Evidence map›Paper›PMID 40770437›Full record

ReviewNature2025

The science fiction science method.

Iyad Rahwan, Azim Shariff, Jean-François Bonnefon

Abstract readReview
PubMed Publisher
In one paragraph

Review in Nature, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Iyad RahwanCenter for Humans and Machines, Max Planck Institute for Human Development, Berlin, Germany. rahwan@mpib-berlin.mpg.de.ORCID 0000-0002-1796-4303
Azim ShariffDepartment of Psychology, University of British Columbia, Vancouver, British Columbia, Canada. shariff@psych.ubc.ca.
Jean-François BonnefonToulouse School of Economics, CNRS (TSM-R), University of Toulouse-Capitole, Toulouse, France. jean-francois.bonnefon@tse-fr.eu.ORCID 0000-0002-4959-188X

Funding

Canada 150 Research Chair from the Social Science Research Council of CanadaTSE–Partnership
6 · The paper itself

Abstract

Predicting the social and behavioural impact of future technologies before they are achieved would enable 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 that uses experimental methods to simulate future technologies and collect quantitative measures of the attitudes and behaviours of participants assigned to controlled variations of the future. We call this method 'science fiction science'. We suggest that the reason that this method has not been fully embraced yet, despite its potential benefits, is that experimental scientists may be reluctant to engage in work that faces such serious validity threats. To address these threats, we consider possible constraints on the types of technology that science fiction science may study, as well as the unconventional, immersive methods that it may require. We seek to provide perspective on the reasons why this method has been marginalized for so long, the 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.

Indexed as

Research PersonnelScienceAttitudeForecastingHumansReproducibility of Results

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.