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Intelligent machines might want to become biological again

C C Offline

EXCERPT: [...] Superficially, the logic behind the conjectures about cosmic machine intelligence appears pretty solid. Extrapolating the trajectory of our own current technological evolution suggests that with enough computational sophistication on hand, the capacity and capability of our biological minds and bodies could become less and less attractive. At a certain point we’d want to hop into new receptacles, custom-built to suit whatever takes our fancy. Similarly, that technological arc could take us to a place where we’ll create artificial intelligences that are either indifferent to us, or that will overtake and subsume (or simply squish) us.

Biology is not up to the task of sustaining pan-stellar civilisations or the far-future human civilisation, the argument goes. The environmental and temporal challenges of space exploration are huge. Any realistic impetus to become an interstellar species might demand robust machines, not delicate protein complexes with fairly pathetic use-by dates. A machine might live forever and copy itself perfectly, unencumbered by the error-prone flexibility of natural evolution. Self-designing life forms could also tailor themselves to very specific environments. In a single generation they could adapt to the great gulfs of time and space between the stars, or to the environments of alien worlds.

Pull all of these pieces together and it can certainly seem that the human blueprint is a blip, a quickly passing phase. [...] Where that’s taking us to isn’t obvious, however. If anything, we could be heading for a hive-mind state, a collective organism more akin to a termite colony or a set of squirmy naked mole-rats. Rather than increasing our intelligence, we might actually be throttling the raw inputs, training ourselves to be increasingly passive. A pessimist might see our minds stalling out, becoming part of a self-referencing swarm rather than a set of exponentially improving geniuses. History also teaches us that it is nigh-impossible to foresee the long-term impacts of disruptive technologies. [...]

[...] Because these machines are hemmed in by efficiency limits, there is a possibility that they’d end up looking at their past for new tricks to move forwards. One thing that they would know (as we already do) is that biology works, and it works extremely well. Some researchers estimate that the modern human brain is at its computational limits, but it might require only a slightly cleverer machine to re-engineer such a complex organ. In other words, there could be a more optimal trajectory that leads away from machines and back to biology, with its remarkable energy efficiency....


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