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Policy·P Space·Evidence-backed problem·Published 2026-07-20

Ethical Challenges and Solutions of Generative AI: An Interdisciplinary Perspective

This paper conducts a systematic review and interdisciplinary analysis of the ethical challenges of generative AI technologies (N = 37), highlighting significant concerns such as privacy, data protection, copyright infringement, misinformation, biases, and societal inequalities. The ability of generative AI to produce convincing deepfakes and synthetic media, which threaten the foundations of truth, trust, and democratic values, exacerbates these problems. The paper combines perspectives from various disciplines…

TRV-2026-0369Peer-reviewedPermanent record — cite & verify
Ethical Challenges and Solutions of Generative AI: An Interdisciplinary Perspective

Ethics of AI in Digital Medicine – Explanation why transparent explainable AI is important by KI-Campus. CC BY-SA 4.0 · https://creativecommons.org/licenses/by-sa/4.0

The quick read

On 2024-08-09, a peer-reviewed paper in Informatics reported a systematic review of 37 sources on generative AI ethics, identifying concerns spanning privacy, data protection, copyright infringement, misinformation, biases, and societal inequalities, with particular attention to convincing deepfakes and synthetic media.

The findings matter because they link technical capabilities to erosion of truth, trust, and democratic values and to inequitable impacts across education, media, and healthcare, while uncertainty remains about which policies, guidelines, and frameworks will effectively operationalize fairness and transparency in practice.

Main points
  • Systematic review of N=37 sources analyzed ethical challenges across disciplines including education, media, and healthcare.
  • Authors advocate for policies, guidelines, and frameworks that prioritize human rights, fairness, and transparency.
  • Paper calls for multidisciplinary dialogue among policymakers, technologists, and researchers for responsible development.
Problem

Generative AI systems create risks of privacy loss, copyright infringement, misinformation, bias, and deepfake synthetic media that threaten truth, trust, and democratic values.

The rundown

The paper is framed as a systematic review and interdisciplinary analysis covering 37 sources, drawing on education, media, and healthcare perspectives to map how generative systems intersect with equity and social inequality.

It concludes by urging proactive ethical development through human-rights-centered policies and sustained dialogue among policymakers, technologists, and researchers, noting theoretical and practical implications and future research directions.

Sources

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The debate