Perhaps you value novelty more than the average person. What might not be "adequate" for you might very well be adequate for a huge portion of people.
Throughout this comment you mention several potential goals of content producers (being memorable, advancing the art, changing someone's life, etc.), but you make no argument for why those goals ought to be prioritized over other goals, other than the implication that you personally prefer those goals.
It isn't about what he values versus what you value. What the author complains about are well known problems with recommendation engines. Take the naive reco algo - "You just bought a 50 inch Philips TV. You might also like - 50 inch Sony TV, 50 inch LG TV, 50 inch Samsung TV, 50 inch ..." - See the problem ? I already bought my fucking TV, you can't expect me to buy more & more of the same or similar goods.
Then there's the CF algorithm & its variants, with well known problems - namely, they don't actually match content to one's preferences. Typically, one POV dominates across the board due to the sparsity of the matrix, & getting the diversity required for the matrix to fill out takes a long long time and a very large number of people with diverse opinions. You mistakenly give a five star rating to Godfather & you are bombarded with mafia movies for a long time. You attempt to confuse the system by giving Pretty Woman five stars as well. Then the system tries to gamely proceed by suggesting "Those who watched Godfather AND Pretty Woman are more likely to watch - So I married an Axe murderer."
Can't win.
There are auto-complete screenplay software that basically make a composite of the top 100 best selling screenplays & do what in the industry is called a flip. Namely, change male to female, winner to loser, comedy to tragedy etc. These data-driven screenplay software might suggest that if you take the ladies from Thelma & Louise & replace them with grizzly old men, you get Unforgiven.
There are lyric generation software with the same flavor, umpteen loop generators & infinite jukeboxes, content recommendation systems along the same lines - since you just starred this code sample on angular, you will enjoy this github repo on react,...
Hopefully you see the downside.
But that's hard, while stupid hill climbers and infinite monkey machines are easy. It will keep working until people tire of it, which judging from the abysmal sales in music is happening. Won't be long before people also stop going to see Batman Redone.
[0] That said, I've seen lots of counterintuitive but very real phenomena regarding user behavior, so I won't claim to be that confident about this being ineffective. Perhaps people return TVs a lot and buy other ones. I don't have the data.
Imagine a machine that could make procedurally generated movies, would that interest you?
Stories have already been distilled to the Seven Basic Plots [1]
Novelty needs repetion in order to be novel.
[1] http://tvtropes.org/pmwiki/pmwiki.php/Main/TheSevenBasicPlot...
Better in what way?
Let's say Movie A is a well loved blockbuster that millions of people see and enjoy. Movie B is a very mixed piece that isn't really enjoyable to watch, but "advances the art" in some key ways. Movie C is an even more well loved blockbuster than movie A, which even more millions of people will see and enjoy, but that was only made because the director was one of the few that really understood Movie B.
The argument, as I understand it, is that Movie B is somehow objectively better than Movie A and Movie C, because it enables Movie C to exist, even though Movie C isn't actually good, because it doesn't advance the art? That doesn't make sense to me. The journey has value only to the extent that the destination is valuable, no? If C is trash, then what was the point of "advancing the art" enough that we could make C? (Conversely, if we're discussing "advancing the art" in a way that isn't required to make anything anyone wants to watch, then we're clearly not discussing finding a global maxima, right?)
B exists for D, which will be better than B.
Isn't this the history of progress in creative human activities?
Perhaps that's true with all else being equal, but clearly all else isn't equal.
> I guess that what he meant is that global maxima is better than local maxima (which is clearly true), and data-driven vision is a hill climbing strategy, thus locking you into a local maxima.
My issue is that none of those examples are backed by any evidence that they are not doing a decent job of finding a global maximum.
You're pretty much suggesting that using strong feedback to force culture to stay within a tiny area of the total possible cultural phase space is just as interesting as allowing chaotic exploration of the entire space.
It's not just an argument against creativity, it's an argument against invention in general.
>My issue is that none of those examples are backed by any evidence that they are not doing a decent job of finding a global maximum.
That's the thing about global maxima - you only know that you've found a global maximum if you've explored the entire space.
Otherwise you've just stumbled across a local attractor, and you're stuck in a loop around it.
This isn't even a good analogy, because cultural attractors are contingent, and they vary over time. They're also unpredictable.
The reason they capture attention isn't because they're maxima in some analytic sense. They become found maxima because they summarise some aspect of human experience, so they appeal to a lot of people at once.
The spectrum of possible maxima is mysterious and not understood, which is how you get - say - Harry Potter coming out of nowhere and captivating a generation.
Culture is music, not a sine wave. You don't just want a single signal - you want a mix of related-but-different signals running all the time.
I am not very educated in the field of art. I always find orders of magnitude more beauty in nature than in art.
In contrast, being data-driven means selecting goals that are easy to measure without any attempt to justify them as intrinsically more valuable than other, more difficult to measure goals.
The reality is that goal-selection is always at least somewhat arbitrary, and words like 'data' and 'science' can be and often are used as a cudgel anyone who might support different (arbitrary) goals.
