trivial check to add - if you got assigned that ticket, you'd probably point it at like 2 or so hours. Yep, totally a 2hr task for an engineer who works on homedepot.com to “check” that you bought a fridge from lowes.com after you first price shopped the other site. Also a two hour task for a Google engineer to know you bought one in person at Best Buy after researching online first. Yes, ther…

We're talking the basic case. I visit website X, look at item Y, purchase item Y, then get advertising for item Y for the next Z days.

You can throw your hands up and yell impossible by looking for outliers with just about anything

Re: ML is not that good at predicting consumers' choices

#208

Post by mgraczyk »

mellavora wrote: post #188
mgraczyk wrote: post #58

Earlier quoted context omitted.

The actual conclusion of the study is so absurd that it's not worth engaging with seriously. That is, to maximally understand, and therefore predict, consumer preferences is likely to require information outside of data on choices and behavior, but also on what it is like to be human. I was responding to the interpretation from the blog post, which is more reasonable.

ok, let me help you out: http://www.stat.columbia.edu/~gelman/ https://en.wikipedia.org/wiki/Andrew_Gelman which would give strong prior evidence that the author's writing is not absurd. Note also that he has strong connections to a leading psychologists meaning he has some background on human choices and behavior. https://en.wikipedia.org/wiki/Susan_Gelman Please be careful with attack statements such as "so absurd…

He didn't write the paper I'm criticizing

Re: ML is not that good at predicting consumers' choices

#210

Post by ljw1001 »

malkia wrote: post #130
Melatonic wrote: post #97

Earlier quoted context omitted.

I dont think most people are arguing that machines will replace everyone anytime soon - it is that they will replace a huge portion of people. If one person can do the job of 10,000 by being the tweaker / approver of an advanced AI that is still 9,999 jobs eliminated. That might be hyperbole (you still probably will need people to support that system)

I agree, but it's true that some jobs should not simply exists. To this day, if I go to our airport in Sofia (Bulgaria), and my baggage is over the limit of 20 or was it 25kg I have to go to another place, pay for it and come back (why? bureaucracy - not only I have to do it, but I'm slowing anyone waiting for me to this - it's like 25-50 meters one place to the other) Unlike Frakfurt, Munich or Heathrow airport wher…

Jobs don’t just exist to provide the best possible consumer experience. They are fundamental to individual feelings of self worth and societal stability. Unless you have a replacement for those things, endless automation may ultimately do much more harm than good - your inconvenience in Bulgaria not withstanding
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