# The Science Fiction Science Method

arXiv: https://arxiv.org/abs/2508.03430 · HTML: https://mlsanity.com/paper/2508.03430/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- Builds on 5 of its 104 references that are in the map.
- First posted on arXiv 5 Aug 2025.

## Builds on (most cited first, 5 of 5)

- [Sparks of Artificial General Intelligence: Early experiments with GPT-4](https://mlsanity.com/paper/2303.12712/) (2023)
- [The social dilemma of autonomous vehicles](https://mlsanity.com/paper/1510.03346/) (2015)
- [Cooperating with Machines](https://mlsanity.com/paper/1703.06207/) (2017)
- [Ethical Decision Making During Automated Vehicle Crashes](https://mlsanity.com/paper/2010.16309/) (2020)
- [Artificial Intelligence can facilitate selfish decisions by altering the appearance of interaction partners](https://mlsanity.com/paper/2306.04484/) (2023)

## Built on by (most cited first, 4 of 4)

- [Mental Models of Autonomy and Sentience Shape Reactions to AI](https://mlsanity.com/paper/2512.09085/) (2025)
- [Agent-Supported Foresight for AI Systemic Risks: AI Agents for Breadth, Experts for Judgment](https://mlsanity.com/paper/2602.08565/) (2026)
- [Afterlife Delegation Protocol: Speculative Design of Self-Sovereign Agents that Outlive Their Principals](https://mlsanity.com/paper/2608.15405/) (2026)
- [Spook the Machine: Gamified Exploration of Human Imagination of Machine Fear](https://mlsanity.com/paper/2609.15472/) (2026)

## Abstract (arXiv)

Predicting the social and behavioral impact of future technologies, before they are achieved, would allow us to guide their development and regulation before these impacts get entrenched. Traditionally, this prediction has relied on qualitative, narrative methods. Here we describe a method which uses experimental methods to simulate future technologies, and collect quantitative measures of the attitudes and behaviors of participants assigned to controlled variations of the future. We call this method 'science fiction science'. We suggest that the reason why this method has not been fully embraced yet, despite its potential benefits, is that experimental scientists may be reluctant to engage in work facing such serious validity threats as science fiction science. To address these threats, we consider possible constraints on the kind of technology that science fiction science may study, as well as the unconventional, immersive methods that science fiction science may require. We seek to provide perspective on the reasons why this method has been marginalized for so long, what benefits it would bring if it could be built on strong yet unusual methods, and how we can normalize these methods to help the diverse community of science fiction scientists to engage in a virtuous cycle of validity improvement.