AIML Product Management for Ethical AI Defining Metrics for Fairness, Transparency, and Accountability in AI Models
DOI:
https://doi.org/10.63282/3050-922X.ICRCEDA25-118Keywords:
Ethical AI, Fairness Metrics, Transparency, Accountability, AI Product Management, Bias Mitigation, Explainable AI, AI Governance, Stakeholder Engagement, Sustainable AI DevelopmentAbstract
As artificial intelligence (AI) systems become integral to various sectors, ensuring their ethical deployment is paramount. This paper explores the role of AI/ML product management in defining and implementing metrics for fairness, transparency, and accountability in AI models. We analyze existing frameworks, propose methodologies for metric selection, and discuss the challenges and best practices in integrating these metrics throughout the AI development lifecycle. By emphasizing ethical considerations, we aim to guide product managers and developers toward creating AI systems that uphold societal values and foster trust
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