Paper Type
Complete
Abstract
Generative Artificial Intelligence (GenAI) technologies, such as ChatGPT, are reshaping domains by enhancing innovation and efficiency, but they also raise critical ethical dilemmas. This study develops a conceptual framework that translates core ethical principles – fairness, accountability, transparency, and inclusion – into actionable mitigation strategies. The framework includes systematic bias auditing, transparency guidelines, accountability structures, and inclusive practices to guide responsible GenAI development and deployment. Emphasizing the importance of interdisciplinary approaches and proactive ethical governance, the study contributes to the evolving discourse on AI ethics by offering structured pathways for organizations, policymakers, and developers to align GenAI technologies with societal values. Future empirical validation is recommended to refine and adapt the framework to real-world applications, ensuring that the benefits of GenAI are equitably distributed and ethically grounded.
Paper Number
1547
Recommended Citation
Carrasco, Lais Barbudo, "Towards Responsible AI: A Conceptual Framework for Mitigating Ethical Risks in Generative Artificial Intelligence Systems" (2025). AMCIS 2025 Proceedings. 8.
https://aisel.aisnet.org/amcis2025/ict_global/ict_global/8
Towards Responsible AI: A Conceptual Framework for Mitigating Ethical Risks in Generative Artificial Intelligence Systems
Generative Artificial Intelligence (GenAI) technologies, such as ChatGPT, are reshaping domains by enhancing innovation and efficiency, but they also raise critical ethical dilemmas. This study develops a conceptual framework that translates core ethical principles – fairness, accountability, transparency, and inclusion – into actionable mitigation strategies. The framework includes systematic bias auditing, transparency guidelines, accountability structures, and inclusive practices to guide responsible GenAI development and deployment. Emphasizing the importance of interdisciplinary approaches and proactive ethical governance, the study contributes to the evolving discourse on AI ethics by offering structured pathways for organizations, policymakers, and developers to align GenAI technologies with societal values. Future empirical validation is recommended to refine and adapt the framework to real-world applications, ensuring that the benefits of GenAI are equitably distributed and ethically grounded.
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