Compression, The Fermi Paradox and Artificial Super-Intelligence
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Abstract (arXiv)
The following briefly discusses possible difficulties in communication with and control of an AGI (artificial general intelligence), building upon an explanation of The Fermi Paradox and preceding work on symbol emergence and artificial general intelligence. The latter suggests that to infer what someone means, an agent constructs a rationale for the observed behaviour of others. Communication then requires two agents labour under similar compulsions and have similar experiences (construct similar solutions to similar tasks). Any non-human intelligence may construct solutions such that any rationale for their behaviour (and thus the meaning of their signals) is outside the scope of what a human is inclined to notice or comprehend. Further, the more compressed a signal, the closer it will appear to random noise. Another intelligence may possess the ability to compress information to the extent that, to us, their signals would appear indistinguishable from noise (an explanation for The Fermi Paradox). To facilitate predictive accuracy an AGI would tend to more compressed representations of the world, making any rationale for their behaviour more difficult to comprehend for the same reason. Communication with and control of an AGI may subsequently necessitate not only human-like compulsions and experiences, but imposed cognitive impairment.
Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). Builds on 5 of its 19 references that are in the map. First posted on arXiv 5 Oct 2021.
Builds on
5 of 19 references.
References · 5
- 2018Symbol Emergence in Cognitive Developmental Systems: a Surveycited by 39
- 2015Symbol Emergence in Robotics: A Surveycited by 31
- 2021Symbol Emergence and The Solutions to Any Taskcited by 9
- 2017Verification of quantum computation: An overview of existing approachescited by 2
- 2018Building Safer AGI by introducing Artificial Stupiditycited by 1
Built on by
Citing papers per year: 2022: 1; 2023: 3; 2024: 1; 2025: 2.
7 papers.
- 2023The Optimal Choice of Hypothesis Is the Weakest, Not the Shortestcited by 12
- 2023Computational Dualism and Objective Superintelligencecited by 8
- 2022Computable Artificial General Intelligencecited by 6
- 2023On the Computation of Meaning, Language Models and Incomprehensible Horrorscited by 5
- 2025Agent Identity Evals: Measuring Agentic Identitycited by 5
- 2024Why Is Anything Conscious?cited by 1
- 2025What the F*ck Is Artificial General Intelligence?cited by 0
- 2025Agent Identity Evals: Measuring Agentic Identity23 Jul 2025
- 2025What the F*ck Is Artificial General Intelligence?31 Mar 2025
- 2024Why Is Anything Conscious?22 Sep 2024
- 2023On the Computation of Meaning, Language Models and Incomprehensible Horrors25 Apr 2023
- 2023Computational Dualism and Objective Superintelligence2 Feb 2023
- 2023The Optimal Choice of Hypothesis Is the Weakest, Not the Shortest30 Jan 2023
- 2022Computable Artificial General Intelligence21 May 2022