Intro

Machines Like Us 

 

 

“I think everybody should be a machine.” said Andy Warhol in 1963. A 2019 novel by Ian McEwan hooks up with Warhol’s frivolous wish in its ambiguous title: Machines Like Me. Machines are like us—and they like us. Is this affection a threat, too? And which machines are we speaking about anyway? Robots that poison us in war or nurse us in old age? Voice recognition-based virtual assistants with an eavesdropping function, or complete social control systems that generate an “us” and a “them”? The armament of biotechnologies, bots, or cyborgs? 

In this light, the man/machine dichotomy becomes increas- ingly blurry. Humans use machines, which in turn affect and change them. Transhumanist-minded people upgrade their bodies, while our data-self is taking on more and more “flesh” and branches of research like affective computing are tinkering with the simulation of affect. At the same time, an abyss manifests in the presence of machines, which up- dates the category of the uncanny. Google’s DeepDream software mutates images as if they were on-screen encoun- ters with psychedelic animations made by beings from un- known dimensions. 

What’s also uncanny is the economic power of the big players in the data exploiting surveillance capitalism of the twenty-first century. Whoever can process more data than competitors has the advantage—as a state, as a secret service, as a company, as a spin doctor. The discriminating preconditions of the programming are typically ignored in the black box society, while the output of control society (think of China’s social credit system) becomes increasingly onerous. Algorithms can augment hallucinations and illu- sions—or be allies in rebellions and protest movements, too. 

Or in art. 

For example, in digital imagery that turns the ambig- uous, the morphing into a principle of style. Or in mu- sical AI applications, like Holly Herndon’s last album Proto. Herndon calls the unison of choir and AI inter- dependent music, rather than independent music. 

This interdependence points to the entanglement of man and machine. We’ve already changed since learning how machines sound, make images, or spur us, for instance, to ruminate about robot ethics or so- called death algorithms in self-driving cars. And we will change again, once we find out what machines are capable of when they offer us—beyond binary notions of dystopia and utopia, like in the computer animated films Geomancer (2017) or AIDOL爱道 (2019) by Lawrence Lek—a world without humans but full of af- fect. 

Thomas Edlinger 
Artistic Director 

 

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