Citation

Parables of AI in/from the Majority World

Author:
Singh, Ranjit; Guzmán, Rigoberto Lara; Davison, Patrick
Year:
2022

This anthology was curated from stories of living with data and AI in/from the majority world narrated at a storytelling workshop in October 2021 organized by the Data & Society Research Institute. Encounters with data and AI require contending with the uncertainties of navigating systems that are often only understood through their inputs and outputs. Storytelling offers a medium to make sense of these uncertainties. It provides a way to voice one’s own truth, make sense of mundane and ongoing struggles with computational systems, reconcile these struggles, and open a space for healing. Storytelling is also relational; it places storytellers in a relationship with a community of listeners. It is this relationship that turns a story into a parable. A story becomes a parable when it is valued by its listeners—when they take on the responsibility of passing it on. When stories cause communities to organize or when they represent a theory within scholarship, they become parables. This anthology is only one beginning to the search for parables of AI as it increasingly becomes a part of everyday life across the world. It is our hope that the search for parables of AI becomes a much larger project that will: (1) explore storytelling as a research strategy to engage with the scale and complexity of living with data and AI; (2) build a networked community of experts, activists, and practitioners willing to narrate their stories and listen to stories of others; (3) curate an anthology of stories from this community; and (4) demonstrate how storytelling events and training workshops are crucial ground for public engagement in the process of developing a shared vocabulary around the uneven challenges of living with data and AI. This ongoing effort will create a spoace from which these stories can emerge and converge, which will allow us to trace the keywords and patterns in the complexity of living in a data-driven world.