I was a fan of Google and Google search from the beginning because their algorithm for prioritizing search results made sense to me. Pagerank was similar to citation frequency which academics recognize as an indication of the importance of their work. Pagerank counted the number of links to a given web page and the number of links to the linkers. Translation – how popular is your page and how influential are the linkers linking to your page. As a way to count something to estimate perceived value in a way that is possible to calculate on a massive scale, this makes about as much sense as anything.<\/p>\n\n\n\n
However, Page, Brin, and colleagues were not content with this and continually searched for other signals that could be calculated and applied. At some point, they found ways to count things about the behavior of their customers. This is where there should have been some thought as to what their goal really was. Was it to return the most generally valued information or the most personally valued information? Engineers lack some of the insights of psychologists. Or, perhaps, those who want to make money don\u2019t mind taking advantage of multiple human biases. It is hard to know how important decisions are made.<\/p>\n\n\n\n
Of course, most have at least some understanding of what Google has done. We either don\u2019t care or don\u2019t know what can be done about it. There are alternative search engines that don\u2019t accommodate personal biases – e.g., DuckDuckGo<\/a>. <\/p>\n\n\n\n I wish Google would offer its own solution. They already do this with their news service <\/a>– you can get news based on personal biases or a more independently selected set of stories. Google could offer a personalized search service and an approach more based in something like PageRank.<\/p>\n