Ok. so now you got to understand that algorithms were generally viewed as positive back then.

The thing to keep in mind is that an algorithm is the instrument which optimizes for some incentive structure. In the early days of Google Search, the incentive was predominantly Adsense ads displayed alongside the search results. So to optimize views of these ads, the search algorithm had to be good enough so that people would keep coming back to Google Search for their web search needs. More users means more views means more eyeballs for ads.

What changed everything started with the incentive, when it became clear that marketers' demands to hyper-target consumers could be met if websites like Google or Facebook could learn more about users than just the search terms they entered. This is when user tracking took off, where the incentive is now to monetize user habits and identity, ideally cross referenced to their social media profiles or login details.

With that new incentive, the way to optimize that is to use tracking cookies and to expand Google Analytics and AdSense so they appear on even more websites, each of which would report data back to Google as users moved around the web. Note how this means the quality of web search is no longer important, because whether or not the user lingers on Google Search, their habits are still recorded and monetizable. In this sense, we would say that the algorithm's optimizing incentive is no longer aligned with the user's interests, such as privacy or performance.

Capitalism, as always, requires an examination into incentive structures, and this explains pretty much most of what Google has been doing vis-a-vis web behavior for the last decade, with the notable exception of their Gemini AI. I readily admit that I have no idea how AI fits into their web search business model, apart from being a loss leader that keeps up the impression that they're a major player in the current bubble. And I often wonder if they have any idea too.