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Towards Artificial Intelligence Augmenting Facilitation : AI Affordances in Macro-Task Crowdsourcing

Titelangaben

Gimpel, Henner ; Graf, Vanessa ; Laubacher, Robert ; Meindl, Oliver:
Towards Artificial Intelligence Augmenting Facilitation : AI Affordances in Macro-Task Crowdsourcing.
In: Group Decision and Negotiation. Bd. 32 (2023) . - S. 75-124.
ISSN 1572-9907
DOI: https://doi.org/10.1007/s10726-022-09801-1

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Projekttitel:
Offizieller Projekttitel
Projekt-ID
Projektgruppe WI Digitalisierung
Ohne Angabe
Projektgruppe WI Künstliche Intelligenz
Ohne Angabe
Projektgruppe WI Digital Life
Ohne Angabe
Projektgruppe WI Digital Society
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Abstract

Crowdsourcing holds great potential: macro-task crowdsourcing can, for example, contribute to work addressing climate change. Macro-task crowdsourcing aims to use the wisdom of a crowd to tackle non-trivial tasks such as wicked problems. However, macro-task crowdsourcing is labor-intensive and complex to facilitate, which limits its efficiency, effectiveness, and use. Technological advancements in artificial intelligence (AI) might overcome these limits by supporting the facilitation of crowdsourcing. However, AI’s potential for macro-task crowdsourcing facilitation needs to be better understood for this to happen. Here, we turn to affordance theory to develop this understanding. Affordances help us describe action possibilities that characterize the relationship between the facilitator and AI, within macro-task crowdsourcing. We follow a two-stage, bottom-up approach: The initial development stage is based on a structured analysis of academic literature. The subsequent validation & refinement stage includes two observed macro-task crowdsourcing initiatives and six expert interviews. From our analysis, we derive seven AI affordances that support 17 facilitation activities in macro-task crowdsourcing. We also identify specific manifestations that illustrate the affordances. Our findings increase the scholarly understanding of macro-task crowdsourcing and advance the discourse on facilitation. Further, they help practitioners identify potential ways to integrate AI into crowdsourcing facilitation. These results could improve the efficiency of facilitation activities and the effectiveness of macro-task crowdsourcing.

Weitere Angaben

Publikationsform: Artikel in einer Zeitschrift
Begutachteter Beitrag: Ja
Keywords: Affordance; Artificial Intelligence; Facilitation; Macro-Task Crowdsourcing
Institutionen der Universität: Fakultäten > Rechts- und Wirtschaftswissenschaftliche Fakultät > Fachgruppe Betriebswirtschaftslehre
Forschungseinrichtungen
Forschungseinrichtungen > Institute in Verbindung mit der Universität
Forschungseinrichtungen > Institute in Verbindung mit der Universität > Institutsteil Wirtschaftsinformatik des Fraunhofer FIT
Forschungseinrichtungen > Institute in Verbindung mit der Universität > FIM Forschungsinstitut für Informationsmanagement
Fakultäten
Fakultäten > Rechts- und Wirtschaftswissenschaftliche Fakultät
Titel an der UBT entstanden: Nein
Themengebiete aus DDC: 000 Informatik,Informationswissenschaft, allgemeine Werke > 004 Informatik
300 Sozialwissenschaften > 330 Wirtschaft
Eingestellt am: 07 Feb 2023 09:51
Letzte Änderung: 16 Nov 2023 14:15
URI: https://eref.uni-bayreuth.de/id/eprint/73597