Receipts and Receipts NB

Abstract

This paper reports on two iterations of our ongoing Receipts project. The project serves as a means to experiment with and propose processes that use social practice and machine learning technologies to prepare testimonies and listeners to more clearly and impactfully speak, hear, and feel what it is like to respond to mimetic trauma and be part of an equity-deserving group in public space. The work is guided by the following question: How can the process of facilitating the preparation and presention of anonymized testimonies of discriminatory aggression in public spaces with the witnesses and victims of said agressions create structures of accountability, solidarity, healing, and community? The first project, Receipts (2020), was presented as part of The Bentway’s Safe in Public Space program in Toronto, and addressed anti-Asian aggression in public spaces. The second project, Receipts NB, in collaboration with ArtFix, an organization that works with artists with substance abuse and mental health lived experience in North Bay, will address the stigmatization and isolation of this community during the pandemic. It will be presented as part of IceFollies 2023, a week-long public art festival on frozen Lake Nipissing. These explorations emerge from and reflect upon a theoretical framework that connects visual culture, data creation, visual perception, cognition, machine learning processes, human-computer interaction, social practice and a practice-based framework for research-creation. The work is also informed by an approach to technoscience that uses a critical race, feminist, and decolonial lens. A necessary component of this framework is to prioritize equity through an emphasis on critical pedagogy, co-creation, and participatory art and design practice. The critical media art practices and processes of Receipts do not aim to replace identifying video as an important means of holding people accountable. Instead, we hope that the project can shape technical, social, cultural practices of testimony and listening and make collectivized community resistance resonate more deeply. We also reflect on how computer vision and artificial intelligence tools increasingly deployed as part of “smart city” infrastructures have been proposed as a means to address these issues in real time by predicting, identifying, and aggregating transgressions. Yet, in practice, these tools lack nuance, approximate and automate-out the importance of relationship building with communities, and have generally been used to identify patterns and build predictive surveillance that disproportionately disadvantages already discriminated-against groups. We hope that Receipts can serve as an example of how to engage the potentials of urban technology while also highlighting some of its pitfalls.