Live data from Hacker News

ML is not that good at predicting consumers' choices

statmodeling.stat.columbia.edu

211–220 of 228 posts

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

#211

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. 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.

I haven't worked at Amazon in this vertical so if people know definitively feel free to correct.

The Amazon case could be the same problem I discussed before. Third party sellers can pay fees to promote/boost their listings on Amazon so ultimately the same incentive structure holds if there's fees for impressions and not just sales.

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

#212
post #29

I can personally vouch that Amazon, Twitter, and YouTube all do horrible horrible jobs predicting my taste. And they have got worse over the years, not better

Youtube's is actually pretty surprisingly good, in my experience. After years of use, it consistently filters out all the absolute trash I don't want to see, and recommends me things I do actually want. It's not perfect, but it often directs me to channels I wouldn't have heard of otherwise that have solid content.

It often finds a video I would like and throws it on my front page. I avoid it for awhile thinking it wouldn't be a good fit (I don't recognize the creator, bad thumbnail/title, unclear why the content would be of interest to me, etc) but find it was great and I should have watched it days ago.

If I log out of my account, the front page of the site is just awful, makes me want to throw up.

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

#213
post #193

Earlier quoted context omitted.

I buy a package of underwear. All I see for next three weeks on my browser is close ups of men’s briefs. It’s embarrassing, when associates glance at my screen.

Kind of your fault - you're buying your underwear on a work device and you don't use an adblocker.

1. Not a work device.

2. We are discussing how ads are selected for presentation.

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

#214
The title is oversimplified clickbaity, and their actual finding is [from abstract], and my reaction below:

Our main conclusion is that for most of the more interesting consumer decisions, those that are “new” and non-habitual, prediction remains hard. In fact, in many cases, prediction has become harder due to the increasing influence of just-in-time information (user reviews, online recommendations, new options, etc.) at the point of decision that can neither be measured nor anticipated ex ante. Sophisticated methods and “big data” can in certain contexts improve predictions, but usually only slightly, and prediction remains very imprecise—so much so that it is often a waste of effort.

My initial reaction on skimming it is "savvy consumers are becoming increasingly desensitized to a sea of Facebook ads, Amazon fake reviews and rigged star ratings, undisclosed compensated influencers", aka the "unprecedented information environment" as the author describes things. I wouldn't call an Amazon review or FB ad/influencer post/affiliate link "information" as distinct to "this laptop has a rated battery life of 18h" or "this toaster comes in the following 5 color choices"; it's simply an influencing attempt; whether those contain any information (/misinformation), and whether users trust that they contain accurate information, seems to be something the study doesn't want to look into. Really the authors seem to be giving a very-judgment-free pass to anything calling itself "information".

Consider "unprecedented information environment" could also characterize the 2016 and 2020 US elections, 2016 UK Brexit referendum and 2022 Philippines election: "it is important to first understand how consumers make choices, particularly in the current information environment in which they have access to an unprecedented amount of information at the time they are making decisions." [obviously third-party political advertising is far less trustworthy than consumer advertising, but still].

What if the authors merely succeeded in proving that the rise in targeted influencing attempts has rendered the public more wary of targeted influencing attempts?

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

#215

Earlier quoted context omitted.

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 re…

It's not mind reading, I explained how it works.

You are friends with your parents on Facebook. Your parents buy the pillow. The pillow seller tells facebook that your parents bought the pillow.

Now Facebook knows that somebody who is your friend recently bought the pillow. Facebook may decide to show you an ad for that pillow because somebody who is your friend recently bought the pillow.

The result may look like "mind reading", but it's actually very simple in terms of actual prediction.

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

#216

Earlier quoted context omitted.

Yea machines did that to laborers and computers did that to clerks, yet people still have jobs.

People today have jobs, but what we don't hear about are the people who were made redundant and the suffering they went through. They're just forgotten about, or even ridiculed, like the Luddites are today. For the Luddites who were not shot by the state or factory owners, or were tried and literally executed by the state for machine breaking, the rest of them and their families lived and died in utter destitution ha…

>but were made redundant in the wake of the financial crisis and economic restructuring.

The recession didn't make anyone redundant. The people that were laid off were laid off because the people hiring them ran out of money to pay all of their employees. Yes, it is true "many people are laid off because they are redundant", but in the wake of the recession, companies ran out of money and they had to stop doing things that cost money, and then lay off people that did those things.

Also, to be clear, automating work didn't cause those people to lose their jobs - because their jobs were stopped.

Also, I'm very sorry for all of the people that were impacted by that recession. It was big amd a lot of people hurt because of it.

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

#218

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. 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

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

Show me where I did that?

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

#219
post #130

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…

There are reasons for it. Probably less so today now that most people just credit cards, but having one place that handles money solves some issues as opposed to having a bunch of places handling money. While there are some jobs that can go the way of the buggy whip maker, this was probably not a good example.

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

#220

Earlier quoted context omitted.

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

> You can throw your hands up and yell impossible by looking for outliers with just about anything Show me where I did that?

[deleted]
Post reply on HN