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When a new technology comes along no one knows what ideas are good and what ideas are bad, so people try a bunch of things and most of them aren't very useful and the few that are become standardized. In the case of UX stuff like visualizations users also learn the grammar of the technology and get used to seeing things done in certain ways, which makes it harder to do things differently.

So basically there's less innovation in data visualization because we mostly figured out how to solve our data visualization problems. If you look at the history of printed visualizations I think you'd find a similar pattern. The only somewhat recent innovation I can think of there is the violin plot, which became possible due to advances in statistics that led to probability distributions becoming more important.

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Sometimes something is a "solved" problem. There hasn't been a lot of innovation in say, firearms, because we pretty much figured out the best way to make a gun ~100 years ago and there isn't much to improve.

Not everything needs innovation, and trying to innovate anyway just creates a solution in search of a problem.

They said the same thing about hash tables. Innovation from a single individual blew away (no pun intended) all prior expectations and opened an entirely new baseline understanding of this.

Just because we THINK we’ve solved the problem doesn’t mean coming at it from an entirely different angle and redefining the entire paradigm won’t pay dividends.

Sure, and no one is saying that people should stop experimenting and testing out alternative approaches. But we wouldn't expect to see experimental approaches displacing established conventions in mature use cases unless they actually are major breakthroughs that unambiguously improve the status quo. And in those situations, we'd expect the new innovations to propagate rapidly and quickly integrate into the generally accepted conventions.

But there's obviously going to be something analogous to declining marginal utility when trying to innovate in mature problem spaces. The remaining uncaptured value in the problem space will shrink incrementally with each successive innovation that does solve more of the problem. So the rate at which new innovations propagate into the mainstream will naturally tend to slow, at least until some fundamental change suddenly comes along and modifies the constraints or attainable utility in the context, and the process starts over again.

That's true enough. We don't know what we don't know, and there's always the potential for some groundbreaking idea to shake things up. That's why it's important to fund research, even if that research doesn't have obvious practical applications.

But this sort of innovation comes from having an actual solution that makes tangible improvements. It does not come from someone saying "this technology hasn't changed in years, we need to find some way to innovate!" That sort of thinking is how you get stuff like Hyperloop or other boondoggles that suck up a lot of investments without solving any problems.

What's the history here?

https://www.quantamagazine.org/undergraduate-upends-a-40-yea...

Thanks!

I hadn't realised it was something so recent.

My irrational side really laments where many parts of modern life are in this process and how...standardised things have become. When I look at e.g. old camera designs, they are so much more exciting to see evolve, and offer so many cool variations on "box with a hole and a light sensitive surface in it". Seeing how they experimented and worked out different ways to make an image-making machine with that requirement, I feel like I'm missing out on a period of discovery and interesting development that now is at a well-optimised but comparatively homogenous dead end.