Compression, The Fermi Paradox and Artificial Super-Intelligence
Michael Timothy Bennett

TL;DR
This paper explores how advanced AI might use highly compressed signals that appear as noise, complicating communication and control, and offers insights into the Fermi Paradox and AGI behavior.
Contribution
It proposes that AGI may employ extreme data compression, making their signals indistinguishable from noise and challenging human understanding and control.
Findings
Highly compressed signals can appear as noise to humans
AGI's rationales may be outside human comprehension
Control may require imposing cognitive impairments
Abstract
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…
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