Sinha’s experience building stories in sound applies to his work using machine learning and AI tools by materially engaging with the technology and assumptions underlying machine learning applications addressing the audio domain. Seeking human-centred outcomes, Sinha continues the process (shared by many) of building new cultural futures that embrace and imagine storytelling as something deeply embedded in and expanded by the technologies we use to create them.
Applying machine learning processes to ‘lived’ sound – live recordings, in personally and culturally significant moments/places – is a compelling use and exploration of the edges of what machine learning can do for our communities. This exploration is very in line with the workshop’s aim to understand what attempts at liberatory machine learning…could look like in our imagined futures
– reviewer, Resistance AI workshop @ NeurIPS 2020 on ds’ work Dhakuria Bridge
In Sinha’s ML works we confront a world just outside of our understanding, a cloud of ideas and concepts that nonetheless remain connected to our innermost impulses. An idea of technology as cultural practice and an embrace of criticism and criticality as part of a process of true techno-optimism.
His audio and audiovisual works and performances using machine learning and AI have been shown at NeurIPS, the Museum of Contemporary Art (Toronto), Poesiefestival Berlin, the Royal Anthropological Institute’s 2022 Conference “Anthropology, AI and the Future of Human Society”, and Prefix Gallery Toronto, among other venues.
[This research is] at its heart about expanding the conversation around storytelling and ways in which we communicate culture. It’s also very directly about questioning what we consider to be valid systems of knowledge, and why and how that validity has been and continues to be assigned, and by whom
Listen to an interview on Wave Farm discussing this approach with NAISA’s artistic director Darren Copeland.
A conversation with choreographer and academic Shanti Pillai on Sinha’s approach to AI in storytelling and cultural transmission is featured in Theatre Journal, published by Johns Hopkins University Press.
Further documentation of machine learning and AI works here. Check the “Now” page for other upcoming exhibitions and projects.