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Since its public release in November 2022, OpenAI's Generative AI (GenAI) has been met with varied responses, from widespread individual adoption to institutional caution. This phenomenon is evident among Egyptian public policy makers, where some institutions quickly embraced GenAI, while others hav...
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| Format: | Thesis |
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AUC Knowledge Fountain
2026
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| Summary: | Since its public release in November 2022, OpenAI's Generative AI (GenAI) has been met with varied responses, from widespread individual adoption to institutional caution. This phenomenon is evident among Egyptian public policy makers, where some institutions quickly embraced GenAI, while others have been slow to integrate it. The adoption of GenAI among these professionals is influenced by multiple factors, with institutional factors and budget constraints being the most significant. The varied adoption creates a need for new skills and the enhancement of existing ones. This uneven adoption is hypothesized to cause two main issues in Egyptian public policy: a policy communication gap and information asymmetry. To test this, the researcher used the Delphi method, an iterative process that allowed for the validation of data through repeated engagement with participants. The findings confirmed that a potential policy communication gap could arise from the varied adoption of GenAI, driven by underlying information asymmetry. Additionally, the research revealed a "public administration brain drain" is already occurring and may intensify as professionals independently reskill for GenAI. The findings ultimately suggest that Egyptian public policy making is vulnerable to fragmentation, potentially led by the interests of GenAI-integrated organizations rather than serving the public good. |
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