Recommender systems have a terrible public image. many people see algorithmic recommendation as harmful. Allegations include:
- they create filter bubbles, where clusters of people are shown only stuff that confirms their biases
- they boost low-quality but engaging content. E.g. false info, click bait, rage bait
- anything else?
the filter bubble idea is weak (see the Reuters article, maybe that recent study on Twitter, the panel thing with Rasmus Kleis Nielsen). however the opposite thing might be true: social media and/or their recommendation algorithms cause people to see a larger diversity of opinions. however the end result is still the same: the content from the opposing side ends up just ethrenching people in their beliefs. Basically we’re going from “algos cause filter bubbles” to “algos don’t cause enough filter bubbles”.
I’m reminded of a Scott Alexander post about trapped priors. I think the idea is that for people to change their mind, it helps if they see ideas from the other side which aren’t too far in the other direction. it needs to happen gradually. boil the frog basically. so a potential problem with social media and/or algorithms is that it creates this structure where you end up seeing the most extreme/worst takes from the other side, and it drives polarization.
(that actually seems pretty credible to me, for the record–but I’m not sure how much of it is unique to social media or algorithms vs traditional media/society)
see also: age of algorithmic anxiety
I don’t have a strong opinion on whether social media as it exists today has been net positive. I am after all working full time on building alternatives to the current landscape.
But I do strongly believe that recommendation algorithms can be a force for good.
I think a big part of the problem is that recommendation algorithms are understandably associated with Big Tech. I think a lot of the concern isn’t about recommendation algorithms per se, it’s about who’s in charge of the algorithms. people have a sense that they’re being manipulated by large corporations. Big Brother.
As a thought experiment, imagine you’re a programmer. Say you created your very own recommendation algorithm for your own personal use. It downloads news articles from a large variety of sources and suggests ones for you to read. you make it suggest articles that haven’t had many shares on Twitter, so the algorithm helps you to find things that you otherwise might not have seen. When you get a suggestion, you give a rating on how good of a suggestion it was (which doesn’t necessarily correlate with whether or not you agree with the article!) Over time, the algorithm learns to suggest things that have a higher chance of receiving a positive rating, while still recommending articles a variety of sources.
if you had the time to do all that, it seems quite plausible (probable, even!) to me that the algorithm would be beneficial. There’s no conflict of interest; you’ve designed it to meet your own needs. Hopefully this illustrates that recommendation algorithms aren’t inherently bad; it’s just a question of how they’ve been designed and whose interests they serve.
Coming back to the real world in which the vast majority of people are not programmers with infinite free time, there are two questions:
is it possible to alter the social media landscape so that people have confidence that the algorithms they use are prioritizing their own interests?
Is the potential benefit of recommendation large enough that this would be worth the effort? (as opposed to abandoning recommendation altogether)
I think yes! The key is competition. Although we can’t get all the way to the extreme of “everyone is a programmer who wrote their own recommendation algorithm,” we could go a lot further in that direction than we currently are. The social media landscape should consist of lots of smaller services instead of a few huge services. If people are unsatisfied with one service due to algorithmic anxiety (or any other reason), they can switch to a new one. If lots of people have algorithmic anxiety, that creates a market opportunity for services which solve that problem (either by not using algorithms, or by finding ways to increase users’ trust in their algorithms–different services can try different approaches!).
(I guess that’s a response to question #1)
- discuss question #2 (or is it unnecessary? the main point here is that we need more competition, and even–especially–people who don’t like recommendation algorithms can agree with that. With more competition, the question of “can algorithms actually be good” can be left to the market–if they can be, then there will be small services which continue to use them)
- discuss the “how” of #1 more. How in-depth? That’s the entire focus of all my work currently. Maybe just give an abbreviated version.
- What exactly is the takeaway of this article? is it just “we need more competition”? that’s disconnected from the current title (“in defense of recommendation”). Do I actually care about convincing people that algorithms can in fact be good (question #2)? I think yes. Who am I trying to convince? people who might build these recommender systems? people who might want to try the recommender system(s) I’m building? (probably the latter I guess)
- mention The Toxoplasma Of Rage | Slate Star Codex – Regardless of if algorithms are involved or not, information flow always has and always will be governed by complex system beyond any one person’s control, and the “default” system is not necessarily good! Even if you get all your information from chronological RSS feeds, how did the creators of those feeds get their information? etc