The goal of this paper is to describe the mechanism of the public perception of risk of artificial intelligence. For that we apply the social amplification of risk framework to the public perception of artificial intelligence using data collected from Twitter from 2007 to 2018. We analyzed when and how there appeared a significant representation of the association between risk and artificial intelligence in the public awareness of artificial intelligence. A significant finding is that the image of the risk of AI is mostly associated with existential risks that became popular after the fourth quarter of 2014. The source of that was the public positioning of experts who happen to be the real movers of the risk perception of AI so far instead of actual disasters. We analyze here how this kind of risk was amplified, its secondary effects, what are the varieties of risk unrelated to existential risk, and what is the dynamics of the experts in addressing their concerns to the audience of lay people.
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As we saw in the introduction, existential risks are events that threaten “to cause the extinction of Earth-originating intelligent life” (Bostrom 2002, p. 381).
A further study to show how the life cycle of this critical moment of communication of this risk perception propagated would need us to do a network analysis reconstructing the spread.
See Levy (2007). Sex bots are taken as risk for some group of people for different reasons. On the one hand, there are feminists’ groups that argues that sex bots will just enhance the gender discrimination and stereotypes. On the other hand, there are conservatives’ religious groups that are by definition against the hedonism.
The propensity to take corresponding actions may lead to behavioral patterns, which generate secondary social or economic consequences that extend far beyond direct harm to humans or the environment, including significant indirect impacts such as liability, insurance costs or loss of trust in institutions (Kasperson et al. 1988). The consequences can also be good or neutral, with the foundation of new companies and institutes, as in the case of AI. Such secondary effects often trigger demands for additional institutional responses and protective actions (like the Whitehouse Policy initiative), or conversely (in the case of risk attenuation), place impediments in the path of needed protective actions. An interesting contribution for further studies would be the analysis of how media institutions (profiles and websites) frame the risk perception of AI, how and why layman amplifies specifics risk. In this sense, the research on risk perception may benefit from further developments on the role that experts play not only in the assessment of risk, but also their communication to the public, and sometimes how they shape or formulate the risk.
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This research was funded by the São Paulo Foundation (Fapesp) grants 2018/09681-4 and 2019/07665-4 and Brazilian National Council for Scientific and Technological Development (CNPq) grant 312180/2018-7.
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Neri, H., Cozman, F. The role of experts in the public perception of risk of artificial intelligence. AI & Soc 35, 663–673 (2020). https://doi.org/10.1007/s00146-019-00924-9
- Artificial intelligence
- Social impacts of artificial intelligence
- Risk perception