Science Fiction as a Science Driver
One August morning when I was walking my dog in my Capitol Hill neighborhood, I spotted signs posted to the trunks of street trees. The signs featured a photo of a family’s lost cat. What surprised me was the poster’s request that neighbors check video footage from their doorbell cameras for sightings of the missing pet.
Doorbell cameras are examples of active pixel sensors, in which each pixel consists of a photodetector connected to one or more transistors. The technology was invented in 1967 by physicist and engineer Peter J. W. Noble, whose employer, UK electronics company Plessey, asked his team to develop a camera that could interpret the numbers on paper bank checks.
The decades-long journey from check readers to doorbell cameras got me thinking about how difficult it can be to anticipate future technologies, their uses, and their ramifications. Science-fiction authors eagerly take up that gauntlet. “[A] good science-fiction story should be able to predict not the automobile but the traffic jam,” wrote the prolific sci-fi-writer Frederik Pohl, citing an old saying [1].
Pohl’s quote appears in a recent Nature article by computer-scientist Iyad Rahwan of the Max Planck Institute for Human Development in Germany and collaborators [2]. In “The science fiction science method,” Rahwan and company tackle the problem of anticipating and regulating future technologies, mentioning the so-called Collingridge dilemma: “When change is easy, the need for it cannot be foreseen; when the need for change is apparent, change has become expensive, difficult, and time-consuming” [3].
Resolving the Collingridge dilemma is important, Rahwan and company argue. People might be more accepting of genetically modified food now if their concerns had been discussed before the foods were introduced in the 1990s. Likewise, some of the adverse effects of social media on mental health and political discourse might have been foreseen. In fact, researchers at Facebook did evaluate the psychological effects of contagious peer pressure—but only 8 years after the company opened its platform to all users over the age of 13 [4].
Rahwan and colleagues propose conducting behavioral experiments in which participants are placed in futuristic scenarios. There, participants become aware of, and interact with, a technology that is both mature enough to be plausibly simulated and immature enough that its realization is not imminent.
Increasingly capable virtual-reality equipment makes the researchers’ approach increasingly feasible. The bigger challenge, they admit, comes with the scenarios. Present-day participants might not respond in the same way as their future counterparts. The technology might never be developed, or it might go off in a different direction. Our or a future society might be too different from today’s society for a study to be relevant. With those concerns in mind, Rahwan and company advocate testing only near-term technologies, such as autonomous vehicles, embryo screening, and social-credit systems that monitor citizens and assign them scores on the basis of their good or bad behavior.
The researchers lay out various ways for simulating future scenarios. One method envisages immersing participants in “a realistic physical simulation of a future situation.” The example they give is a human employee obeying the directions of a robot boss (most likely a human actor in a robot suit or a remotely operated puppet). I’m skeptical. Participants would know that they are in a simulation, and that knowledge would be hard for them to ignore.
But we readily suspend our disbelief when we read or watch science fiction. Charlie Brooker’s dystopian TV anthology series Black Mirror often hinges on modest extrapolations of current technologies, such as artificial intelligence, the Internet of Things, and industrial robots. The opening episode, “Nosedive,” of the show’s third season explored the consequences of trying—and spectacularly failing—to boost one’s online reputation. I contend that viewers of “Nosedive” were more deeply engaged in the question of social credit than they would have been if immersed in a so-called realistic physical simulation of a future society. For simulations to become as compelling as science fiction, they might have to become as realistic as those in the holodeck onboard the USS Enterprise and other Star Trek spaceships.
In 2019 at the age of 78, Noble wrote a memoir for a local newspaper, the Marshwood Vale Magazine. He closed with a note of hope. “One of my unfulfilled ambitions was to use what I had invented to help give blind people sight,” he wrote. “We have the image sensors, but the snag has always been how to connect them to the brain. Maybe it will happen one day.”
Noble’s remarks remind us that most technologies are developed for profit, like the active pixel sensor, or to make the world better, like artificial retinas. The motives are not mutually exclusive. Rahwan and his collaborators make a strong case for evaluating the social impacts of future technologies before they reach commercial viability. Ironically, their science-fiction-science method will be more successful the closer it resembles science fiction. Once virtual-reality technology has matured, the method could yield its best results when participants are told they are participating in a work of fiction rather than in a scientific study.
Correction (4 February 2026): The original caption gave the mistaken impression that the space settlement in the figure is one of Gerard O’Neil’s designs. In fact, the depicted design is a Stanford Torus, which came out of a 1975 study by NASA and Stanford University.
—Charles Day
Charles Day is a Senior Editor for Physics Magazine.
References
- F. Pohl, “Editorial: The great new inventions,” Galaxy Magazine 27, 6 (1968).
- I. Rahwan et al., “The science fiction science method,” Nature 644, 51 (2025).
- D. Collingridge, The Social Control of Technology (F. Pinter, London, 1980)[Amazon][WorldCat].
- A. D. I. Kramer et al., “Experimental evidence of massive-scale emotional contagion through social networks,” Proc. Natl. Acad. Sci. U.S.A. 111, 8788 (2014).