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Artificial Intelligence and Social Simulation

  • Recent advances in artificial intelligence and computer science can be used by social scientists in their study of groups and teams. Here, we explain how developments in machine learning and simulations with artificially intelligent agents can help group and team scholars to overcome two major problems they face when studying group dynamics. First, because empirical research on groups relies on manual coding, it is hard to study groups in large numbers (the scaling problem). Second, conventional statistical methods in behavioral science often fail to capture the nonlinear interaction dynamics occurring in small groups (the dynamics problem). Machine learning helps to address the scaling problem, as massive computing power can be harnessed to multiply manual codings of group interactions. Computer simulations with artificially intelligent agents help to address the dynamics problem by implementing social psychological theory in data-generating algorithms that allow for sophisticated statements and tests of theory. We describe anRecent advances in artificial intelligence and computer science can be used by social scientists in their study of groups and teams. Here, we explain how developments in machine learning and simulations with artificially intelligent agents can help group and team scholars to overcome two major problems they face when studying group dynamics. First, because empirical research on groups relies on manual coding, it is hard to study groups in large numbers (the scaling problem). Second, conventional statistical methods in behavioral science often fail to capture the nonlinear interaction dynamics occurring in small groups (the dynamics problem). Machine learning helps to address the scaling problem, as massive computing power can be harnessed to multiply manual codings of group interactions. Computer simulations with artificially intelligent agents help to address the dynamics problem by implementing social psychological theory in data-generating algorithms that allow for sophisticated statements and tests of theory. We describe an ongoing research project aimed at computational analysis of virtual software development teams.zeige mehrzeige weniger

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Metadaten
Verfasserangaben:Jesse HoeyORCiD, Tobias SchröderORCiDGND, Jonathan Howard MorganORCiD, Kimberly B. Rogers, Deepak Rishi, Meiyappan Nagappan
DOI:https://doi.org/10.1177/1046496418802362
ISSN:1552-8278
Titel des übergeordneten Werkes (Englisch):Small Group Research
Untertitel (Englisch):Studying Group Dynamics on a Massive Scale
Verlag:Sage Publications
Verlagsort:London
Dokumentart:Wissenschaftlicher Artikel
Sprache:Englisch
Datum der Veröffentlichung (online):10.03.2022
Jahr der Erstveröffentlichung:2018
Veröffentlichende Institution:Fachhochschule Potsdam
Datum der Freischaltung:10.03.2022
GND-Schlagwort:Künstliche Intelligenz; Gruppendynamik; Maschinelles Lernen; Virtuelles Team; Simulation
Jahrgang:49
Ausgabe / Heft:6
Erste Seite:647
Letzte Seite:683
Fachbereiche und Zentrale Einrichtungen:FB1 Sozial- und Bildungswissenschaften
Forschungs- und An-Institute / Inst. für angewandte Forschung Urbane Zukunft (IaF)
DDC-Klassifikation:000 Informatik, Informationswissenschaft, allgemeine Werke / 000 Informatik, Wissen, Systeme
Lizenz (Deutsch):License LogoCreative Commons - CC BY-NC-SA - Namensnennung - Nicht kommerziell - Weitergabe unter gleichen Bedingungen 4.0 International
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