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<p>This paper presents an integrative narrative review of the tacit background assumptions underlying AI existential risk (X-risks) futures. Once confined to science fiction, concerns about AI X-risks now shape debates at the crossroads of the tech world, NGOs, politics and (social) media. Despite growing attention, the plausibility of AI surpassing human controllability remains highly contested. Examining 81 peer-reviewed papers from Scopus and Web of Science, we find a fragmented discourse characterized by bold yet often unsubstantiated claims, including accelerationist growth models and speculative calculations of catastrophic tipping points. Anthropomorphic and speculative AI conceptualizations prevail, while interdisciplinary perspectives that consider issues of infrastructure, social agency, Big Tech power position and politics remain scarce. Delineating how these speculative tendencies are detrimental to the current regulatory need to tackle AI harms, we deduce an AI X-risk heuristic and advocate for a shift in attention from the maximum possible negative consequences to the structural and socio-technical characteristics of how AI is embedded—which are the prerequisites for any AI futures to emerge.</p>

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AI going rogue? An integrative narrative review of the tacit assumptions underlying existential AI-risks

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年2月9日

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  • Jascha Bareis,
  • Clemens Ackerl,
  • Reinhard Heil

摘要

This paper presents an integrative narrative review of the tacit background assumptions underlying AI existential risk (X-risks) futures. Once confined to science fiction, concerns about AI X-risks now shape debates at the crossroads of the tech world, NGOs, politics and (social) media. Despite growing attention, the plausibility of AI surpassing human controllability remains highly contested. Examining 81 peer-reviewed papers from Scopus and Web of Science, we find a fragmented discourse characterized by bold yet often unsubstantiated claims, including accelerationist growth models and speculative calculations of catastrophic tipping points. Anthropomorphic and speculative AI conceptualizations prevail, while interdisciplinary perspectives that consider issues of infrastructure, social agency, Big Tech power position and politics remain scarce. Delineating how these speculative tendencies are detrimental to the current regulatory need to tackle AI harms, we deduce an AI X-risk heuristic and advocate for a shift in attention from the maximum possible negative consequences to the structural and socio-technical characteristics of how AI is embedded—which are the prerequisites for any AI futures to emerge.