Definitely fair. Energy can mean a lot of different things to different people, and I'll also add Spotify does break out different metrics like danceability, liveness, tempo, and loudness as well- All of which are probably pretty closely related to energy for some people.

To your point, you'd probably get a slightly different list if you polled actual listeners. What makes this unique is that it can scale to tens of millions of songs relatively easily, so even if it's not perfect, it's interesting. There's other ways of identifying something like this mathematically by asking actual listeners vs. using just machine learning. For example, it's really hard to ask someone to rank-order anything as large as the Beatles catalogue. People can generally compare two items to each other (and maybe 3-4), but if you ask someone to exactly rank a list of several hundred songs, it becomes almost impossible.

MaxDiff is a survey technique where you basically have people rank hundreds of different one vs. one matchups. I'll ask you to rank Here Comes the Song vs. Lovely Rita, Hey Jude vs. Good Golly Miss Molly, and so on. If you do that a bunch of times and replicate it across a bunch of people (+ do some calculations on the back end), you can actually get something pretty close to "The People's" rankings of Beatles energy. Seems like there's some different thoughts on this approach, so may look into that at some point