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Comment by snicksnak | Hacker News Reader

What would be the actual goal RL should aim for when being applied to the newsfeed? I understood RL for amazon aims for suggesting you things you're looking for or you're likely to buy. One might think this correlates directly with minimizing the time spent on browsing amazon. For the newsfeed it probably would be the complete opposite right, so maximizing the scroll of doom?

Also, from the transcript:

> when you go to Facebook, [...], you see all these posts from your friends

Maybe I'm an outlier but my newsfeed probably contains ~5% of posts related to my friends, birthday wishes included. I use facebook primarily as a news aggregator nowadays.

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> I use facebook primarily as a news aggregator nowadays.

Isn't this how people end up trapped in alternative-facts bubbles?

Depends which news he's taking about.

Sports news is usually pretty factual.

Thanks for reading or listening to the episode!

I think that is the hardest question, what to optimize for. Jason mentions that facebook employs social scientists who help set what the value is they are optimizing for.

> I don’t work on the social science part of it. We try to optimize and we do it on good faith that the goals we’re optimizing for are good faith goals. But I’ve been in enough of the meetings to see the intent is really a good intent. It’s just a thing that’s very difficult to quantify.

> But I do think that the intent is to provide that value. And I do think that they would trade some of the margin for the value in a heartbeat.

Not profit? I thought it was for profit.

Ads optimizes for profit, all other content is broadly optimized for meaningful social interaction and against problematic content.

https://www.facebook.com/business/news/news-feed-fyi-bringin...

https://about.fb.com/news/2019/04/remove-reduce-inform-new-s...

Ads 100% does not optimise for profit.

Source: I had a bunch of long conversations with FB Ads engineers about what they optimise for. I believe that it's a weighted sum over conversions, which seems like a better metric for an ads system (FB could increase profit in the short term by implementing price floors, but this wouldn't lead to more long term revenue, because advertisers would stop using the platform).

I was oversimplifying, but I stand by my words.

It does optimize for profit, just with extra steps. For most FB ads products (that you see in feed), advertisers pay based on conversions (views, clicks, likes, joins, purchases, etc.). So revenue is directly tied to conversions. Then there are extra steps weighing in revenue != profit, advertiser retention, repetitiveness, long term user value, etc.

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