Cultural Research: Please Don't Understand This
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Cultural research can complement and enhance traditional research when dealing with complex and multifaceted issues such as climate change, technological volatility, and rising authoritarianism. These issues often require integrating subjective experiences, emotional responses, and diverse perspectives, which are areas where we excel. Our past cultural research has generated deep insights into individual and collective experiences.
Example: Please Don’t Understand This
Much of the debate about AI has prioritized the exploration of a small number of theoretical, ethical, and ideological principles and consideration of what should underpin policies and public interest in the deployment of these systems.
Overwhelmingly, the ethics that emerge on all sides of the debate extend from Western ideologies and traditions. However, the ultimate objective ought to be effective governance of these extremely powerful tools. Good governance requires meaningful participation from affected communities. Meaningful participation requires literacy to discuss and explore socio-technical systems.
“Please Don’t Understand This”, as part of the Goethe-Institut Toronto’s Algorithmic Culture programming, invited creators in communities closest to the impacts of AI to imagine their own visual symbols and languages to share their experiences of living with artificial intelligence and surveillance. Works by artists in Beijing, China; Dzaleka, Malawi; and Cairo, Egypt were then shared and remixed by diasporic Toronto-based creators. The goal was to communicate in ways that confuse those that administer these systems and as an alternative to the abstracted approaches of Western ethical traditions.
The outputs from this process revealed new depth and nuance to the experiences of those closest to AI systems, capturing emotions, motivations, and values that were overlooked by traditional research. Moreover, these kinds of cultural methods encourage the exploration of new ideas, fostering the development of novel solutions and approaches that traditional research might not achieve.