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På AI-teknikens axlar [Elektronisk resurs]: om kunskapssociologin och stark artificiell intelligens
Lunds universitet. (Biblioteks- och Informationsvetenskap)
2009 (Swedish)Doctoral thesis, monograph (Other academic)Alternative title
On the Shoulders of AI-technology : Sociology of Knowledge and Strong Artificial Intelligence (English)
Abstract [en]

This dissertation is concerned with Sociology’s stance in the debate on Strong Artificial Intelligence, i.e. such AI that is able to shape new knowledge without human interference. There is a need for sociologists to realize the difference between two approaches to constructing AI systems: Symbolic AI (or Classic AI) and Distributed AI – DAI.Sociological literature shows a largely critical attitude towards Symbolic AI, an attitude that is justified. The main theme of this dissertation is that DAI is not only compatible with Sociology’s approach to what is social, but also constitutes an apt model of how a social system functions. This is consolidated with help from Niklas Luhmann’s social systems theory and from Vygotsky-oriented education scientists who claim that processes leading to new knowledge are about expansion and not about problem solving. Problem solving only leads to elaborating existing knowledge. It is shown that human being has always used several types of artefacts and tools to produce culture and knowledge. This shows that humans are dependent on their environment and that knowledge is not only something that has to do with their brain, but also the rest of their bodies and their environments.Further, Strong AI is not about robots thinking in the same way as humans, but about holistic social processes where the actor does not need to have a complex functionality. This provides a good opportunity to explain what sociologists call emergency, i.e. how social processes shape new knowledge independent of human actors.The possibility of AI has to be evaluated in terms of human beings’ capacities to cope with reflexive processes. Luhmann teaches us that we have to see the difference between three different forms of reflexivity: self-reference, reflexivity and reflection. We contend that, in order to be able to shape new knowledge in expanding processes, there must be circumstances that allow reflection. Luhmann writes that knowledge-producing processes are dependent on capacities for reflection between the social systems and their environments. Strong AI has more capacity to handle these processes than humans have, while the strongest argument for strong DAI is that it can reach a far wider area than human beings’ brains can. This capacity for reflection is a better way of judging the capacity of strong AI, than questions about causal capacity and capacity for action.

Place, publisher, year, edition, pages
Lund: Department of Sociology at Lund University , 2009. , 225 p.
Series
Lund Dissertations in Sociology, ISSN 1403-6061 ; 87
Keyword [en]
Gregory Bateson, James Wertsch., Yrjö Engeström, Katherine N. Hayles, Lucy Suchman, Hubert Dreyfus, John Searle, David Bloor, Lev Vygotsky, Niklas Luhmann, Chinese room, Turing test, socionics, darwinism, emergence, relativism, posthumanism, environmentalism, situationism, social communication, second order cybernetics, systems theory, sociology of knowledge, connectionism, Strong artificial intelligence, distributed artificial intelligence
National Category
Sociology (excluding Social Work, Social Psychology and Social Anthropology)
Research subject
Social Sciences, Sociology; Humanities, Library and Information Science; Social Sciences, Practical Philosophy
Identifiers
URN: urn:nbn:se:lnu:diva-17548ISBN: 91-7267-289-7 (print)OAI: oai:DiVA.org:lnu-17548DiVA: diva2:502043
Public defence
2009-05-29, Kulturen, Lund, 13:15 (Swedish)
Opponent
Supervisors
Available from: 2012-02-16 Created: 2012-02-14 Last updated: 2012-02-16Bibliographically approved

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