If it sounds like science fiction, it sort of is. \u201cScience fiction science\u201d or \u201csci-fi-sci\u201d is an idea put together by researchers Iyad Rahwan (from the Max Planck Institute for Human Development in Germany), Azim Shariff (from the University of British Columbia in Canada), and Jean-Francois Bonnefon (from the Toulouse School of Economics in France). They describe it as a new process that attempts to apply the scientific method<\/a> to technologies that are either being planned or are in the early phases of development. Such predictions have been made in science fiction before, but outside of the genre, they have never been fully explored from a scientific perspective.<\/p>\n Related Story<\/p>\n \u201cPredicting 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,\u201d the researchers said in a study posted to the preprint server arXiv<\/a>. \u201c[We use] experimental methods to simulate future technologies, and collect quantitative measures of the attitudes and behaviors of participants assigned to controlled variations of the future.\u201d<\/p>\n Rahwan, Shariff, and Bonnefon suggest that using the scientific method to predict the effects of technologies that will likely surface in the near future (though, what exactly \u201cnear future\u201d means can be hazy) will make their potential effects more clear to developers, consumers, and policymakers. This unconventional approach has been met with skepticism, as experimental scientists understandably tend to question its validity. But the trio has pushed on. Using social media<\/a> as an example, they suggest that in retrospect, running simulations of how the technology might have operated and having participants virtually interact with it could have helped predict the aftermath of its widespread use, from self-esteem issues to ethics being seriously questioned.<\/p>\n Predicting the effects of social media before everyone was constantly checking socials on their smartphones might have led to a more cautious outlook. For instance, effects of the technology gone to extremes become a dystopian reality on the Black Mirror episode \u201cNosedive,\u201d<\/a> where social media not only broadcasts people\u2019s lives, but social scores that help gauge their popularity and use that data to rank them among their peers. And the scoring technology suggested in this episode is on the edge of being released into society<\/a>. <\/p>\n Gage<\/a> is an app that keeps track of how employees are rated by coworkers. Created by founder and CEO Justin Henshaw, it logs a \u201csocial credit score,\u201d includes the number of compliments and virtual high-fives given, and is meant to be transferred from one job to another. YouTube creator Joshua Fluke criticized Gage<\/a> as \u201can algorithmic reputation system\u201d that could be extremely problematic. When employee evaluation relies more heavily on social scores than the quality of actual work done, entire groups could suffer. Those who are neurodivergent and may not communicate<\/a> in the expected neurotypical way could face difficulty being hired as a result of codified negative social feedback.<\/p>\n Related Story<\/p>\n The researchers describe social credit systems on an even larger scale than Black Mirror, and list them among other types of what they refer to as \u201cnascent or speculative technologies\u201d that could potentially spark policy debates. Hypothetical systems that use AI to monitor every behavior in real time before publicly releasing social credit scores have sparked so much controversy that the European Union<\/a> is leaning toward preemptively banning them.<\/p>\n On the same list are autonomous vehicles, the process of screening embryos for desired traits, and ectogenesis (reminiscent of the artificial gestation in Aldous Huxley\u2019s Brave New World). <\/p>\n \u201cStudying the behavior of future humans<\/a> interacting with future technology in a future social world raises unusual challenges for behavioral scientists, which call for unconventional methods,\u201d the researchers said<\/a>. <\/p>\n