I also don't think math is to be blamed -- human psychology plays an important role -- i.e. I may be interested in software-dev stuff or in startups stuff, but not every hour of every day. Basically I'm inclined to read such stuff only in the morning, while drinking my coffee (the perfect time of day for big plans).
But in the afternoon I prefer reading articles about my OTHER (lighter) interests / hobbies, like photography. And I also prefer getting stuff solved, like finding an electrician to fix the poor wiring in my house or searching for gifts for my wife/child.
For any person on this earth, immediate interest in something is relative, based on time of day, time of year, mood, current needs, current problems, current hobbies, etc...
A good recommendation engine is practically unfeasible -- because if it cannot anticipate your future desires, both short-term and long-term, then it's useless; because people "search" for stuff as soon as they realize they have a new need/desire, and then it is too late to make a recommendation (at this time, the user's history is only useful to "understand" / parse the search query).
Recommendations need to happen before the user searches for stuff.
For example -- I searched for books on drawing / colors on Amazon, and bought 2. Amazon should have anticipated that I may like getting into photography, as they do know a lot about me, but it didn't, even though Amazon's recommendations are some of the best. Now that I already bought stuff, I don't care about special offers on the same kind of stuff that I already bought.
Also, people with "hackish" attitudes have done pretty amazing stuff btw, contributions to AI included -- software isn't just math, it's also biology / chemistry / physics / psychology / philosophy, amongst others.