David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Ezio Di Nucci
Jack Alan Reynolds
Learn more about PhilPapers
Mind and Matter 4 (1):91-113 (2006)
The central paradigm of arti?cial intelligence is rapidly shifting toward biological models for both robotic devices and systems performing such critical tasks as network management, vehicle navigation, and process control. Here we use a recent mathematical analysis of the necessary conditions for consciousness in humans to explore likely failure modes inherent to a broad class of biologically inspired computing machines. Analogs to developmental psychopathology, in which regulatory mechanisms for consciousness fail progressively and subtly understress, and toinattentional blindness, where a narrow 'syntactic band pass' de?ned by the rate distortion manifold of conscious attention results in pathological ?xation, seem inevitable. Similar problems are likely to confront other possible architectures, although their mathematical description may be far less straightforward. Computing devices constructed on biological paradigms will inevitably lack the elaborate, but poorly understood, system of control mechanisms which has evolved over the last few hundred million years to stabilize consciousness in higher animals. This will make such machines prone to insidious degradation, and, ultimately, catastrophic failure
|Keywords||No keywords specified (fix it)|
|Categories||categorize this paper)|
Setup an account with your affiliations in order to access resources via your University's proxy server
Configure custom proxy (use this if your affiliation does not provide a proxy)
|Through your library|
References found in this work BETA
No references found.
Citations of this work BETA
Robert G. Wallace & Rodrick Wallace (2009). Evolutionary Radiation and the Spectrum of Consciousness. Consciousness and Cognition 18 (1):160-167.
Similar books and articles
Gordana Dodig-Crnkovic (2011). Significance of Models of Computation, From Turing Model to Natural Computation. Minds and Machines 21 (2):301-322.
Hava T. Siegelmann (2003). Neural and Super-Turing Computing. Minds and Machines 13 (1):103-114.
Pentti O. A. Haikonen (2007). Essential Issues of Conscious Machines. Journal of Consciousness Studies 14 (7):72-84.
B. Jack Copeland & Oron Shagrir (2007). Physical Computation: How General Are Gandy's Principles for Mechanisms? Minds and Machines 17 (2):217-231.
Rodrick Wallace, New Mathematical Foundations for AI and Alife: Are the Necessary Conditions for Animal Consciousness Sufficient for the Design of Intelligent Machines?
Stevan Harnad (2003). Can a Machine Be Conscious? How? Journal of Consciousness Studies 10 (4):67-75.
Peter Kugel (2002). Computing Machines Can't Be Intelligent (...And Turing Said So). Minds and Machines 12 (4):563-579.
Added to index2009-01-28
Total downloads16 ( #220,559 of 1,792,926 )
Recent downloads (6 months)1 ( #464,728 of 1,792,926 )
How can I increase my downloads?