How Using AI Tools Can Be Like Asking for a Book Recommendation From a Friend
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How Using AI Tools Can Be Like Asking for a Book Recommendation From a Friend
Today, I want to talk about the fuzzy art of book recommendations and how they relate to AI by posing a hypothetical: imagine you’re a lapsed reader and haven’t read fiction or followed books for a decade. You resolve to get back into reading and want to increase the chances that you become a fiction reader again by picking a good mystery because that’s a genre you enjoyed years ago. The trouble is where to start to find a mystery you’ll like.
There are lots of ways to approach this kind of problem. You could ask friends and family for recommendations, ask people online what they like, dive into reviews from publications you respect, or pore over sales charts. These are all common approaches, but each is limited in its own way. Your tastes may not align with those of people recommending books to you, reading lots of reviews takes time that might be better spent reading your book, and sales charts are a pretty rough approximation of quality. But because you want to get reading and not research endlessly, you choose a way to approach the problem, pick a book, and hope for the best, knowing full well that you’re operating on incomplete, imprecise inputs.