Our artistic research led us to amass an archive of thousands of recorded worries from people in the US and abroad. Ecology of Worries asks the question of whether we should teach a machine to worry for us. The animation consists of hand drawn critters. Some critters are driven by synthetic worries generated with TextGenRnn recurrent neural network trained on the transcribed worries archive. Other characters are driven to worry by a novel machine learning system called Generative Pretrained Transformer 2 (GPT-2), which was dubbed by some commentators as the AI that was too dangerous to release (but it was released anyway). The creatures’ performance of synthetic worries spans a gradient of intelligibility, reflecting on our deeper collective reality.

By characterizing the synthetic worries of various sophistication as variously evolved creatures we aim to engage the empathy of the viewers. It is one thing to experience a text generating neural network failing into mode collapse, which is a state where the system generates the same unchanging output no matter the input (e.g. a string of the same repeating vowel over and over again). It is a whole other thing to watch a mode collapse personified by one of these critters: as we watch the creature struggling to get a word out we can’t stop ourselves from feeling like we should help it finish the sentence. The mode collapse text result of ‘aaa aaaaaaa’ becomes a living wail. The critters in Ecology of Worries appear sentient not because of omniscience a tech evangelist might expect from a digital assistant, but due to their very real flaws. The creatures become uncanny through a juxtaposition of familiar and abstract concerns. The work invites people to watch, listen, and engage with these cute and disturbing beings to make shared concerns—whether serious or hilarious—intimate.