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Monte Carlo model of brain emulation development

Abstract:

Whole brain emulation (WBE) is the possible future technology of one-to-one modelling of the function of the entire (human) brain. It would entail automatically scanning a brain, decoding the relevant neural circuitry, and generate a computer-runnable simulation that has a one-to-one relationship with the functions in the real brain (as well as an adequate virtual or real embodiment)2.

Obviously this is a hugely ambitious project far outside current capabilities, possibly not even feasible in theory3. However, should such a technology ever become feasible there are good reasons to expect the consequences to be dramatic4 : it would enable software intelligence, copyable human capital, new ethical problems, and (depending on philosophical outlook) immortality and a posthuman species. Even if one does not ascribe a high probability to WBE being ever feasible it makes sense to watch for trends indicating that it may be emerging, since adapting to its emergence may require significant early and global effort taking decades5.

Predicting when a future technology emerges is hard, and there are good reasons to be cautious about overconfident pronouncements. In particular, predictions about the future of artificial intelligence have not been very successful and there are good theoretical reasons to have expected this6. However, getting a rough estimate of what is needed for a technology to be feasible compared to current trends can give a helpful “order of magnitude estimate” of how imminent a technology is, and how quickly it could move from a primitive state to a mature state.

This paper will describe a simple Monte Carlo simulation of the emergence of WBE as a first tool for thinking about it.

Publication status:
Published
Peer review status:
Reviewed (other)

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Institution:
University of Oxford
Division:
HUMS
Department:
Philosophy Faculty
Role:
Author


Publisher:
Future of Humanity Institute
Place of publication:
Oxford
Publication date:
2014-01-01


Language:
English
Keywords:
Pubs id:
1774408
Local pid:
pubs:1774408
Deposit date:
2024-03-07

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