I use Google Photos to back up all my cell phone camera photos. It automatically generates galleries from trips I make, and selects the "best" photos. I still

I use Google Photos to back up all my cell phone camera photos. It automatically generates galleries from trips I make, and selects the "best" photos. I still review them, and decide if I agree on Google's ML agorithm's opinion of best (from a series of snaps of someone's face or a landscape) While it's really good at removing blurry shots, aligning crooked ones, and discarding those where someone half-blinked, it cannot AT ALL tell the difference between a weird interesting endearing facial expression and a weird strange off-putting facial expression. And that's because the real data is not in the image. It's in the personality that I know of the person. A picture of a person smiling who I know is dour or unhappy is the one I want. Meanwhile for a person who's incredibly photogenic and always has a flawless smile - but is usually consistent and bordering on insincere - I'd prefer a candid shot where they're not looking their best - but the real personality that maybe only I know of them is shining through. These are not objective truths. My favourite photos of my wife are ones she hates. And it's not even about having a different SELF-image from those that others have of you - we also like different photos of our dog, and of our mutual friends. No ML model will be able to pick that, and unfortunately this isn't just a case of "let's give them more data and wait". If we trust the algorithms to make these decisions for us, we will just encourage the rounding of all the uneven edges of our world until we settle on a bland average existence where everyone has the same idea of what a "cute baby" looks like. This is already happening with information bubbles on Facebook and Twitter. The trend needs to be reversed, not doubled-down on.