Rahwan Iyad, Shariff Azim, Bonnefon Jean-François
Center for Humans and Machines, Max Planck Institute for Human Development, Berlin, Germany.
Department of Psychology, University of British Columbia, Vancouver, British Columbia, Canada.
Nature. 2025 Aug;644(8075):51-58. doi: 10.1038/s41586-025-09194-6. Epub 2025 Aug 6.
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.
在未来技术实现之前预测其社会和行为影响，将使我们能够在这些影响根深蒂固之前引导其发展和监管。传统上，这种预测依赖于定性的叙述方法。在此，我们描述一种方法，该方法使用实验方法来模拟未来技术，并收集分配到未来不同受控变体的参与者的态度和行为的定量测量数据。我们将这种方法称为“科幻科学”。我们认为，尽管这种方法有潜在益处，但尚未被充分接受的原因是实验科学家可能不愿从事面临如此严重效度威胁的工作。为应对这些威胁，我们考虑科幻科学可能研究的技术类型的可能限制，以及它可能需要的非常规沉浸式方法。我们试图就该方法长期被边缘化的原因、如果能基于强大但不寻常的方法建立该方法将带来的益处，以及如何使这些方法常态化以帮助不同的科幻科学家群体参与效度提升的良性循环提供观点。
