Your eye already does this naturally to help you determine detail. There's a fascinating article about it here:
http://accidentalscientist.com/2014/12/why-movies-look-weird...
What's happening is the added noise causes the spectrum of the error to change. With uniform uncorrelated noise (and some constraints), you can prove that the error is also uniform + uncorrelated, which means that the signal distortion must be zero (because otherwise the error would not be uncorrelated).
You can see that this gives you a discernible image with only 1 bit of depth. The same technique gives digital audio extra range and lower distortion.
The phenomenon is interesting, although the connection to UI is a little vague. Still, I think author has a good point.
Take bevels for instance. They may be considered a visual "noise", and in flat design they are frowned upon, but how do I know where I can click (push a button)?
Similar thing for window shadows, they help to recognize the window boundary.
There's a related phenomenon in astronomy called Eddington Bias. If you're doing a survey of stars in the sky, often times you are limited by the brightness of the stars, so there's some brightness below which you don't detect any stars.
Because photons arrive at your detector randomly, sometimes a few more photons arrive at the detector from a particular star than average, and sometimes fewer. One therefore sees small random fluctuations in the brightness of the star.
Because there are many more faint stars than bright stars, it is much more likely for a star just below your detection threshold to fluctuate up above your detection threshold than for a star just above your detection threshold to fluctuate down below your detection threshold. This ends up biasing the inferred median luminosity to higher values.
I'm not sure how he makes the association to UI, but I agree that the minimalist and flat designs are way too far gone to be useful. Sure, I despise noisy and cluttered and fake leather bound UI too, but that doesn't mean we need to go full bi-polar swing and jettison everything.
Regarding noise and this post, I could see it as a metaphor against Google's tendency to significantly reduce the information density by adding white-space to every frigging things, everywhere, at all times. Take the bookmark boondoggle that they just backpedaled on; guess what Google, I would like to see more than 8 bookmarks per view and I don't see how a miniature thumbnail of the site really helps anyone. I want the "noise" in that case, which consists of density of information, which hopefully is of the relevant type. I want a quick overview with as much information as possible, but I also need it to be visually distinguishable. That is another big problem which this post maybe addresses, visual hierarchy, which is another one of those principles that has been jettisoned with the minimalist and flat design binge. The user should be able to pic out content and interactions in a relevant sequence without significant gaps in visual progression; each level of visual hierarchy should be an equal or relevantly spaced distance apart without significant gaps. /my2cent
This is also reminiscent of the Gumbel trick[1] If your noise is Gumbel noise, you can actually get the probability to exceed the threshold to be proportional to the intensity of the pixel.
[1] https://hips.seas.harvard.edu/blog/2013/04/06/the-gumbel-max...
It's also used in cochlear implants.
Could someone expand on this phenomenon as it relates to noise machines? They normally help people sleep but could they actually make certain sounds more distracting based on this phenomenon?
Professor Bart Kosko at USC is an active publisher in this area.
Example: sipi.usc.edu/~kosko/TSP_May2009.pdf
Isn't this (just) dithering noise?
AFAIK, the reason it's so effective in the example is that adding the noise helps the quantization process in the posterization better represent the original color spectrum. Without the dithering the quantization error can keep adding up in a way that the posterization filter cannot control (but which the image author can engineer to be problematic, as surely was the case here). With the dithering you have a statistical guarantee that the quantization errors average out.