Crying wolf: Warning about societal risks can be reputationally risky

Lucius Caviola (Global Priorities Institute University), Matthew Coleman (Northeastern University), Christoph Winter (ITAM & Harvard) and Joshua Lewis (New York University)

GPI Working Paper No. 15-2024

Society relies on expert warnings about large-scale risks like pandemics and natural disasters. Across ten studies (N = 5,342), we demonstrate people’s reluctance to warn about unlikely but large-scale risks because they are concerned about being blamed for being wrong. In particular, warners anticipate that if the risk doesn’t occur, they will be perceived as overly alarmist and responsible for wasting societal resources. This phenomenon appears in the context of natural, technological, and financial risks and in US and Chinese samples, local policymakers, AI researchers, and legal experts. The reluctance to warn is aggravated when the warner will be held epistemically responsible, such as when they are the only warner and when the risk is speculative, lacking objective evidence. A remedy is offering anonymous expert warning systems. Our studies emphasize the need for societal risk management policies to consider psychological biases and social incentives.

Other working papers

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There has been widespread endorsement from the academic and philanthropic communities on the new model of giving cash to those in need. Yet the recipient’s perspective has mostly been ignored. The present research explores how food-insecure individuals feel and respond when offered either monetary or food aid from a charity. Our results reveal that individuals are less likely to accept money than food aid from charity because receiving money feels relatively more shameful and relatively less socially positive. Since many…

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The singularity hypothesis is a radical hypothesis about the future of artificial intelligence on which self-improving artificial agents will quickly become orders of magnitude more intelligent than the average human. Despite the ambitiousness of its claims, the singularity hypothesis has been defended at length by leading philosophers and artificial intelligence researchers. In this paper, I argue that the singularity hypothesis rests on scientifically implausible growth assumptions. …