I've noticed this many times too, particularly recently, and I call it "Google Alzheimer's" --- what was once a very powerful search engine that could give you thousands (yes, I've tried exhausting its result pages many times, and used to have much success finding the perfect site many dozens of pages deep in the results) of pages containing nothing but the exact words and phrase you search for has seemingly degraded…
I'm not certain yet, but I think it has to do with systems relying more and more on the the system giving a high weighting on popular or frequent searches. In other words, these systems are filtering content by how frequent they are searched and annealing returns which have low frequency.
This makes sense from a machine learning perspective. If I want to build a system which returns a search quickly, then it will be biased towards pathways with strong weights. So in the end, systems would be biased against outlier searches and very specific terms which have low or weak search pathways. Effectively the system is getting really fast and good at giving you the most popular return, rather than a precise return.
The major problem there is that over time the search space will atrophy, much like memories do, and will kill off pathways which have low frequency. It's unclear if this is good or bad long term for a search engine, because it will remain popular for the majority of users, so long as their search terms and desired results live within the same space. In other words, we're creating a less diverse and more homogenous space by virtue of giving higher weights to more common thoughts/searches/desires.