Hendriks, Patrick ; Sturm, Timo ; Olt, Christian M. ; Buxmann, Peter (2023)
The Impact of Human-Artificial Intelligence Partnerships on Organizational Learning.
European Conference on Information Systems (ECIS 2023). Kristiansand, Norway (June 11-16, 2023)
Konferenzveröffentlichung, Bibliographie
Kurzbeschreibung (Abstract)
To make sense of their increasingly digital and complex environments, organizations strive for a future in which machine learning (ML) systems join humans in collaborative learning partnerships to complement each other’s learning capabilities. While these so-called artificial assistants enable their human partners (and vice versa) to gain insights about unique knowledge domains that would otherwise remain hidden from them, they may also disrupt and impede each other's learning. To explore the virtuous and vicious dynamics that affect organizational learning, we conduct a series of agent-based simulations of different learning modes between humans and artificial assistants in an organization. We find that aligning the learning of humans and artificial assistants and allowing them to influence each other’s learning processes equally leads to the highest organizational performance.
| Typ des Eintrags: | Konferenzveröffentlichung |
|---|---|
| Erschienen: | 2023 |
| Autor(en): | Hendriks, Patrick ; Sturm, Timo ; Olt, Christian M. ; Buxmann, Peter |
| Art des Eintrags: | Bibliographie |
| Titel: | The Impact of Human-Artificial Intelligence Partnerships on Organizational Learning |
| Sprache: | Englisch |
| Publikationsjahr: | 16 Juni 2023 |
| Ort: | Atlanta |
| Verlag: | AIS eLibrary |
| Buchtitel: | ECIS 2023 Proceedings |
| Reihe: | ECIS 2023 Research Papers |
| Veranstaltungstitel: | European Conference on Information Systems (ECIS 2023) |
| Veranstaltungsort: | Kristiansand, Norway |
| Veranstaltungsdatum: | June 11-16, 2023 |
| URL / URN: | https://aisel.aisnet.org/ecis2023_rp/359/ |
| Kurzbeschreibung (Abstract): | To make sense of their increasingly digital and complex environments, organizations strive for a future in which machine learning (ML) systems join humans in collaborative learning partnerships to complement each other’s learning capabilities. While these so-called artificial assistants enable their human partners (and vice versa) to gain insights about unique knowledge domains that would otherwise remain hidden from them, they may also disrupt and impede each other's learning. To explore the virtuous and vicious dynamics that affect organizational learning, we conduct a series of agent-based simulations of different learning modes between humans and artificial assistants in an organization. We find that aligning the learning of humans and artificial assistants and allowing them to influence each other’s learning processes equally leads to the highest organizational performance. |
| Fachbereich(e)/-gebiet(e): | 01 Fachbereich Rechts- und Wirtschaftswissenschaften 01 Fachbereich Rechts- und Wirtschaftswissenschaften > Betriebswirtschaftliche Fachgebiete 01 Fachbereich Rechts- und Wirtschaftswissenschaften > Betriebswirtschaftliche Fachgebiete > Wirtschaftsinformatik 01 Fachbereich Rechts- und Wirtschaftswissenschaften > Betriebswirtschaftliche Fachgebiete > Fachgebiet Software Business & Information Management |
| Hinterlegungsdatum: | 26 Jun 2023 06:36 |
| Letzte Änderung: | 28 Jun 2023 12:56 |
| PPN: | 509045251 |
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