Governance of Generative Artificial Intelligence for Companies
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arXiv
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| Hauptverfasser: | , , , |
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| Format: | Preprint |
| Veröffentlicht: |
2024
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| _version_ | 1866915808234438656 |
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| author | Schneider, Johannes Kuss, Pauline Abraham, Rene Meske, Christian |
| author_facet | Schneider, Johannes Kuss, Pauline Abraham, Rene Meske, Christian |
| contents | Generative Artificial Intelligence (GenAI), specifically large language models (LLMs) like ChatGPT, has swiftly entered organizations without adequate governance, posing both opportunities and risks. Despite extensive debate on GenAI's transformative potential and emerging regulatory measures, limited research addresses organizational governance from both technical and business perspectives. While frameworks for AI governance exist, it remains unclear to what extent they apply to GenAI. This review paper fills this gap by surveying recent literature to better understand the fundamental characteristics of GenAI and to adapt existing governance frameworks specifically to GenAI within organizations. To this end, it extends Nickerson's framework development process by incorporating prior conceptualizations. The resulting framework delineates scope, objectives, and governance mechanisms designed to both harness business opportunities and mitigate risks associated with GenAI integration. Overall, this research advances a focused approach to GenAI governance, offering practical guidance for companies navigating the challenges of GenAI adoption and highlighting research gaps. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2403_08802 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Governance of Generative Artificial Intelligence for Companies Schneider, Johannes Kuss, Pauline Abraham, Rene Meske, Christian Artificial Intelligence Computers and Society Machine Learning I.2.m Generative Artificial Intelligence (GenAI), specifically large language models (LLMs) like ChatGPT, has swiftly entered organizations without adequate governance, posing both opportunities and risks. Despite extensive debate on GenAI's transformative potential and emerging regulatory measures, limited research addresses organizational governance from both technical and business perspectives. While frameworks for AI governance exist, it remains unclear to what extent they apply to GenAI. This review paper fills this gap by surveying recent literature to better understand the fundamental characteristics of GenAI and to adapt existing governance frameworks specifically to GenAI within organizations. To this end, it extends Nickerson's framework development process by incorporating prior conceptualizations. The resulting framework delineates scope, objectives, and governance mechanisms designed to both harness business opportunities and mitigate risks associated with GenAI integration. Overall, this research advances a focused approach to GenAI governance, offering practical guidance for companies navigating the challenges of GenAI adoption and highlighting research gaps. |
| title | Governance of Generative Artificial Intelligence for Companies |
| topic | Artificial Intelligence Computers and Society Machine Learning I.2.m |
| url | https://arxiv.org/abs/2403.08802 |