A scientifically sound, objective test for consciousness

From: Colin Hales <c.hales.domain.name.hidden>
Date: Wed, 28 Jan 2009 13:32:52 +1100

(The journal is free!)

The test itself is not easy or cheap - but it is possible AND you can
perform it on humans as well as AI. To deny that the test is valid
involves a denial that scientists have P-consciousness, whilst being
totally demanding of it and dependent on it for all science outcomes.

Hales, C. (2009), 'An empirical framework for objective testing for
P-consciousness in an artificial agent', The Open Artificial
Intelligence Journal, 3, pp. 1-15.

http://www.bentham.org/open/toaij/

*Abstract:* Two related and relatively obscure issues in science have
eluded empirical tractability. Both can be directly traced to progress
in artificial intelligence. The first is scientific proof of
consciousness or otherwise in anything. The second is the role of
consciousness in intelligent behaviour. This document approaches both
issues by exploring the idea of using scientific behaviour
self-referentially as a benchmark in an objective test for
P-consciousness, which is the relevant
critical aspect of consciousness. Scientific behaviour is unique in
being both highly formalised and provably critically dependent on the
P-consciousness of the primary senses. In the context of the primary
senses P-consciousness is literally a formal identity with scientific
observation. As such it is intrinsically afforded a status of critical
dependency demonstrably no different to any other critical dependency in
science, making scientific behaviour ideally suited to a
self-referential scientific circumstance. The 'provability' derives from
the delivery by science of objectively verifiable 'laws of nature'. By
exploiting the critical dependency, an empirical framework is
constructed as a refined and specialised version of existing
propositions for a 'test for consciousness'. The specific role of
P-consciousness is clarified: it is a human intracranial central nervous
system construct that symbolically grounds the scientist in the distal
external world, resulting in our ability to recognise, characterise and
adapt to distal natural world novelty. It is hoped that in opening a
discussion of a novel approach, the artificial intelligence community
may eventually find a viable contender for its long overdue scientific
basis.

cheers
colin hales




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Received on Tue Jan 27 2009 - 21:31:14 PST

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