We are on the cusp of two potentially transformational movements: (1) the blurring of disciplinary boundaries in scholarship and (2) the rise of Machine Learning (ML), a sub-field of Artificial Intelligence concerned with automating the construction of predictive models. The softening of traditional silos of scholarship allows for increasing dialogue and knowledge-transfer between the arts and sciences. This has facilitated the recognition and advancement of alternative methods of conducting research within academia, fostering a broad new range of research-creation approaches stemming from art and design practices. Research-creation involves a hybrid creative practise where research and production occur in parallel and artistic creativity is valued for its knowledge-generating capacity. Recent breakthroughs in “Deep Learning”, an ML approach using complex networks of simple units, have sparked a “4th industrial
revolution” where adaptive computational systems are rapidly approaching or overtaking human performance in a diversity of fields such as medicine, transportation, and finance. While we are witnessing a movement of convergence between the arts, science, and engineering within public and private sectors, the accelerating industrialization of AI has the potential to cause significant disruptions into multiple spheres of society. Both of these movements will likely have deep consequences regarding how contemporary cultures develop in the coming decades.
At the nexus of the “STEM to STEAM” transition and strides in Deep Learning, an increasing number of artist-researchers have been making use of ML as raw material as part of their research and practice, following a tradition of practitioners working at the intersection of art, computation, cybernetics, and artificial life. In this panel we will address questions such as: Why are artists interested in ML and how do artistic uses differ than those in the sciences? How can ML be a site for artistic enquiry into the nature of concepts and representations of the world and ourselves? How can we examine the bias and prejudice of AI algorithms when they are deployed as black boxes? Are artists responsible for critically reflecting on the AI methods they use?
These questions will be examined through the lenses of the practices of panelists. In particular, they explore two important concepts relevant to ML and new media art: behavior — defined as the stable form of events caused by an agent as it is perceived by an external subject, and imagination — the construction of internal structures by a subjective agent, as detailed in the abstracts.
- Ben Bogart is a nonbinary adisciplinary artist working for nearly two decades with generative computational processes (including physical modelling, chaotic equations, feedback systems, evolutionary algorithms, computer vision and machine learning) and has been inspired by knowledge in the natural sciences (quantum physics and cognitive neuroscience) in the service of an epistemological inquiry. Ben has produced processes, artifacts, texts, images and performances that have been presented at galleries, art festivals and academic conferences in Canada, the United States of America, the United Arab Emirates, Australia, Turkey, Finland, Germany, Ireland, Brazil, Hong Kong, Norway and Spain. Notable exhibitions include solo shows at the Canadian Embassy at Transmediale in 2017 and the TechLab at the Surrey Art Gallery in 2018. They have been an artist in residence at the Banff Centre (Canada), the New Forms Festival (Canada) and at Videotage (Hong Kong). Their research and practice have been funded by the Social Science and Humanities Research Council of Canada, the British Columbia Arts Council and the Canada Council for the Arts. Ben holds both master’s and doctorate degrees from the School of Interactive Arts and Technology at Simon Fraser University (Vancouver, Canada). During their master’s study (2006–2008) they began an artistic inquiry of machine learning and developed a site-specific artwork that uses images captured live in the context of installation as raw material in its ‘creative’ process. In their doctoral work (2009–2014) they made “a machine that dreams” that is framed as both a model of dreaming and a site-specific artistic work manifesting an Integrative Theory of visual mentation developed during their doctorate. Ben’s recent work involves building Machine Subjects that appropriate and reconstruct cultural artifacts using artificial intelligence. Ben is currently embarking on a two year project funded by the Canada Council for the Arts developing a body of work applying machine learning methods to image-making situated in painting history.
- Stephen Kelly is an artist, computer programmer, and musician living in Hamilton, Ontario, Canada. He has exhibited and participated in residency programs internationally. His work incorporates sound, electronics, mechanics, and other media in the creation of thematically diverse complex systems. Kelly has a Bachelor of Fine Arts from the Nova Scotia College of Art & Design and a PhD in Computer Science from Dalhousie University. He is currently a Postdoctoral Research Associate at the BEACON Center for the Study of Evolution in Action at Michigan State University (USA).
- Suzanne Kite aka Kite is an Oglála Lakȟóta performance artist, visual artist, and composer raised in Southern California, with a BFA from CalArts in music composition, an MFA from Bard College’s Milton Avery Graduate School, and is a PhD candidate at Concordia University. Kite’s scholarship and practice highlights contemporary Lakota epistemologies through research-creation, computational media, and performance. Recently, Kite has been developing a body interface for movement performances, carbon fibre sculptures, immersive video and sound installations, as well as co-running the experimental electronic imprint, Unheard Records. For the inaugural 2019 Toronto Art Biennial, Kite, with Althea Thauberger, produced an installation, Call to Arms, which features audio and video recordings of their rehearsals with Her Majesty’s Canadian Ship (HMCS) York, which also consisted of a live performance with the conch shell sextet, who played the four musical scores composed by Kite. Kite has also published extensively in several journals and magazines, including in The Journal of Design and Science (MIT Press), where the award winning article, “Making Kin with Machines,” co-authored with Jason Lewis, Noelani Arista, and Archer Pechawis, was featured. Currently, she is a 2019 Pierre Elliott Trudeau Foundation Scholar. kitekitekitekite.com
- Sofian Audry is an artist, scholar, Professor of Interactive Media within the School of Media at the University of Quebec in Montreal (UQAM). His work is inspired from visual art, artificial intelligence, artificial life, biology and cognitive sciences. His computational artistic practice branches through multiple media including robotics, interactive installations, immersive environments, physical computing interventions, internet art, and electronic literature. Audry studied computer science and mathematics at University of Montreal (BSc, 2001) where he completed a master in machine learning (MSc, 2003); following which he obtained a master in communication (interactive media) at UQÀM (MA, 2010). His PhD is in Humanities from Concordia University (2016). In 2017 he was a Postdoctoral Fellow at the Massachusetts Institute of Technology. His work and research have been presented in multiple international events and venues such as Ars Electronica, Barbican, Centre Pompidou, Club Transmediale, Dutch Design Week, Festival Elektra, International Digital Arts Biennale, International Symposium on Electronic Art, LABoral, La Gaîté Lyrique, Marrakech Biennale, Nuit Blanche Paris, Society for Arts and Technology, V2 Institute for Unstable Media, Muffathalle Munich and the Vitra Design Museum.
- Stephanie Dinkins is a transmedia artist who creates platforms for dialog about artificial intelligence (AI) as it intersects race, gender, aging, and our future histories. She is particularly driven to work with communities of color to co-create more inclusive, fair and ethical artificial intelligent ecosystems. Dinkins’ art practice employs lens-based practices, emerging technologies and community engagement to confront questions of bias in AI, consciousness, data sovereignty and social equity. Investigations into the contradictory histories, traditions, knowledge bases and philosophies that form/in-form society at large underpin her thought and art production. Dinkins is a professor at Stony Brook University (NY, USA) where she holds the Kusama Endowed Chair in Art. She exhibits and publicly advocates for inclusive AI internationally at a broad spectrum of community, private and institutional venues – by design. Her work has been generously supported by fellowships grants, and residencies from Stanford Institute for Human-Centered AI, Creative Capital, Sundance New Frontiers Story Lab, Eyebeam, Data & Society, Pioneer Works, NEW INC and The Laundromat Project.