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Technology & Innovation

There is no difference between computer art and human art

Computer art does not rival human art. Rather, art created by artificial intelligence is at once a compliment to the human brain, and a corollary to the achievements of oil paintings and classical music.
Photo by Cris DiNoto on Unsplash

In December 1964, over a single evening session in Englewood Cliffs, New Jersey, John Coltrane and his quartet recorded the entirety of A Love Supreme. This jazz album is considered Coltrane’s masterpiece – the culmination of his spiritual awakening – and sold a million copies. What it represents is all too human: a climb out of addiction, a devotional quest, a paean to God.

Five decades later and 50 miles downstate, over 12 hours this April and fuelled by Monster energy drinks in a spare bedroom in Princeton, New Jersey, Ji-Sung Kim wrote an algorithm to teach a computer to teach itself to play jazz. Kim, a 20-year-old Princeton sophomore, was in a rush – he had a quiz the next morning. The resulting neural network project, called deepjazz, trended on GitHub, generated a buzz of excitement and skepticism from the Hacker News commentariat, got 100,000 listens on SoundCloud, and was big in Japan.

This half-century gulf, bracketed by saxophone brass and Python code, has seen a rise in computer-generated music and visual art of all methods and genres. Computer art in the era of big data and deep learning, though, is a reckoning for algorithms, capital-A. We must now embrace – either to wrestle or to caress – computer art.

In industry, there is blunt-force algorithmic tension –  ‘Efficiency, capitalism, commerce!’ versus ‘Robots are stealing our jobs!’ But for algorithmic art, the tension is subtler. Only 4 per cent of the work done in the United States economy requires ‘creativity at a median human level’, according to the consulting firm McKinsey and Company. So for computer art – which tries explicitly to zoom into this small piece of that vocational pie – it’s a question not of efficiency or equity, but of trust. Art requires emotional and phrenic investments, with the promised return of a shared slice of the human experience. When we view computer art, the pestering, creepy worry is: who’s on the other end of the line? Is it human? We might, then, worry that it’s not art at all.

Algorithms’ promise holds potent popular allure. A search for the word ‘algorithm’ in the webpages of the empirically minded site FiveThirtyEight (where I’m on staff) returns 516 results, as I write. I’m personally responsible for more than a few of those. In the age of big data, algorithms are meant to treat disease, predict the decisions of the Supreme Court, revolutionise sports and predict the beauty of sunsets. They will also, it’s said, prevent suicide, improve your arugula, predict police misconduct, and tell if a movie will bomb.

The more grandiose would-be applications of algorithms and artificial intelligence (AI) are often preceded by ostensibly more manageable proving grounds – games, say. Before IBM’s question-answering computer, Watson, treats cancer, for example, it goes on the TV quiz show Jeopardy! Google’s AlphaGo took on a top human Go champion in a ‘grand challenge’ for AI. But these contests aren’t trivial stepping stones – they can be seen as affronts to humankind. One commentator, realising that Google’s program would win a match, said he ‘felt physically unwell’.

It’s much the same for computer art projects. Kim and his friend Evan Chow, whose code is used in deepjazz, are members of the youngest generation of a long lineage of computer ‘artists’. (These two aren’t exactly starving artists, though. This summer, Kim’s working at Merck, and Chow’s at Uber.) As the three of us sat in a high-backed wooden booth in Cafe Vivian, on the Princeton campus, actual, honest-to-God human jazz played over the speakers – Rahsaan Roland Kirk’s frenetic ‘Pedal Up’ (1973) – and as Kim played me samples generated by deepjazz from his laptop, we were awash in an unholy jazz + jazz = jazz moment.

‘The idea is pretty profound,’ Kim said, as I strained to decipher what was human in the cacophony. ‘You can use an AI to create art. That’s normally a process that we think of as immutably human.’ Kim agreed that deepjazz, and computer art, is often a proving ground, but he saw ends as well as means. ‘I’m not going to use the word “disruptive”,’ he said, then continued: ‘It’s crazy how AI could shape the music industry,’ imagining an app built on tech like deepjazz. ‘You hum a melody and the phone plays back your own custom, AI-generated song.’

Like a profitless startup, the value of many computer-art projects thus far is their perceived promise. The public deepjazz demo is limited, and improvises off just one song, ‘And Then I Knew’ (1995) by the Pat Metheny Group (Kim wasn’t quite sure how to pronounce ‘Metheny’). But the code is public, and it’s been tweaked to noodle the Friends theme song, for example.


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