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
ML is not that good at predicting consumers' choices
41–50 of 228 posts
Re: ML is not that good at predicting consumers' choices
#42It reminds me a lot of other populist folk-science belief, like vaccine hesitancy. Despite overwhelming data to the contrary, a huge portion of the US population believes that they are somehow better off contracting COVID-19 naturally versus getting the vaccine. I think when effect sizes per individual are small and only build up across large populations, people tend to believe whatever aligns best with their identity.
Re: ML is not that good at predicting consumers' choices
#43Always 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. I…
Re: ML is not that good at predicting consumers' choices
#44I 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?
Re: ML is not that good at predicting consumers' choices
#45I 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 had just preordered novel 9 of The Expanse, and I got an email recommending something else from the same authors: novel 8 of the Expanse. A more sensible recommendation engine might have assumed that someone who preorders part n+1 of a series may already have part n. Not to mention that Amazon should have known that I already had novel 8 on my Kindle.
I guess generating personalized recommendations at scale is still too expensive. We just get recommendations based on what other customers with vaguely similar tastes were interested in.
Re: ML is not that good at predicting consumers' choices
#46I 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
Literally to the point where YouTube never pulls me down into the rabbit hole anymore, I watch one video because it was linked from somewhere else, then I bounce.
Re: ML is not that good at predicting consumers' choices
#47You just bought a washing machine... could I interest you in a washing machine?
Re: ML is not that good at predicting consumers' choices
#48Always 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. I…
I don't think you know who andrew gelman is. Additionally, that's not the conclusion derived from this study.
Re: ML is not that good at predicting consumers' choices
#49Always 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. I…
Have you ever put this data up against something similar to the peer review system in academia, where several experts from a competing deparment (or ideally competing company) try to pick your results apart, disprove your hypothesis?
Re: ML is not that good at predicting consumers' choices
#50Always 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. I…