Ethical Frameworks for Mitigating Algorithmic Bias in Artificial Intelligence Systems Deployed at Scale
Keywords:
Algorithmic bias, Artificial intelligence, Ethics, Fairness-aware Design, AccountabilityAbstract
The deployment of artificial intelligence (AI) systems at scale has brought significant advancements but also raised critical ethical concerns, particularly around algorithmic bias. These biases can result in systemic inequalities, discrimination, and erosion of trust in AI technologies. This paper explores ethical frameworks aimed at mitigating algorithmic bias, focusing on principles of fairness, accountability, transparency, and inclusivity. It emphasizes the need for cross-disciplinary collaboration, regulatory interventions, and continual evaluation to ensure ethical deployment at scale. The discussion provides actionable insights for researchers, practitioners, and policymakers striving to align AI technologies with societal values.
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