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Indicators and Criteria of Consciousness in Animals and Intelligent Machines: An Inside-Out Approach
Department of Cognitive and Systems Neuroscience, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, Netherlands ; Research Priority Area, Brain and Cognition, University of Amsterdam, Amsterdam, Netherlands.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Public Health and Caring Sciences, Centre for Research Ethics and Bioethics. Biogem, Biology and Molecular Genetics Institute, Ariano Irpino, Italy. (Neuroethics)ORCID iD: 0000-0002-3298-7829
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Public Health and Caring Sciences, Centre for Research Ethics and Bioethics. (Neuroethics)
2019 (English)In: Frontiers in Systems Neuroscience, ISSN 1662-5137, E-ISSN 1662-5137, Vol. 13, article id 25Article, review/survey (Refereed) Published
Abstract [en]

In today’s society, it becomes increasingly important to assess which non-human and non-verbal beings possess consciousness. This review article aims to delineate criteria for consciousness especially in animals, while also taking into account intelligent artifacts. First, we circumscribe what we mean with “consciousness” and describe key features of subjective experience: qualitative richness, situatedness, intentionality and interpretation, integration and the combination of dynamic and stabilizing properties. We argue that consciousness has a biological function, which is to present the subject with a multimodal, situational survey of the surrounding world and body, subserving complex decision-making and goal-directed behavior. This survey reflects the brain’s capacity for internal modeling of external events underlying changes in sensory state. Next, we follow an inside-out approach: how can the features of conscious experience, correlating to mechanisms inside the brain, be logically coupled to externally observable (“outside”) properties? Instead of proposing criteria that would each define a “hard” threshold for consciousness, we outline six indicators: (i) goal-directed behavior and model-based learning; (ii) anatomic and physiological substrates for generating integrative multimodal representations; (iii) psychometrics and meta-cognition; (iv) episodic memory; (v) susceptibility to illusions and multistable perception; and (vi) specific visuospatial behaviors. Rather than emphasizing a particular indicator as being decisive, we propose that the consistency amongst these indicators can serve to assess consciousness in particular species. The integration of scores on the various indicators yields an overall, graded criterion for consciousness, somewhat comparable to the Glasgow Coma Scale for unresponsive patients. When considering theoretically derived measures of consciousness, it is argued that their validity should not be assessed on the basis of a single quantifiable measure, but requires cross-examination across multiple pieces of evidence, including the indicators proposed here. Current intelligent machines, including deep learning neural networks (DLNNs) and agile robots, are not indicated to be conscious yet. Instead of assessing machine consciousness by a brief Turing-type of test, evidence for it may gradually accumulate when we study machines ethologically and across time, considering multiple behaviors that require flexibility, improvisation, spontaneous problem-solving and the situational conspectus typically associated with conscious experience.

Place, publisher, year, edition, pages
2019. Vol. 13, article id 25
Keywords [en]
awareness, bird, episodic memory, goal-directed behavior, illusion, robot, rodent, visuospatial behavior
National Category
Neurosciences Ethics Robotics
Identifiers
URN: urn:nbn:se:uu:diva-389486DOI: 10.3389/fnsys.2019.00025ISI: 000477743000001PubMedID: 31379521OAI: oai:DiVA.org:uu-389486DiVA, id: diva2:1337550
Projects
Human Brain Project SGA2
Funder
EU, Horizon 2020, 785907Available from: 2019-07-16 Created: 2019-07-16 Last updated: 2019-09-20Bibliographically approved

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Farisco, MicheleEvers, Kathinka

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