As the science fiction writer William Gibson famously observed, “The future is already here—it’s just not very evenly distributed." The unevenness of the future is particularly apparent in the field of artificial intelligence (AI). Although the capabilities of AI technologies continue to advance at a meteoric pace, they are already disproportionately affecting some sectors of society more than others—and empowering some members of society more than others. Proactive efforts to democratize AI technologies will be crucial to protect civil rights and mitigate long-term societal impacts. Yet expanding the accessibility of AI tools also portends a volatile future of risks and dangers: a potential deluge of disinformation and deepfake media, prolific violations of privacy and security, systemic practices of algorithmic discrimination, and even new forms of high-tech warfare. How can we defragment the AI future, improving both public knowledge and public oversight, while also critically engaging with the ramifications of a future in which human intelligence is everywhere coupled with machine intelligence? If our current ways of imagining AI seem caught between the antinomies of promise and peril, control and freedom, and utopia and apocalypse—a relentlessly uneven future, without end—how can we imagine otherwise?
The Center for Artificial Intelligence and Experimental Futures (CAIEF) at UC Davis addresses these challenges by studying techniques of creative worldmaking, focusing on the significance of cultural narratives, discursive practices, and media representations in shaping AI technologies and the dynamics of human–AI collaboration. The concept of experimental futures underscores that the shape of things to come is not predetermined but can be designed, tested, and implemented through collective efforts to think through and beyond the givens of the present. CAIEF takes an approach to experimental futures that combines fundamental research on the social dimensions of AI with forward-looking research on designing sociotechnical systems.
On the one hand, CAIEF studies how AI technologies are wrapped in futuristic narratives and promises born from science fiction and a long history of scientific speculations. Ways of thinking about the future inevitably affect decisions about AI in the present and influence the course of its development, constituting a powerful feedback loop. Through a set of focused research projects, CAIEF examines the social processes that make some AI futures imaginable while making others unimaginable. By showing how particular AI futures become actionable, CAIEF also addresses disparities of access and representation that may produce an uneven tapestry of prospects and perils to come.
On the other hand, CAIEF experiments with possible AI futures directly, building from humanities research on participatory culture to show how audiences, users, and consumers can creatively influence media discourses, technological systems, and high-tech practices. By using narrative-driven methods of public engagement and participatory design practices, CAIEF involves stakeholders in future-making experiments, prototyping democratic modes of AI governance and responsible innovation. By engaging stakeholder communities in participatory workshops designed to illustrate how futures get made, our research teams gather a variety of perspectives, identifying innovative solutions and potential dilemmas. Approaching AI as a nexus of experimental futures emphasizes our shared responsibility in crafting the world of tomorrow.
By attending to experimental futures, CAIEF takes the democratization of AI as both its central research question and its horizon of action. Our concerns include: enhancing AI access, oversight, and accountability; cultivating critical AI literacies (skills not only for using AI but also for understanding algorithmic models and their social embeddings); providing individuals with meaningful control over how their data is used by AI; and involving the public in the design, assessment, and deliberative governance of AI systems. We also explore civic practices and ethical responsibilities in sociotechnical systems that involve both human actors and intelligent machines. CAIEF studies the implications of democratizing AI in a variety of domains, concentrating on three core research nodes: 1) Cultural Imaginaries; 2) Languages and Literacies; and 3) Civic Infrastructures.