The argument for near-term human disempowerment through AI

AI and Society:1-14 (2024)
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Abstract

Many researchers and intellectuals warn about extreme risks from artificial intelligence. However, these warnings typically came without systematic arguments in support. This paper provides an argument that AI will lead to the permanent disempowerment of humanity, e.g. human extinction, by 2100. It rests on four substantive premises which it motivates and defends: first, the speed of advances in AI capability, as well as the capability level current systems have already reached, suggest that it is practically possible to build AI systems capable of disempowering humanity by 2100. Second, due to incentives and coordination problems, if it is possible to build such AI, it will be built. Third, since it appears to be a hard technical problem to build AI which is aligned with the goals of its designers, and many actors might build powerful AI, misaligned powerful AI will be built. Fourth, because disempowering humanity is useful for a large range of misaligned goals, such AI will try to disempower humanity. If AI is capable of disempowering humanity and tries to disempower humanity by 2100, then humanity will be disempowered by 2100. This conclusion has immense moral and prudential significance.

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Leonard Dung
Ruhr-Universität Bochum

Citations of this work

Understanding Artificial Agency.Leonard Dung - 2025 - Philosophical Quarterly 75 (2):450-472.
Is superintelligence necessarily moral?Leonard Dung - 2024 - Analysis 84 (4):730-738.
Language Agents and Malevolent Design.Inchul Yum - 2024 - Philosophy and Technology 37 (104):1-19.

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References found in this work

Superintelligence: paths, dangers, strategies.Nick Bostrom (ed.) - 2003 - Oxford University Press.
Understanding Artificial Agency.Leonard Dung - 2025 - Philosophical Quarterly 75 (2):450-472.
The singularity: A philosophical analysis.David J. Chalmers - 2010 - Journal of Consciousness Studies 17 (9-10):9 - 10.
Artificial Intelligence, Values, and Alignment.Iason Gabriel - 2020 - Minds and Machines 30 (3):411-437.

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