Comments on “Who is in control of AI?”

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The c word

A 2023-03-15

Great series. Your analysis here seems applicable to any corporate structure, so I am a tad surprised to see no mention of capitalism or corporations more generally.

recommender algorithms vs social networks

Gary Drescher 2023-03-29

Suppose FB, Twitter, etc. eliminated their recommender algorithms and presented you with posts and reposts only from people whom you choose to follow. Then would most people (especially those who are more prone to reflexive outrage) see a substantially different distribution of messages than now? Or would we have the same feedback loop of extreme posts propagating by virtue of their very provocativeness, maybe taking 10% longer to reach saturation or something?

These aren’t rhetorical questions, and I don’t know how to answer them. But it’s not obvious to me that our current level of polarization, as unpleasant and dangerous as it may be, is more extreme than the much lower-tech polarization of the US in the 1960s or 1860s, or the world in the 1930s, etc.

Extreme ads, user control

Pattern 2023-03-29

This is old news, but:

Extreme ads can be an issue as well as extreme content.

That said, if people have more control over their feeds, that puts the choice about polarization (and concentration) in a different place. Block lists already exist, as do more technical tools for users (though this seems to vary by platform). Although social media feeds may be monolithic today*, having different accounts (and being careful with the subscriptions) seems like it can address this, if people want to engage with politics, but not all the time. This seems like a good thing, as does fixing the incentives from having one party with both feed control/moderation and also getting money from the ads. (Mastodon doesn’t do ads.)

*My rss feed reader has folders, so it’s in a better spot.

How Engagement Optimization Fails Users, Creators, and Society

David Chapman 2023-03-29

Hi Gary, nice to see you here!

Yes, the extent to which recommenders harm individuals and/or society is disputed and difficult to quantify (as I acknowledged explicitly).

This very recent long article by Arvind Narayanan, who is a careful and deep thinker, is the state of the art consideration I think: “Understanding Social Media Recommendation Algorithms.”

The “How Engagement Optimization Fails Users, Creators, and Society” section is particularly relevant.

Pattern — thank you!

re: recommender algorithms vs social networks

Gary Drescher 2023-03-30

David: Thanks, good to be here! I appreciate your insights on these issues, and the clarity of your presentation. And thanks for the link; it does make a persuasive case that recommender algorithms make a big difference in what posts get widely seen by others who wouldn’t seen them by network chains (though it’s still, as you agree, hard to quantify what effect that has on social polarization, compared to old-fashioned chains of transmission).

Pattern: Agreed, ads matter too (though in the specific case of weapons ads, I’d be unhappy with FB pushing those even if the ads were untargeted, or targeted only via opt-in user-specified categories of interest).

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