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September 10, 2025

Mitigating Bias in AI: A Review of Sources, Impacts, and Strategies

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Authors

MMMiftah Maulana

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Overview

Systematic literature review analyzed bias mitigation in artificial intelligence, suggesting comprehensive strategies for effective fairness.

Key Points

  • Bias mitigation strategies have shifted from technical to comprehensive lifecycle approaches in AI systems.
  • Key innovations include fairness-aware algorithms and explainable AI, highlighting sector-specific applications.
  • A systematic literature review approach yielded insights from diverse databases for novel findings in bias mitigation.
  • Cross-disciplinary collaboration and public engagement are essential for the acceptance of ethical AI systems.

Cite This Study

Miftah Maulana (2025) studied this question.

synapsesocial.com/papers/68c199e29b7b07f3a061b3dbhttps://doi.org/10.70764/gdpu-bit.2025.1(1)-02
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