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Ethical Considerations in AI-Powered Data Governance

EasyChair Preprint no. 13215

18 pagesDate: May 7, 2024


As the field of artificial intelligence (AI) continues to advance, the importance of ethical considerations in AI-powered data governance becomes increasingly evident. AI technologies have the potential to revolutionize data governance practices by automating decision-making processes, improving data quality, and enabling efficient data management. However, the deployment of AI in data governance raises significant ethical challenges that need to be addressed to ensure responsible and fair use of data.


This abstract highlights key ethical considerations that arise in AI-powered data governance. It begins by discussing the fundamental principles of ethical AI, including transparency, accountability, fairness, and privacy. These principles serve as the foundation for establishing ethical guidelines for AI deployment in data governance.


The abstract then explores specific ethical challenges in AI-powered data governance. One crucial consideration is the potential for bias and discrimination in AI algorithms. Biased training data or biased algorithmic decision-making processes can perpetuate unfair outcomes and reinforce existing inequalities. Mitigating bias requires careful attention to data collection, preprocessing, and algorithm design.


Privacy is another critical ethical concern in AI-powered data governance. AI systems often process vast amounts of personal and sensitive data, raising questions about data protection, consent, and data anonymization. Striking the right balance between data utility and privacy protection is essential to maintain public trust and comply with legal and regulatory frameworks.

Keyphrases: Accountability, AI-Powered, Data Governance, Ethical Considerations, fairness, transparency

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Ayuns Luz and Harold Jonathan},
  title = {Ethical Considerations in AI-Powered Data Governance},
  howpublished = {EasyChair Preprint no. 13215},

  year = {EasyChair, 2024}}
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