Paper short abstract:

This paper details how design anthropology was used to imagine new possibilities and co-design a patent-pending recommendation algorithm for the art industry.

Paper long abstract:

As algorithms become increasingly responsible for discovering information, how we choose to design them will significantly impact our collective lived experience. One example is how algorithmic bias affects the estimated 50 million people that make up the creator economy. This group of independent creators is financially dependent on recommender systems to suggest their content. Currently, most recommender system designs produce rich-get-richer dynamics, resulting in structural inequalities that favor some over others. This paper details how design anthropology was used to imagine new possibilities and co-design a patent-pending recommendation algorithm for the art industry.

Paper short abstract:

A series of short videos in production, reimagining the gods and stories from the Hindu pantheon. Inspired by the massively popular comic book series Amar Chitra Katha, this series uses machine learning generated video and sound to create short works that re-imagine our storytelling.

Paper long abstract:

Saṅkhyā ("number" in Bengali) Stories are a series of short videos using machine learning and media art practices to imagine how we might extend and express cultural knowledge using contemporary tools. The videos take as its inspiration the massively popular Amar Chitra Katha ("My Bright Stories") comic book series, and present a contemporary moving-image catalog that explores Hindu mythology outside the canon, looking for hidden stories in the repository of collectively held mythology, activating the fluid nature of how these stories are told and the beautiful inconsistencies in each telling.

This type of work is part of a larger exploration by artists across the field, summarized recently in the Oxford Internet Institute paper "AI and the Arts: How Machine Learning is Changing Artistic Work" (Ploin, Eynon, Hjorth, Osborne, 2022).

Paper short abstract:

Set in Stone is an artistic project resulting from my inquiries into training bias out of image generation algorithms. Conceptually, the work subverts static generative binary stone faces with color, an explosion of self-expression taking root over the homogeneity of the binary marble statuary.

Paper long abstract:

Set in stone is an exploration into the creative visualization of training bias out of a biased neural network. I created a 3D rendered dataset and trained several GANs first in one gender, then another, then, using semiotic expressions of non-binary gender, I added a third dataset while training and observed the results. Each neural network required specific file handling skills and reacted to the new data additions in different ways. An exploration of gender, of machine creativity and of bias. Through this project I have observed bias retreating and reemerging, I have seen artifacts appear as new data is being assimilated and I have created work with the samples generated as a result. This work has gone on to influence my entire thesis with further research into AI perceptions of gender beyond the binary.

Through this evolving collaborative work with my different AI systems, I am exploring how my machine creates images representing gender and if it holds onto its trained bias. From close up, the audience sees the individual faces and misses the big picture, but from a distance they see how those individuals combine to make a concept bigger than any one person. The unbiasing of the neural network is clear in video presentations, but the installation as a massive wallpaper, larger than life, blends all of those results together in a grand mosaic to show how we can't always see how bias, particularly machine bias, will affect the individual.

Paper short abstract:

Architectural anthropology presupposes the space of the artificial as a human-machine creative symbiosis. This complex coupling between embodied living in and disembodied designing of buildings is explored via the uncanny 3D-printed housing forms as imagined by 3D generative adversarial networks.

Paper long abstract:

“Displaced from artifice into the artificial, architecture became a technological extension of the body that is neither natural nor cultural. Modern architecture is the space of the artificial” [Wigley 1991]. From architecture as the built extension of the anthropological body, to architecture as the unbuilt virtual world extending the mind into a reality that is neither less real nor less meaningful than physical buildings [Chalmers 2022], the human-machine creative symbiosis is very much also a human-architecture creative symbiosis. This symbiotic coupling between Anthropology and Architecture [Oliver 1979], once even alluded by Winston Churchill when he said that "we shape our buildings; thereafter they shape us", has led to a new subfield -- Architectural Anthropology [Stender 2017]. The paper takes such an interdisciplinary attitude to explore the anthropological (or archaeological) reconstruction of lived spaces and the architectural construction (or deconstruction) of to-be-lived spaces as staged at the current exhibition “Eye Rise: Urbanscapes Between Human and Machine” [The Arts House 2022]. Unlike traditional artistic tools, the series of 3D-printed high-rise architectural forms sampled from the latent space of the 3D-GAN-Housing project illustrates an uncanny disembodied human-machine symbiosis. Indeed, “the house is a machine for living in” [Corbusier 1923], but more so -- “The house is a living machine for learning with”.

(Link to 3D-GAN latent walk video at shorturl.at/cqBO1)

(Link to 3D-printed models at shorturl.at/juTW9)

(Link to main exhibition at shorturl.at/imoAM)

Paper short abstract:

Applications of machine learning to creative tasks produce surprisingly good results. The plausibility of outputs produced by machines in tasks such as painting pictures, writing poems, or composing music raises interesting questions about the nature of creativity. My contribution to the symposium will start from the FolkRNN project: a collaborative research-creation project exploring the use of machine learning as a creative tool. Together with my colleague Dr. Bob Sturm, we applied machine learning to a data set of traditional Irish music which we then used to generate new tunes in that traditional style (surreptitiously released as an album) but also to compose music that has little to do with the tradition.

Paper long abstract:

This project illustrates the very first steps in the use of new technology. The development is predicated on the capabilities of the technology (and lead by the technologists). But we are moving into the next stage where we need to ask deeper questions such as: what is our vision for future involvement of intelligent machines in creative activities? What does it mean to be musically (poetically, artistically) intelligent (and is it the same for humans and machines)? Should we examine what we value in creative pursuits (and how we pay for these)? Shifting the conversation in this direction requires a broader dialogue that integrates the knowledge and knowhow of artists-practitioners as well as scholars from multiple fields. Since January 2022 I am leading an international research network that aims to explore these issues in relation to music.