Viscerally digital in aesthetic, yet deliberately static and a fixed aspect ratio, highly blended and textured, embracing the imperfection of handmade physicals while analog static collides with digitally emotive outbursts.
Heuristics of Emotion seeks to abstract an expression of what it looks like for a machine or AI to learn how to feel. An adolescent finding its emotional intelligence by emulating what it can pick up from humanity, and from what feedback it gets from it.
Static and optical aberrations showing blind spots in what it means to feel, or to understand one's feelings, mimicking how a person may be learning how to parse and unpack their own feelings as they evolve. It hopes to create empathy between a biological entity and one that's digital.
With minor variations when rendered across browsers and resolutions—yet still deterministic in context—it tries to pull the beauty and volatility of edge conditions in how software and hardware interpret a set of instructions to find unexpected expressions that can only exist by exploring the spaces where interpretations vary. Let's say it's emotional.
It reflects how pre-digital generative instructions—like rulesets for how lines should be drawn on a wall—can be rendered and presented unpredictably because of who may have executed said instructions where. The beauty is in the tension of interpretation and execution, not the final rendering on a pixel level. Context changes how you feel.
One machine may extract sentiment differently than another based on whatever biases have been programmed in or what their hardware allows. These discrepancies can be the most revealing.
A snapshot of a machine—soft or hard—as it learns to feel by emulating emotion, as we do, in part. All of our becomings.
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