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.…
Verfasserangaben: | Jesse HoeyORCiD, Tobias SchröderORCiDGND, Jonathan Howard MorganORCiD, Kimberly B. Rogers, Deepak Rishi, Meiyappan Nagappan |
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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): | Creative Commons - CC BY-NC-SA - Namensnennung - Nicht kommerziell - Weitergabe unter gleichen Bedingungen 4.0 International |