Concept 2: Science Fiction Science

To anticipate the impact of future technologies on humans, we combine our imagination of possible futures with a scientific approach to studying behavior.

Regulators and the momentum of emerging technologies face the so-called Collingridge dilemma (Collingridge, 1982):

• Information Paradox: Early in development, technology is easy to change but its potential impact is unknown, making control difficult.
• Control Paradox: Once mature, consequences are clear, enabling informed control, but the technology is entrenched and hard to regulate. 

One way to mitigate the dilemma is to make regulation more responsive and technology design more agile. But, in addition, can we improve our ability to predict the societal impact of technologies?

Technological forecasting is already a well-established field. But it is largely based on qualitative methods (e.g. Delphi method to elicit expert opinion about technology readiness) or computer simulation (e.g. of the dynamics of adoption of autonomous vehicles). But these approaches lack the behavioral measurement and experimental control characteristics of behavioral science.

Science Fiction Science (Sci-Fi-Sci) (Rahwan et al., 2025), a concept developed at the Center, immerses humans in different simulated futures—each representing a distinct version of a future technology design or regulatory framework. People's reactions, beliefs, and behaviors are then observed, analyzed, and tested. This allows us to anticipate problems, informing policymaking and design, before the technology is fully deployed.

This approach has already yielded impactful foresight, from the power of social media to mobilize people at scale (Pickard et al., 2011), the ethical dilemmas facing the regulation and design of self-driving cars (Awad et al., 2019), to the likely increase in tax fraud when humans can delegate tasks to AI agents (Köbis, Rahwan, et al., 2025). In an era of accelerating technological progress, the Sci-Fi-Sci method holds enormous potential to help us prepare, rather than simply react, to technology's impact on humans.

Science fiction author Isaac Asimov said, "A good science-fiction story should be able to predict not the automobile but the traffic jam." The Center's goal is to predict the traffic jams of future digital technologies.

Key References

• Köbis, N., Rahwan, Z., Rilla, R., Supriyatno, B. I., Bersch, C., Ajaj, T., Bonnefon, J.-F., & Rahwan, I.(2025). Delegation to artificial intelligence can increase dishonest behaviour. Nature, 646, 126–134. https://doi.org/10.1038/s41586-025-09505-x

  [These authors contributed equally: Nils Köbis, Zoe Rahwan. These authors jointly supervised this work: Jean-François Bonnefon, Iyad Rahwan.].

• Rahwan, I., Shariff, A. & Bonnefon, JF. The science fiction science method. Nature 644, 51–58 (2025). https://doi.org/10.1038/s41586-025-09194-6 

• Awad, E., Dsouza, S., Kim, R., Schulz, J., Henrich, J., Shariff, A., Bonnefon, J.-F., & Rahwan, I. (2018). The Moral Machine experiment. Nature, 563(7729), 59–64. https://doi.org/10.1038/s41586-018-0637-6

• Pickard, G., Pan, W., Rahwan, I., Cebrian, M., Crane, R., Madan, A., & Pentland, A. (2011). Time-Critical Social Mobilization. Science, 334(6055), 509–512. https://doi.org/10.1126/science.1205869

Other Guiding Concepts