Abstract
Generative AI has revolutionized the creation of synthetic data, offering scalable and privacy-preserving solutions for data augmentation, testing, and analytics. However, the growing adoption of generative AI technologies raises critical ethical questions, including biases in generated data, misuse risks, accountability gaps, and potential erosion of trust. This systematic literature review employs Chitu Okoli’s method to synthesize the ethical implications of generative AI-induced synthetic data. By analyzing peer-reviewed articles, industry reports, and guidelines, this study categorizes the key ethical concerns, evaluates existing mitigation strategies, and identifies research gaps. The findings contribute to ethical AI discourse by highlighting challenges and proposing avenues for developing responsible generative AI applications. This work provides valuable insights for researchers, practitioners, and policymakers seeking to balance innovation with ethical integrity.
Recommended Citation
Adjei, Joseph Kwame; Owusu, Henry; and Yeboah, Clifford, "Generative AI-Induced Synthetic Data: Explicating the Ethical Implications" (2025). UK Academy for Information Systems Conference Proceedings 2025. 1.
https://aisel.aisnet.org/ukais2025/1