Many developments in the history of everything have started out as a mimesis of one kind or another. The arm became the lever while the horse became the steam engine and the mind became the computing machine. At some moment then typically comes a sort of inflection point at which the mimic surpasses its model: suddenly, there were hundreds of horses in the space of one. Often, this leads to other effects, ones much less obvious, unintended and almost impossible to foresee. Those horses, history tells us, facilitated a fundamental change in the urban landscape of North America; a change that came with a universe of social, ecological and economic transformations, not all of them for the better.
Cognitive technologies are likely to follow a similar pattern, although their mode of mimicry is much less linear. Consequently, inflection points may differ: instead of being an analog of our own thinking apparatus, they started off as apparatuses of logic. Running mechanically at first, such as the Antikythera mechanism, Charles Babbage’s difference engine or Gottfried Wilhelm Leibniz’s stepped reckoner, those machines could perform as many simple calculations as mechanical resistance (the arm) would allow for. The rise of electrical power and the vast paradigm shift it initiated then changed the mode of resistance into one of scale and integration: logical formations, materialized into ever-shrinking circuits, now powered by an invisible force at the speed of light. A sense of inflection followed: what if our souls fundamentally work the same way? But it turned out to be a mirage: our brains are not digital computers, just as little as the steam engine is a horse.
After more decades of trying to construct an apparatus that can think, we may be finally witnessing the fruits of those efforts: machines that know. That is to say, not only machines that can measure and look up information, but ones that seem to have a qualitative understanding of the world. A neural network trained on faces does not only know what a human face looks like, it has a sense of what a face is. Although the algorithms that produce such para-neuronal formations are relatively simple, we do not fully understand how they work. A variety of research labs have also been successfully training such nets on functional magnetic resonance imaging (fMRI) scans of living brains, enabling them to effectively extract images, concepts, thoughts from a person’s mind. This is where the inflection likely happens, as a double one: a technology whose workings are not well understood, qualitatively analyzing an equally unclear natural formation with a degree of success.
Andreas N. Fischer’s work Computer Visions II seems to be waiting just beyond this cusp, where two kinds of knowing beings meet in a psychotherapeutic session of sorts, consistent with the ideas that Joseph Weizenbaum first raised half a century ago with his software ELIZA. Yet, in Fischer’s interpretation, this relationship presents itself as a peculiar clash of surreal images and a voice tending to the very human. It is perhaps no coincidence then, that some of the images, particularly the carcass of an animal, are reminiscent of Werner Herzog’s 1971 film Fata Morgana, which depicts the Sahara and Sahel deserts to the sound of Lotte Eisner’s voice reciting the Mayan creation myth.
Like Herzog, Fischer created the images first and the voice-over followed after, almost in an effort to decode them and with them offer an experimental analysis of a future to come. Herzog’s film, after all, was initially intended as a science fiction narrative and only later turned into an exegesis of the origin of the world. In both films, the images serve as surreal divining rods to explore the nature of dreams and visions. “What kind of life is it?” asks the therapist. We do not hear the answer, but perhaps we have not heard the question right either: in a time of talk, simultaneously, of both the Anthropocene and the possibility of a posthuman condition, should the question not rather be what the dreams are, at their base of bases? And would it not be only fitting if—after passing the epochal inflection point of a machine that truly knows—its first words would be: “hi there, do you want me play back some of your dreams for you?”
Sascha Pohflepp, September 2017