{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,9]],"date-time":"2026-01-09T15:08:05Z","timestamp":1767971285923,"version":"3.49.0"},"reference-count":53,"publisher":"World Scientific Pub Co Pte Ltd","issue":"01","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J. AI. Consci."],"published-print":{"date-parts":[[2023,3]]},"abstract":"<jats:p>Consciousness in higher animals, by virtue of its 100 ms time constant, is a necessarily greatly simplified and stripped-down version of more complex multiple tunable workspace cognition\/ regulation dyads like wound healing, immune function, gene expression, institutional function and the like. These more complex dynamic entities emerged through evolutionary exaptation of the inevitable information crosstalk between coresident cognitive modules. In consequence of the debrided nature of consciousness, it should not be difficult to construct a fast, single workspace \u201cconscious machine\u201d that mimics the human tunable neuronal global workspace system. Tied to a \u201cbackbrain\u201d AI that has learned hyperrapid stereotypic pattern responses to some particular set of likely challenges, the result is an elementary \u201cemotional\u201d conscious machine. A clever designer, however, may want to use available high-speed electronics to mimic the more capable multiple-workspace\/ workforce systems inherently less susceptible to inattentional blindness and related failings of overfocus and thrashing. Contrary to current social constructions, however, the ultimate utility of such machines remains obscure. Here, we explore these matters in formal detail, restricting argument to the asymptotic limit theorems of information and control theories.<\/jats:p>","DOI":"10.1142\/s2705078522500187","type":"journal-article","created":{"date-parts":[[2023,3,10]],"date-time":"2023-03-10T07:55:07Z","timestamp":1678434907000},"page":"125-148","source":"Crossref","is-referenced-by-count":8,"title":["On \u201cMachine Consciousness\u201d"],"prefix":"10.1142","volume":"10","author":[{"given":"Rodrick","family":"Wallace","sequence":"first","affiliation":[{"name":"Division of Epidemiology, The New York State Psychiatric Institute, Box 47, 1051 Riverside Drive, New York, NY 10032, USA"}]}],"member":"219","published-online":{"date-parts":[[2023,3,10]]},"reference":[{"key":"S2705078522500187BIB001","doi-asserted-by":"crossref","first-page":"471","DOI":"10.1023\/A:1026244616112","volume":"13","author":"Adams F.","year":"2003","journal-title":"Minds Mach."},{"key":"S2705078522500187BIB002","doi-asserted-by":"crossref","first-page":"711","DOI":"10.1093\/intimm\/10.6.711","volume":"10","author":"Atlan H.","year":"1998","journal-title":"Int. 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