✍️ By Ismael Kherroubi Garcia.
Ismael is Founder & Co-lead of the Responsible Artificial Intelligence Network (RAIN), and Founder & CEO of Kairoi.
📌 Editor’s Note: This article is part of our Tech Futures series, a collaboration between the Montreal AI Ethics Institute (MAIEI) and the Responsible Artificial Intelligence Network (RAIN). The series challenges mainstream AI narratives, proposing that rigorous research and science are better sources of information about AI than industry leaders. This seventh instalment of Tech Futures by RAIN celebrates our upcoming Crafting Participatory Tech Futures workshop at FAccT, which turns AI governance on its head, centring self-reflection and storytelling in the process of designing the future of AI.
The direction of technological progress often seems out of reach. Political leaders are at the helm of artificial intelligence (AI) policy and regulation. Tech billionaires are peddling the technologies and infrastructures that best suit their interests. Executives at universities, businesses and nonprofits are driving the adoption of AI tools to bring costs down at the expense of any social good they might otherwise produce. AI feels unavoidable, and we—the 99%—can’t do anything about it.
The future role of AI in society seems inevitable, but we wholeheartedly disagree. In the most recent State of AI Ethics Report, Ana Brandusescu, researcher at McGill University, reminded us of workers organizing against Big Tech firms for exploiting data workers. Both Brandusescu and Blair Attard-Frost, professor at the University of Alberta, also brought up the 2023 union strike against the misuse of AI in the American film industry. Attard-Frost specifically denounces “what policy researcher Inga Ulnicane refers to as ‘governance fixes’: centralized, top-down practices of policymaking and decision-making that favour a ‘narrow and technocratic approach’ to AI governance.” It is this centralized, top-down approach that we—RAIN and MAIEI—believe makes AI seem inevitable.
There are many approaches to countering the seemingly inevitable nature of AI. Tania Duarte and colleagues from the We and AI community suggest a taxonomy of initiatives to counter AI inevitability narratives: resisting, refusing, reclaiming and reimagining. Roughly, each item can be defined as follows:
- Resisting is about organizing and standing against a wide range of AI technologies and practices on the basis of a deep understanding about how they perpetuate socioeconomic injustices;
- Refusing can be based on a similar understanding of AI but takes the form of more individualized, local and/or targeted stances, such as refusing to use large language models in educational contexts;
- Reclaiming is about building AI technologies and promoting AI practices that centre the needs and interests of a grassroots or minoritized community, thus making AI more responsive to local or socially-determined needs; and
- Reimagining taps into historical and marginalized forms of knowing to design more inclusive technologies that are respectful of diverse social and natural environments.
Reimagining AI may be the most abstract approach to the future of AI, but it is also the most visionary. We can resist, refuse and reclaim activities and technologies that are past and present but what follows needn’t be defined. Reimagining turns AI governance on its head, placing the tech futures we want to see as the starting point.
See you at FAccT ‘26!
Led by the Responsible Artificial Intelligence Network (RAIN), in partnership with MAIEI, and with support from We and AI, the San Diego Supercomputer Centre, and Kairoi, we will be running the workshop Crafting Participatory Tech Futures during the Fairness, Accountability and Transparency (FAccT) conference in Montreal, June 25-28.
The workshop will ignite conversations revolving around RAIN’s responsible AI diagram, which defines responsible AI as “an AI lifecycle that is inclusive of diverse stakeholders who strive for social justice and inform better AI narratives and governance practices.” The diagram also captures four futures that RAIN “strives for.”
Harmonious Knowledge Systems: Diverse forms of knowledge are open to one another. Insights can be gained from new links between geographically, linguistically and culturally distinct perspectives on the world. Science is enriched by new connections between knowledge-building artefacts, such as libraries, universities, oral histories and science labs.
Attuned to Nature: Human activity enables a healthy natural environment. Humanity is at peace with nature, and technological advancements serve to strengthen this relationship. More specifically, we approach AI in a way that is conscious of its environmental impacts, ensuring minimal or even positive impact throughout the AI lifecycle.
Intentional Social Impacts: We advance AI technologies and research in a way that is intentional in their social impacts. On the one hand, comprehensive impact assessments are common practice, and “unintended consequences” are considered thoroughly. On the other hand, pertinent decision makers, policy makers, institutions and organisations are held to account where errors occur.
Equitable Innovations: Nuanced understandings of real human needs inform targeted technological innovations. Commercial opportunity is secondary to the social gains made through thoughtful innovations. AI technologies are reconceptualised as solutions to real problems.
Embracing the spirit of reimagining AI, workshop participants will be asked to tap into their own lived experiences, and to share stories that help articulate the technological practices and artefacts that matter to them. The workshop format, described in its proposal, will mean leaving theory and preconceptions about AI at the door, ultimately prioritizing:
- Story-telling over scripts,
- Holistic understandings over binaries, and
- Embodied knowledge over computationalist notions of cognition.
The workshop is just the start; there will be many opportunities to contribute, whether people can make it to FAccT or not. There are two newsletters to receive specific updates about the ongoing initiative, and we hope you will join!
Image credit: Deborah Lupton / Better Images of AI / CC BY 4.0