Admissibility, selection criteria & best practices
We are looking for publications that broadly incorporate interdisciplinary artificial intelligence design in their process. We also welcome art projects, especially inter-arts or transdisciplinary forms of art, such as : new media addressing algorithmic bias, traditional art exploring AI ethical implications, or public art projects involved in AI literacy.
Particular attention will be paid to the quality of curation, data collection and annotation. Indeed, new scientific frameworks and the inter-arts discipline in AI ethics can intervene in a sociotechnical "pipeline" of data collection and algorithmic design while helping to enrich a more inclusive narrative and understanding of the ethical, social, legal, cultural, economic, and political implications of AI.
We understand that interdisciplinarity in science is not new, however the integration of Arts and Humanities (STEAM approach) in AI is still subject to resistance when it comes to forming and funding research and development teams. This is why we favour a "design" of AI models integrating social sciences, law, humanities and arts, from the initial stages of preparation of datasets, foundations of machine learning models. From the body of work received, we hope to demonstrate this approach’s efficiency in contributing to high-quality AI models as well as a mission-driven (SDGs, human rights, reconciliation) governance.
The following best practices will also guide our committee in the evaluation of submitted AI art projects and publications
1- Avoid dystopia and foster a sense of "agency" or civic engagement. Research shows that a curation process designed to give participants a capacity to intervene and be part of the solution when facing complex social or environmental problems, are the most effective in achieving the desired change.
2- Pro-actively select methods that increase inclusion and diversity of perspectives in the design team. Please be mindful that tokenizing “consultation” methods tend not to include stakeholders right from the start, nor pay stakeholders for their expertise and experience. Feel free to show off your inclusion and diversity design process.
3- Make your art political, adapted to social context, and contribute to democratic evolution of AI governance. For example, notions of data sovereignty are leading to major policy and regulatory change internationally. We welcome projects that create iterative environments with citizens of the digital age and inform public policy.
4- Facilitate collective learning. Ex: interactive public art or immersive installations or collaborative data curation applications.
5- Get out of “institutions” & favour public places. Many researchers are showing the benefits of holding public art installations in easy to access locations that are not associated with the elite such as museums. However, some traditional museal institutions put this in practice by partnering with the community, holding their events outside of the physical structures of the museum.
6- Recognize the plurality of knowledge sources in the co-construction, co-creation processes that you might have used.
*Please note: An "inter-arts" practice is an art discipline recognized by the Canada Council for the Arts (CCA). It is defined as “the exploration or integration of multiple traditional and/or contemporary artistic disciplines that are merged in such a way that no single artistic discipline dominates the final result. These transdisciplinary methods intersect the arts with other non-arts disciplines to explore a theme or issue.” This includes a practice at the junction of Art, AI, ethics, Sustainable Development Goals, human Rights, or other relevant fields to the call above.