Music preferences are emotional, subjective and full of social and cultural meaning. Practical experience building industrial recommendation applications suggests that user "trust" (a fuzzy concept combining user psychology with UI design and presentation) often overshadows actual results. What if making good music recommendations is actually a Dark Art and not a foundational problem of Information Retrieval Science? By tracing the beginnings of MIR, we present an early attempt at a Philosophy of Recommendation Science which tries to answer:
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Does recommendation science exist only as a practical application? Is it possible ground-truth metrics such as those proposed in the ISMIR 2001 Resolution don't actually exist? What types of solvable scientific problems should receive academic attention from the MIR community? Cee Lo's Teeth: Scariest in the entire history of recorded music?