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GenAI's Ethical Imperative: Building Robust Data Governance Frameworks

  • Generative AI (GenAI) brings transformative power but raises challenges in data governance and ethics.
  • Concerns include biases amplification, intellectual property issues, deepfakes, and data traceability.
  • Establishing robust data governance is crucial for ethical GenAI deployment and preventing misinformation.
  • Key aspects involve pre-training data curation, ethical review boards, human oversight, and adaptive policies.
  • Privacy-preserving techniques like differential privacy and federated learning are recommended.
  • Technical measures such as bias detection and output lineage tracking play a role in governance.
  • Global regulatory frameworks, such as the EU AI Act and the US AI Disclosure Act, impact AI governance.
  • China's regulations focus on content management and data protection for Generative AI services.
  • International organizations must adapt governance frameworks to comply with evolving AI regulations worldwide.
  • Building trust and ensuring fairness in GenAI deployment require continuous vigilance and commitment to responsible innovation.

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