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Yes, the more popular terms you search for, the more muddy the waters get.

If you search for anything related to sexuality and psychology, the results are littered with sites that were squatted for serving ads (i.e. no relevant content, just ads), poor quality articles with very low quality content (e.g. poorly formed Quora questions with no expert answers).

As with anything, you have to know what search terms for a given subject are good. For example, you'll get more objective answers the more academic sounding you are, because the fewer people have tried to occupy those search terms.

I agree with your experience - to me it also seems I used to enter a search phrase and get back a page of results that exactly match it, these days, I often get things that only vaguely thematically relate to my search phrase instead. Sometimes I would change a word in my search phrase or add an extra word to make the intent much more specific and still get essentially the same search results!!! Terrible, just terrible.

If I'm searching for a development issue, and my first results page contains 2-3 sites that 1-1 copy stackoverflow/github issues, then Google has failed. I doubt those can be more authorative than the original sources

Even programming related topics now return heavily SEOd sites with instead of high quality programming content. Often the SEOd content is not completely awful for these searches, but it’s usually not great & never as good as the best sites.

Most often it's a rip of StackOverflow surrounded by spammy ads

> I'm very often able to find exactly what I'm looking for after 15 minutes of massaging search terms on 3-4 different search engines.

If you are adjusting your query, then you are going to get different results, possibly including ones that contain the information you want (but not your original search terms).

We've been tweaking search terms to find what we were looking for since day one, what's changed the most it's that it's gotten far less likely that you'll realize you need to do this.

I think this is one of the real drawbacks of ML-algorithms, their failure modes are completely incomprehensible. Dumb algorithms we can grok, and learn to help along the way when it doesn't work. There is really no point where it will always work.

I think this is my biggest problem with how Google now works. It's always been disappointing when you didn't find what you were looking for. But you used to be able to examine the results and see how your search terms might not have been optimal, and adjust accordingly. It was the expectation that you'd have to tweak. Now, changing your exact search terms hardly seem to make a difference.

I think the major difference is that the algorithm used to highly weight matching of specific words and phrases from the search terms, so adding a word, re-ordering, and swapping for synonyms would drastically change the results. Now it seems they're using ML and natural language processing to try to actually understand what you're looking for and give it to you. You can change your search terms, but the language embedding doesn't change much, so the system is actually working as intended. I could see that this might actually be desirable for a large segment of the population who wants their search engine to "just work" in response to natural language queries. If the corpus being indexed was high quality, maybe this would be a good experience. But due to the ads, affiliate marketing, and blogspam that make up a large part of modern internet content, it's simply frustrating.

I wouldn't be surprised if they've done user testing that validates their approach. Programmers tend to be comfortable with the concept that a computer will do what you ask, even if it's not what you meant, but most people want to get the right results on the first try. The natural language/ML approach may be much more intuitive and forgiving in that regard. It's just not an approach that's compatible with the low average quality of the content being indexed, in that it takes away the authority of the user to improve their search results.

I think there's somewhat of a tradeoff in search performance between quality of results on the first try and ability to improve the results on subsequent tries, and google is now optimizing for the former at great cost to the latter. And honestly they're failing at both.

Either google failed, or the pop science listicles have won ... they're not passively being indexed, sorry you found them by mistake. They actively and aggressively create completely artificial content, tailored not at humans but at google, so that they can push the latest stupid ad for some telephone company on you.

It's like bitcoin if you want - they compete for something so useless the entire concept becomes a huge waste of time. Search engine SEO is like hashrate-dependent token mining: the only people who win are the farmers at the cost of burning their entire ecosystem.