A L G O R I T H M S   I N   A R T

by Magda Stanová

In 2005, scientists from the Massachusetts Institute of Technology made an algorithm, titled SCIgen, able to generate texts that looked like research papers. A couple of years later, two scientists from Rensselaer Polytechnic Institute, Allen Lavoie and Mukkai Krishnamoorthy, decided to make a classifier—a program that would be able to distinguish genuine papers from those generated by SCIgen. They were successful: Out of 200 papers, the program correctly identified all 100 papers that were generated by computer. Of the 100 papers written by humans, it correctly classified 98.

Two papers written by humans were identified as computer-generated. The incorrect identification was a problem with the classifier, not the authors of the papers. (The classifier expected certain formal characteristics typical of research papers that weren’t present in these two papers.) Let’s imagine, however, a classifier—either computer-based or human—that would detect algorithmic behavior and obtain the same results. How would you feel if a text you wrote were classified as computer generated?

People interested in artificial intelligence usually ask whether computers could become as intelligent and creative as humans. I decided to think about it the other way around: I’m interested in the extent to which the creative process of artists is algorithmic.

1 (Niépce’s decision)

2 (Edgar Allan Poe)

Popular algorithms in photography

Popular algorithms in art

3 (1000 × 1000 pixels)


4 (Fog)


5 (Fitness)


The moment when everything was possible



6 (Hierarchical structure)




7 (I know | I don’t know)





8 (Schultz’s experiments)






9 (Triggering and resolving an ambiguity)







Works of art that couldn’t be used in textbooks as illustrations of scientific knowledge








Taking someone on a trip without letting them know that they’ve been taken









10 (Giakomo)










11 (Reward system)











12 (Trigger miners and distributors)












13 (Fading)













14 (Phantom)














15 (Fade rate)















Berlyne’s version of the Wundt curve
















16 (Individual differences)

















17 (Berlyne’s wave)


















18 (Retro)


















Triggers that always work



















19 (Thrill combo)




















20 (Semantic, episodic, and emotional memory)





















21 (Outsourcing the fitness function)






















Many people seem to be irritated by the idea that an algorithm could generate thrill-triggering artifacts. I suppose this aversion comes from a fear of losing thrills caused by inventing/creating/discovering. But the motivation of those who try to invent an algorithm for art is, in fact, precisely this: If they succeeded in creating a really good algorithm, it would cause them a huge thrill.






















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