TLDR: Science Fiction Science (sci-fi-sci) is an innovative research method that applies experimental techniques to simulate future technologies and quantitatively predict their social and behavioral impacts. By immersing participants in controlled simulations of speculative futures, sci-fi-sci aims to provide early insights for guiding technology development and regulation, addressing the challenge of understanding effects before technologies are widely deployed. The method tackles validity challenges through increasing simulation fidelity and focuses on near-future, moderate-impact technologies.
Imagine being able to understand how a new technology will affect society and human behavior long before it even exists. This foresight could allow us to guide its development and create regulations proactively, rather than reacting to problems after they’ve become deeply ingrained. Traditionally, predicting the impact of future technologies has relied on qualitative, narrative approaches, but a new method called ‘science fiction science’ (sci-fi-sci) is changing this by bringing experimental methods into the mix.
Sci-fi-sci involves simulating future technologies and collecting quantitative data on how people might react to them. Think about social media: if behavioral scientists had simulated its potential effects on mental health and democratic life before its widespread adoption, we might have designed and regulated it differently, avoiding some of the issues we face today. Similarly, the public opposition to genetically modified foods in the 1990s might have been mitigated if early studies had anticipated psychological concerns.
The core idea behind science fiction science is to apply the rigorous scientific method to the speculative project of anticipating behavioral and social changes driven by technologies that don’t yet exist. Researchers recruit present-day participants and immerse them in controlled experimental simulations of possible futures. By doing so, they can measure attitudes and behaviors as participants interact with these simulated future technologies, uncovering potential benefits and harms.
A notable example of sci-fi-sci research involves autonomous vehicles. Between 2016 and 2018, studies surveyed participants on the ethical preferences they would want these vehicles to follow in unavoidable collision scenarios. Even though fully autonomous vehicles were not widely available for purchase at the time, this research allowed policy debates to take place ahead of technological developments, helping to shape ethical regulations. Another area where sci-fi-sci has been applied is in understanding how humans might cooperate with autonomous agents, like robots or advanced software, especially when their interests aren’t perfectly aligned.
However, conducting sci-fi-sci experiments comes with unique challenges, particularly regarding ‘prospective validity’ – the likelihood that findings from the lab will accurately predict real-world behavior in the future. This is tricky because the ‘real world’ the studies aim to generalize to doesn’t exist yet. Challenges include participants accurately imagining their reactions to unfamiliar future technologies, the simulated technology differing significantly from its eventual real version, and unexpected changes in the social context.
To address these challenges, researchers are experimenting with various simulation methods to increase the fidelity and immersion of the experience. These range from simple text descriptions (vignettes) to more advanced techniques like multi-modal descriptions, mock versions of futuristic apps, and even virtual and augmented reality simulations. For instance, studies on autonomous vehicle dilemmas evolved from text-based scenarios to interactive computer graphics and, most recently, virtual reality, to better immerse participants in a driverless car world. Some research even uses elaborate physical simulations, like those for Mars missions, to mimic extreme future environments.
When choosing topics for science fiction science, it’s generally best to focus on technologies that are in the near future and have a moderate impact, rather than those that are far off or would cause revolutionary societal changes. This helps minimize uncertainty and makes it easier to design valid experiments. For example, studying the immediate social acceptability of future parents selecting genetic traits for embryos is more feasible than predicting the long-term societal stigma against ‘undesigned’ persons generations later.
Also Read:
- Designing AI for Human Well-being: A New Framework for Human-AI Interaction
- A New Lens for AI Regulation: Focusing on Freedom and Societal Impact
While sci-fi-sci is not a completely new field, it aims to unify disparate research efforts under a common banner, fostering a community dedicated to developing robust methods for studying future human behavior. This approach offers a powerful way to anticipate and guide the development of emerging technologies, ensuring we are better prepared for the future they bring. To learn more about this fascinating field, you can read the full research paper here.
