Ethical AI Development: Balancing Innovation and Responsibility in Machine Learning
Abstract
The rapid advancement of artificial intelligence has brought transformative benefits across industries but also raised critical ethical concerns. This paper examines the ethical dimensions of AI development, focusing on fairness, accountability, transparency, and bias mitigation. Through a comparative analysis of existing ethical frameworks and real-world case studies, the study identifies best practices for responsible AI deployment. It proposes a novel methodology combining algorithmic auditing and stakeholder engagement to ensure equitable outcomes. The findings emphasize the importance of interdisciplinary collaboration and regulatory oversight in fostering trust and sustainability in AI innovation.
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