Document Type
Article
Source of Publication
Informatics
Publication Date
8-9-2024
Abstract
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, including education, media, and healthcare, underscoring the need for AI systems that promote equity and do not perpetuate social inequalities. It advocates for a proactive approach to the ethical development of AI, emphasizing the necessity of establishing policies, guidelines, and frameworks that prioritize human rights, fairness, and transparency. The paper calls for a multidisciplinary dialogue among policymakers, technologists, and researchers to ensure responsible AI development that conforms to societal values and ethical standards. It stresses the urgency of addressing these ethical concerns and advocates for the development of generative AI in a socially beneficial and ethically sound manner, contributing significantly to the discourse on managing AI’s ethical implications in the modern digital era. The study highlights the theoretical and practical implications of these challenges and suggests a number of future research directions.
DOI Link
ISSN
Publisher
MDPI AG
Volume
11
Issue
3
First Page
58
Last Page
58
Disciplines
Computer Sciences
Keywords
Generative AI, Ethical challenges, Deepfakes, Societal inequalities, Privacy
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Recommended Citation
Al-kfairy, Mousa; Mostafa, Dheya; Kshetri, Nir; Insiew, Mazen; and Alfandi, Omar, "Ethical Challenges and Solutions of Generative AI: An Interdisciplinary Perspective" (2024). All Works. 6842.
https://zuscholars.zu.ac.ae/works/6842
Indexed in Scopus
no
Open Access
yes
Open Access Type
Gold: This publication is openly available in an open access journal/series