Art and AI

Frederic Bazille’s Studio 9 Rue de la Condamine (1870) and Norman Rockwell’s Shuffleton’s Barber Shop (1950)

When A Machine Learning Algorithm Studied Fine Art Paintings, It Saw Things Art Historians Had Never Noticed
The Physics arXiv Blog via Medium, Aug 2014
Source document: Toward Automated Discovery of Artistic Influence

There's some stirring in the dusty world of art history, with the rise of encultured robots threatening human livelihoods. A promising young algorithm is set upon the world, fed with centuries of art imagery, design principles, and historical documentation. Our little algorithm then grows up and learns how to identify patterns in the art world better than its teacher.

In the two compared images above, this little art-historian algo recognized similar compositional patterns that had never been seen before - a hidden Norman Rockwell, see above.

First of all, as an art history major in college, I look at all the compared/related images discovered by the AI, and I am not so impressed. Maybe the general concept is what fails to impress me. When you follow the art world long enough you get to know something about how influence works, and about the power that one thing can have on an artist's work. And I say that there is no such thing as one thing.

The nature of the artist is to take the world at large, a fuck-tonnery of pre-filtered miasma, and to make sense, or at least to fight with it in a way that leaves a record of the battle, and for the benefit of humankind. To say that one painting influenced another because they have similar stylistic elements or design principles is kind of silly. I do understand that subconscious influence has its way with the creative process. But that refers to life as well as art. The new style checker cab, or Triangle shirtwaists, or bubble tea or middle-hipster Americana folk music or The Beatles or African masks or even syphilis could influence an artists' work.

Charge of the Lancers - Umberto Boccioni - 1915

Take ^Futurism, for example. It is inspired by, among other things, the fragmentation of society, be it from national upheaval circa the World Wars, or from the way the landscape looks while riding a speeding train which propelled people faster past the countryside than they had ever moved before. How does an algorithm find that?

I heard Picasso's mistress Françoise Gilot, in her bio of Pable Picasso, say some of his lobster paintings were a response to her hard-shelled personality which came to a head prior to their separation. Algorithms can see that? Nah man.

I know someone can come on here and argue with me, successfully, that artists do influence each other in simple visual ways, and at times, the visual connections can supplement a lack of historical data surrounding their work. But still, there is a need for socio-biographical data in all this, and I wonder if our little algo could be even better trained.

Now, all this having been said, I just finished watching this: Davos talk about the future of artificial intelligence, with IBM CEO Ginni Rommetti. She says that the goal of IBM's artificial intelligence (Watson, by the way, in case you forgot) is to extend human faculties, not replace them. According to her premonitions, the art historian is not doomed, rather it will be enriched and extended by our algorithmic overlords.

Eyeborg

The first person in the world to become a government-recognized cyborg
Annalee Newitz, io9.com, 02 Dec 2013

Neil Harbisson is the first person on the planet to have a passport photo that shows his cyborg nature — in his UK passport, he's wearing a head-mounted device called an eyeborg. The color-blind artist says the eyeborg allows him to see color [by translating it into sounds], and he wants to help other cyborgs like himself gain more rights.

totally unrelated

Bursts

Hand Fixing Hand, Shane Willis

partially unrelated internet image

9.5% of words make up 90.5% of Reuters news by word count."The Pareto Principle",
Network Science, Jerome Kunegis, 2012-02-07

Poisson distributions display exponential decay, whereas Pareto distributions, or power laws, display a long-tail, with lots of activity in a short period of time, followed by long times of no activity. Barabasi's Bursts are a reference to the latter, upon study of the patterns of human activity.

Consider also, that the computer has aided the magnified temporal resolution of human activity frequency, thus forcing us to see ourselves as such.

A.L. Barabasi, Bursts, 2010
A Bit on Networks
The Big Heap, Time and Network Configuration


ZIPF

...if "the" is the most popular word in any random text, and it shows up a number of 1,000 times, then "of" (the second-most popular word) would show up 500 times...

 Zipf's law states that given some corpus of natural language utterances, the frequency of any word is inversely proportional to its rank in the frequency table. Thus the most frequent word will occur approximately twice as often as the second most frequent word, three times as often as the third most frequent word, etc.

For example, in the The Brown University Standard Corpus of Present-Day American English, the word "the" is the most frequently occurring word, and by itself accounts for nearly 7% of all word occurrences (69,971 out of slightly over 1 million). True to Zipf's Law, the second-place word "of" accounts for slightly over 3.5% of words (36,411 occurrences), followed by "and" (28,852). Only 135 vocabulary items are needed to account for half the Brown Corpus.

The same relationship occurs in many other rankings unrelated to language, such as the population ranks of cities in various countries, corporation sizes, income rankings, and so on.
http://en.wikipedia.org/wiki/Zipf's_law

*Zipf's law is referenced in Science Fiction author Robert J. Sawyer's www.wake, when the main character is searching for intelligent life on the web.
http://en.wikipedia.org/wiki/Wake_(Robert_J._Sawyer_novel)

Ethiopian Kids Hack PLPCS in 5 Months with Zero Instruction

What happens if you give a thousand Motorola Zoom tablet PCs to Ethiopian kids who have never even seen a printed word? Within five months, they’ll start teaching themselves English while circumventing the security on your OS to customize settings and activate disabled hardware. Whoa.

The One Laptop Per Child project started as a way of delivering technology and resources to schools in countries with little or no education infrastructure, using inexpensive computers to improve traditional curricula. What the OLPC Project has realized over the last five or six years, though, is that teaching kids stuff is really not that valuable. Yes, knowing all your state capitols how to spell “neighborhood” properly and whatnot isn’t a bad thing, but memorizing facts and procedures isn’t going to inspire kids to go out and learn by teaching themselves, which is the key to a good education. Instead, OLPC is trying to figure out a way to teach kids to learn, which is what this experiment is all about.

Rather than give out laptops (they’re actually Motorola Zoom tablets plus solar chargers running custom software) to kids in schools with teachers, the OLPC Project decided to try something completely different: it delivered some boxes of tablets to two villages in Ethiopia, taped shut, with no instructions whatsoever. Just like, “hey kids, here’s this box, you can open it if you want, see ya!”

Just to give you a sense of what these villages in Ethiopia are like, the kids (and most of the adults) there have never seen a word. No books, no newspapers, no street signs, no labels on packaged foods or goods. Nothing. And these villages aren’t unique in that respect; there are many of them in Africa where the literacy rate is close to zero. So you might think that if you’re going to give out fancy tablet computers, it would be helpful to have someone along to show these people how to use them, right?

But that’s not what OLPC did. They just left the boxes there, sealed up, containing one tablet for every kid in each of the villages (nearly a thousand tablets in total), pre-loaded with a custom English-language operating system and SD cards with tracking software on them to record how the tablets were used. Here’s how it went down, as related by OLPC founder Nicholas Negroponte at MIT Technology Review’s EmTech conference last week:

“We left the boxes in the village. Closed. Taped shut. No instruction, no human being. I thought, the kids will play with the boxes! Within four minutes, one kid not only opened the box, but found the on/off switch. He’d never seen an on/off switch. He powered it up. Within five days, they were using 47 apps per child per day. Within two weeks, they were singing ABC songs [in English] in the village. And within five months, they had hacked Android. Some idiot in our organization or in the Media Lab had disabled the camera! And they figured out it had a camera, and they hacked Android.”

This experiment began earlier this year, and what OLPC really want to see is whether these kids can learn to read and write in English. Around the world, there are something like 100,000,000 kids who don’t even make it to first grade, simply because there are not only no schools, but very few literate adults, and if it turns out that for the cost of a tablet all of these kids can simply teach themselves, it has huge implications for education. And it goes beyond the kids, too, since previous OLPC studies have shown that kids will use their computers to teach their parents to read and write as well, which is incredibly amazing and awesome.

via: Surrogate Self

via: DVICE

Evan Ackerman, Oct 30, 2012

source: MIT

A bold experiment by the One Laptop Per Child organization has shown “encouraging” results.

By David Talbot on October 29, 2012

Technological Complexity as a Function of Latitude

More complex technological units are needed (or have been invented) by historical hunter-gatherer tribes the higher the latitude of their homes.

(p25)
What Technology Wants
Kevin Kelly
2010