Why does the YT algo bombard me with Niall Ferguson and Jordan Peterson videos? These may have been serious thinkers a long time ago, but now they’re hacks. And why does Amazon Music bombard me with filthy rap songs? I’m a man of God. I don’t want this crap, but sometimes I am so occupied by other priorities, sometimes all of my critical faculties are engaged in serving the One Truth that I just passively accept what the algo dishes out to me.
I’m the victim here!
Gemini says: It is incredibly frustrating when algorithms reduce complex changes in taste to “you watched this once five years ago, so you must love it forever,” or when they default to generic trending lists that clash with your sensibilities.
Here is why this is likely happening on both platforms and how you can try to fix it.
1. YouTube: The “Zombie Interest” Effect
You asked why you are being bombarded with Niall Ferguson and Jordan Peterson despite viewing them as “hacks” now. The YouTube algorithm is likely trapping you in a few specific loops:
The “Intellectual Dark Web” (IDW) Adjacency: YouTube groups channels into clusters. Ferguson (History/Geopolitics) and Peterson (Psychology/Culture) are tightly linked in the algorithm’s “Intellectual” cluster. If you watch any adjacent content—historical analysis, sociology, or even critiques of modern culture—the algorithm assumes you want the “heavy hitters” of that genre. It does not understand quality or nuance; it only understands topic correlation.
The “Hate-Watch” Trap: Algorithms cannot distinguish between “watching because I agree” and “watching because I am annoyed.” If you click on a video to see what they are saying, or if you watch a critique of them, the algorithm registers engagement. High completion rates (watching a video to the end) are the strongest signal. If you watch them to get angry, the algorithm thinks you are a superfan.
Legacy Data: YouTube has a very long memory. If you watched them years ago when they were “serious thinkers,” that data remains a core part of your profile unless you surgically remove it. The algorithm assumes your deep past interest is still relevant.
The Fix:
Nuclear Option (Watch History): Go to your History tab. Search for “Ferguson” or “Peterson” and delete those specific views. This removes the “seed” data the algorithm is using.
“Don’t Recommend Channel”: Click the three dots next to a recommendation and select “Don’t recommend channel.” You have to do this a few times, but it is the strongest “negative signal” you can send.
2. Amazon Music: The “Generic Drift” Problem
Amazon Music’s recommendation engine is notoriously aggressive about reverting to “Trending” or “Global Top 50” lists, which currently skew heavily toward explicit rap and pop.
The Autoplay/Station Default: When your specific playlist or album ends, Amazon defaults to Autoplay. If its confidence in your specific taste is low (or if the queue runs dry), it often defaults to the “lowest common denominator”—what is popular globally. Right now, that is rap.
The “Explicit” Filter Failure: Amazon’s explicit filter is known to be buggy. Even if you have it on, it sometimes plays “Radio Edits” of rap songs. The lyrics might be “clean” (bleeped), but the themes (which you likely find objectionable) remain, and the algorithm considers them “safe.”
Device Confusion: If you use Alexa/Echo devices, sometimes a voice command is misheard, triggering a generic station. Once one rap song plays through, the algorithm thinks, “Ah, they like this now,” and pivots your entire session.
The Fix:
Disable Autoplay: In the Amazon Music app settings, find “Autoplay” and turn it OFF. This stops the app from drifting into “Trending” garbage when your music ends.
Thumbs Down Aggressively: You must actively “Thumb Down” these tracks. Skipping them isn’t enough; the algorithm just thinks you weren’t in the mood right now. A “Thumb Down” is a hard “never play this.”
