Trust in Recommendation Systems

en in code • 3 min read
Mind the age! Most likely, its content is outdated. Especially if it’s technical.

On the Internet is so much information which no one can consume it all. That’s why almost every bigger page uses some type of recommendation system. To find what user likes and filter out undesirable content. For example, look at Facebook—you would need at least half a day to read everything that just your friends share. Google does that as well with Google Play Music, YouTube, or even maps or search engine! The last one is actually called a personalized search. Also, for some time, Twitter plays with „best Tweets“ or „in case you missed it,“ which totally changes your timeline—not even mentioning e-shops like Amazon or ad platforms.

The trend is clear. We all are just a bunch of numbers in different databases, and when we came to some web page, it will do some crazy math behind and show content which we probably want. The question is—can we trust in those numbers representing us?

I don’t know.

I currently work on one recommendation system at, and I also build my own „general Internet reader, which will sort automatically content by my preferences. “ I’m saying that only to mention that I know a little bit about those systems, and it somehow shapes my point of view about trust.

And my point of view is: I don’t trust them.

I’m a little bit scared of what some pages can do with those systems. They can basically change our thinking. They can keep us in some kind of social bubble. I know it’s the worst scenario, but there are also everyday scenarios like when I mark I don’t like something, and something is similar to it, there is a chance I will not see it! Or worst, I will not be able to find it easily.

And that’s why I block 3rd-party cookies. I block not ads but everything that can track me. I don’t follow anything at Facebook. I don’t use YouTube recommendations. I don’t care about Twitter’s best Tweets for me. Actually, I moved Twitter feed to my app. I don’t dislike songs at Google Music. I am careful about clicking to anything that could fire some kind of signal about me, some sort of number to equations that will try to do the best to recommend something else.

The craziest thing about that is probably that I do that also with systems I’m programming. At work, I don’t use it at all, and at home, I know the exact meaning of all signals, so I am very cautious about what I’m clicking at.

Actually, my little project helps me to understand this new era and see all problems about it. It’s tough to do it well, and I think it’s similar to security. When security is messed up, users are hurt. The same applies to recommendation systems. But there is a bigger problem—everyone is trying best to make the best possible security, but the best recommendation system does not mean better revenue. And that’s probably why generally I don’t trust them and try to avoid them.

There are only two systems I trust now. Google personalized search because I never had a problem with it (yet) and my own reader because I know every bit of it.

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