mlsanityData to 7 Oct 2026

Making AI Inevitable: Historical Perspective and the Problems of Predicting Long-Term Technological Change

arXiv 2508.16692 ↗First posted 21 Aug 2025cs.CY cs.AI cs.ETcited by 1

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Abstract (arXiv)

This study demonstrates the extent to which prominent debates about the future of AI are best understood as subjective, philosophical disagreements over the history and future of technological change rather than as objective, material disagreements over the technologies themselves. It focuses on the deep disagreements over whether artificial general intelligence (AGI) will prove transformative for human society; a question that is analytically prior to that of whether this transformative effect will help or harm humanity. The study begins by distinguishing two fundamental camps in this debate. The first of these can be identified as "transformationalists," who argue that continued AI development will inevitably have a profound effect on society. Opposed to them are "skeptics," a more eclectic group united by their disbelief that AI can or will live up to such high expectations. Each camp admits further "strong" and "weak" variants depending on their tolerance for epistemic risk. These stylized contrasts help to identify a set of fundamental questions that shape the camps' respective interpretations of the future of AI. Three questions in particular are focused on: the possibility of non-biological intelligence, the appropriate time frame of technological predictions, and the assumed trajectory of technological development. In highlighting these specific points of non-technical disagreement, this study demonstrates the wide range of different arguments used to justify either the transformationalist or skeptical position. At the same time, it highlights the strong argumentative burden of the transformationalist position, the way that belief in this position creates competitive pressures to achieve first-mover advantage, and the need to widen the concept of "expertise" in debates surrounding the future development of AI.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 8 of its 79 references that are in the map. First posted on arXiv 21 Aug 2025.

Builds on

8 of 79 references.

References · 8

  1. 2023The Curse of Recursion: Training on Generated Data Makes Models Forgetcited by 343
  2. 2023The Impact of AI on Developer Productivity: Evidence from GitHub Copilotcited by 264
  3. 2023GPTs are GPTs: An Early Look at the Labor Market Impact Potential of Large Language Modelscited by 174
  4. 2023Levels of AGI for Operationalizing Progress on the Path to AGIcited by 94
  5. 2021Why AI is Harder Than We Thinkcited by 40
  6. 2016Long-Term Trends in the Public Perception of Artificial Intelligencecited by 22
  7. 2024Scenarios for the Transition to AGIcited by 13
  8. 2025Future progress in artificial intelligence: A survey of expert opinioncited by 6

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