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ML is not that good at predicting consumers' choices

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

#91
post #79
post #57

Earlier quoted context omitted.

This is incorrect. You can predict many things that drive incremental revenue lift. The simplest: Predict what features a user is most interested in, drive them to that page (increasing their predicted conversion rate) -> purchases that occur now that would not have occurred before. Similarly: Predict products a user is likely to purchase given they made a different purchase. The user may not have seen these incremen…

ML is useful for many things. I'm asking the question of whether prediction is useful, and whether it is accurate to describe ML as making predictions. The reason to raise those questions is that for many people, the word prediction has connotations of surveillance and control, so it is best not to use it loosely. The meaning of the word "predict" is to indicate a future event, so it doesn't make grammatical sense to…

You can predict a present state of affairs if they are unknown to you.

I predict the weather in NYC is 100F. I don’t know whether or not that is true.

Really a pedantic argument, but to appease your phrasing you can reword my comment with “We predict an increase in conversion rate if we assume the user is interested in feature x more than feature y”

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

#92

Earlier quoted context omitted.

If your schedule is so irregular/erratic, how is a ML algorithm supposed to be able to learn it? Sounds like in that case it's better to just control things manually.

ML can learn patterns that humans might not be aware of, so you there might be certain things that happen that show you will be on a mission to East Asia for a couple days.

Only when data is supplied to it to match the trained pattern,

ML is pattern recognition. Anything outside of that is still AI, but it isn't ML. I can think of very few feature sets we could supply to help predict someone will be deployed to East Asia for a few days other than scraping calendars and mail for religious and military organizations.

From a design perspective, Nest and others are either additively learning in situ to enhance a base model or they are working from a base model that doesn't directly learn, just classifies workflow to categorize observations on a base model. I doubt heavy training is occurring where the Nest and similar is treated as the central compute node.

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

#93
post #57
post #53

Earlier quoted context omitted.

If your ML model is able to predict what consumers are going to buy, the revenue lift would be zero. Let's say I go to the store to buy milk. The store has a perfect ML model, so they're able to predict that I'm about to do that. I walk into the store and buy the milk as planned. So how does the ML help drive revenue? The store could make my life easier by having it ready for me at the door, but I was going to buy it…

This is incorrect. You can predict many things that drive incremental revenue lift. The simplest: Predict what features a user is most interested in, drive them to that page (increasing their predicted conversion rate) -> purchases that occur now that would not have occurred before. Similarly: Predict products a user is likely to purchase given they made a different purchase. The user may not have seen these incremen…

Exactly. I know someone who does this for a certain class of loans, based on data sold by universities (and more).

Philosophically -- personally -- I think this is just another way big data erodes our autonomy and humanity while _also_ providing new forms of convenience. We have no way of knowing where suggestions come from, or which options are concealed. Evolution provides no defense against this form of manipulation. It's a double edged sword, an invisible one.

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

#94
post #44

Is there much that is good about predicting this stuff? I find Amazon loves to tell me to buy ... the thing they know I just bought and you don't need more than one of ... I hardly ever get ads or offers for things I want. How do you mess that up?

Google seems like they target by age, gender and income rather than by interests. Sometimes it's convinced I'm a yuppie and keeps showing me luxury cars, personal care/beauty products and high end electronics (when I have zero interest in any of those products).

Ironically I find the "dumb" ads on cable tv news to be a lot more effective since they have to target by interests.

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

#95
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

Part of the reason they're horrible is because people don't have consistent interests. I might be interested in raunchy content right now, but I won't be a few hours later. What determines whether I'm interested in the former is outside of the control of these algorithms - they don't know all of the external events that can change my current mood and preferences. As a result of this it makes sense for people to have many profiles that they switch between, but AI seems incapable of replicating this manual control (so far).

Sometimes I want to watch videos about people doing programming, but usually I don't. When I do though, I would like to easily get into a mode to do just that. Right now that essentially involves switching accounts or hoping random search recommendations are good enough.

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

#96
post #22

You just bought a washing machine... could I interest you in a washing machine?

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.

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

#97
post #75

Some years ago, I worked on a team "Ads Human Eval" - we had raters hired to do A/B testing for ads. These evaluated questionaires carefuly crafted by our linguists, and then analyzed by the statisticians providing feedback to the (internal) group that wanted to know more about. So the best experience was this internal event that we had, where the raters would say that certain Ad would not fare well (long term), whil…

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)

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

#98
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

I think YouTube has given up on figuring me out.

They mostly offer stuff I’ve already watched or stuff on my watch list.

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

#99
post #36
post #22

You just bought a washing machine... could I interest you in a washing machine?

GPT can solve this! I prompted it with "Sarah bought a washing machine and a ". It completed "dryer.". Another "If you buy a hammer you might also want to buy " -> "a nail". Ill forgive the singular. Just to be clear those are not cherry picked - they were my first two attempts.

> GPT can solve this! I prompted it with "Sarah bought a washing machine and a ". It completed "dryer.".

The most natural interpretation there is that Sarah bought a washing machine and a dryer simultaneously, not that, after buying a washing machine the month prior, she was finally ready to buy a dryer.

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