This workshop proposal explores a concept for engaging AI in a non-deterministic manner in order to collaboratively produce physical artworks with a digital system. It draws from a lineage of “games” played by artists, from Surrealists to Situationists, that were targeted towards automatism and creative exploration as opposed to the expression of a preconceived idea.
Copyright © 2017 for this paper is held by the author(s). Proceedings of MICI 2017: CHI Workshop on Mixed-Initiative Creative Interfaces.
Creative practice, non-determinism, AI, humancomputer collaboration
H.5.m. Information interfaces and presentation (e.g., HCI): Miscellaneous;
Descriptions of creative practices offered by designers,
artists, and crafts people alike often highlight the
nonlinear and non-deterministic elements of a creative
practice. For instance, ideas often come from chance
encounters in the everyday world or stem from
accidents. In order to expand their space of ideas and
sensitivities, many artists turn away from a pre-existing
goal or vision and instead, look for ways to work with
his or her materials (be they digital or physical) in
open-ended, exploratory ways that may give rise to
unexpected or serendipitous outcomes or “happy
accidents.” In such practices, technology does not
necessarily need to be enrolled as an assistant or
instrument of productivity. Instead, I have argued that
digital systems for creative practice can be thought of
as “translations” [
While I have studied AI and computer science formally, I have yet to engage advanced algorithmic techniques in the unstable prototypes that I have created to date. I used to see these advanced algorithms as mechanisms that reduced engagement in the physical world, or eliminated the “risk” that I and others find so valuable in a creative practice. I would like to attend this workshop to explore alternative engagements of AI and machine learning in what I have be calling “unstable tools,” thus, unstable AI’s. At a broad level, this project joins wider calls for exploring where technology can participate within non-linear and chance-based creative practices. On a more specific level, it seeks a mode of engagement with AI that can give rise to surprising and beautiful results.
At the workshop, I would like to present a concept for a future MICI or unstable tool that is informed by “games” historically played by artists called AI Reverb.
Artists games are unstable by design and typically bring
multiple creative actors together to produce objects
unique to the situation of production, a form of extreme
collaboration where “players” correspond in an open
field of creative possibility. For instance, Surrealist
artists created several games for generating artwork
automatically and in a stream of consciousness fashion,
“Solitary and collective automatic techniques, and the
exploitation of chance are central to many surrealist
games…automatic techniques may be used as a
beginning of a creative activity, to stimulate and
encourage spontaneity of utterance or image-making”
[
Led by the writings of Guy Debord, The Situationist
International extended surrealist games into the ream
of everyday life, developing tactics for engaging the
everyday that could denature the habitual and lead to
experiences to allow someone to see beyond spectacle
[
Ono’s event score fuses poetry with practice, creating a prompt for a sensory engagement in sun and sandwiches alike. The goal of the work is less oriented around a “thing” produced, and more focused on how the execution of the instructions shaped the person who executed them.
While each example is targeted towards different outcomes and audiences, whether it be an automatically generating thing, a critique of spectacle, or an attempt at anti-art, they share in common a vision of making where control extends beyond an individual maker or audience. They position the artist as one of many numbers of forces capable of producing creative work, not necessarily the individual who stands above controlling what is produced. As such, these games tend to be oriented towards sensitization and understanding as opposed to a particular creative “object” outcome.
Drawing from this lineage of artists’ games or event scores, I imagine a system called AI Reverb that prompts an artist to take action in response to directives supplied by an artificial intelligence agent. In keeping with my interest in engaging with the everyday and materials, I imagine a system composed of a camera and text output screen. The camera captures the present scene, say, the maker sketching on a piece of paper. That scene (i.e. the paper) is processed as input to an AI that classifies what the object that the maker is drawing (much like Google’s Quick Draw application 1.) Based on how the AI identifies the object (for instance, if it thinks the artist is drawing a cat), it can supply instructions for the maker to perform on the drawing (e.g. draw multiple tails on cat, throw away drawing of cat and draw a dog instead, etc.). As the artist performs the command, the drawing changes, the classification of the drawing changes and a new set of commands is born ad infinitum. The outcome of such a system represents a reverberation between an artist and a machine, a surrealist drawing born out of a collective human-machine intelligence.
In AI Reverb accuracy and the correctness no longer function as meaningful bounds for the design space of interaction. Like a game of telephone, the pleasure emerges from the moments in which the AI makes an incorrect prediction or works in an imperfect manner. And while I have illustrated the concept within the relatively simplistic realm of drawing, one could 1 https://quickdraw.withgoogle.com/
imagine a mode of AI reverb that more readily embraced everyday life. For instance, an AI agent that feeds back on signage in shop windows and billboards in order to direct artists to take different actions within public space.
The tension with a project AI Reverb this is differentiating between a system that “breaks” well and a system that is just plain broken. At the present concept stage, I cannot predict exactly where those lines will be drawn. I see the sketch provided here as a benchmark for a new way of thinking about AI more than a set of plans for a system that I plan to enact. One of my goals for the workshop, then, is to refine this direction, learn more about the tools and techniques available, and hopefully gather feedback from artists in the group about how such a system might adapt into exploratory phases of their own practice. Computing Systems (CHI ’15), 2477–2486.
https://doi.org/10.1145/2702123.2702547 6. Lucian Leahu. 2016. Ontological Surprises: A Relational Perspective on Machine Learning. In
https://doi.org/10.1145/2901790.2901840 7. Yoko Ono and John Lennon. 2000. Grapefruit: A
Simon & Schuster, New York. 8. La Monte Young (ed.). 1963. An Anthology of Chance Operations. La Monte Young & Jackson Mac Low.