As an artist working with experimental technologies, hacking/re-purposing tools to create artistic works I’m often looking for ways in which I can create intimate shared experiences. Even before the pandemic, a lot of my practice was being conducted solely through computer based interactions due to a lack of funding and other resources. This mode of working allowed me to focus my practice towards making accessible works and I began thinking about the language, technology and context accessibility of my works within a larger contemporary art conversation.Continue reading “04 ಕಥೆ Kathe (Story) / Dematerialise”
‘your dataset won’t let me thrive / your dataset must die’ are a pair of video essays that seek to counter the mythologies surrounding Artificial Intelligence datasets & algorithms They are carried out as a comparative study of the works of the Black Beat Poet Bob Kaufman and the Kannada Dalit poet Siddalingaiah whose words (translation) are input into the text based neural network GPT-2. The visual aesthetics of the work are drawn from generative AI imagery of brown faces, creative programming as well as animated representation of the words of each poet alongside text generated by the algorithm. The inability of the algorithm to generate text drawn from sufficient references to Black & Bahujan lived experiences reveal the encoded biases within the dataset and trace their origins to harmful mythologies of Caste & Race.
The works were commissioned by the Mozilla Foundation as part of the Reclaiming AI Futures project for the AI Observatory (https://ai-observatory.in/)
Over the last two years, I’ve been developing a theoretical and critical framework titled ‘Subaltern Futurism’. Subaltern Futurism is envisioned as a speculative resource framework for artistic research, practice and the technological education of marginalised. Drawing from anti-caste literature, critical race theory, bahujan solidarity practices among other guiding experiences, it asks if artistic practice can become pedagogical tools to communities that are excluded from regular access to critical discourse around contemporary art & technology. The framework views technology through a sociological lens, as a fundamental right and shared resource. It expands upon Gramsci’s post-colonial notion of the Subaltern as ‘colonial populations who are excluded from the hierarchy of power’ to include the current state of digital colonisation, the shared sites for the digital commons and sections of technology users rendered ‘subaltern’ due to the capitalist pursuit of efficiency. Subaltern Futurism speculates that developing empathic relationships with technology through a range of critical & pragmatic actions can assist in the imagination of radical futures that are diverse, inclusive and conducted from multiple geographies especially arising from the global south and from contexts outside of euro-centric biases of inquiry. By considering a very wide scope at the outset, it is envisioned as a multi-year generative project occurring as various modular forms and widely disseminated within the ethos of open access.Continue reading “02 Subaltern Futurism”
In 2020, I was able to bring the ideas behind Subaltern Futurism as a speculative framework into my practice through my work Swaayattate (Autonomy). The work is an investigation into the complex entanglements of the synthetic and organic worlds. Taking the form of a bi-lingual trilogy, the films are set inside a computer repair marketplace in Bangalore and examines the nature of human-machine relationships through the contemporary lens of gender, caste and labour. The narrative moves between multiple timelines as the evolution of an embedded neural network references prescient concerns around language, accessibility and justice.
Portions of the script for the films were written in collaboration with a text based neural network GPT-2 Transformer (https://transformer.huggingface.co/) extracting & revealing the extent of encoded biases within this AI model. GPT-2 is essentially a text generator similar to the autocomplete functions on our phones. You can input words or sentences and the neural network generates the next word or sentence using pre trained machine-learning models. Widely hailed as being very close to human speech and syntax, my interactions with the language model has proven this to be highly misleading as they contain encoded biases brought over from the subjectivity of the programmers and its own training data. Chapter 2 ADI, speculates upon this process of transference of social biases into algorithmic ones.
Excerpt from Swaayattate (Autonomy)