We need to understand the effect of narratives about generative AI

Abstract

Public concerns about the societal effects of generative artificial intelligence (AI) are shaped by narratives that have the potential to influence research priorities and policy agendas. Understanding the origins and dynamics of these narratives is crucial to effectively address the actual impacts of AI and ensure a constructive discourse about its risks and potential.

This shift in media coverage points to the need for a closer examination of the underlying discourse. We currently see four main types of narratives around generative AI:

1. (1)

   The ‘existential risk’ narrative contends that existential risks from artificial superintelligence or artificial general intelligence could stem from the next generations of generative AI-type systems. As generative AI systems become more sophisticated, their capabilities could surpass human control and lead to potentially existentially catastrophic consequences. Strong versions of this narrative raise the concern that artificial superintelligence or artificial general intelligence technologies could lead to human extinction³.

2. (2)

   The ‘effective accelerationist’ narrative champions the rapid development of AI. Proponents argue that its potential benefits for solving complex global problems far outweigh the risks, and the existential risks from advanced AI are zero or near zero and so can be dismissed⁴. This narrative is driven by a strong belief in the power of AI progress to bring about substantial positive change.

3. (3)

   The ‘real, immediate societal risks’ narrative focuses only on the tangible, immediate societal risks of generative AI. It emphasizes issues such as the creation of deepfake pornography, unjust capability distribution or the growing environmental effects of generative AI, and argues that these present-day concerns are much more pressing and relevant than speculative existential risks. Proponents of this view argue that focusing on distant existential threats distracts us from addressing the real and present dangers of AI⁵.

4. (4)

   The ‘balanced risks’ narrative advocates for an approach to AI risk governance that acknowledges both the existential and immediate societal risks posed by AI. It encourages finding meaningful connections between these two classes of risks, and suggests that addressing them in tandem can lead to more comprehensive and effective risk mitigation strategies and policies⁶.