Title: Mitigating Gender Bias in AI-as-a-Service (AIaaS)

This proposal introduces a groundbreaking Gender Bias Mitigation Framework (GBMF) designed to seamlessly integrate into AI-as-a-Service (AIaaS) platforms. The GBMF addresses the pressing issue of gender bias within AI systems by utilizing state-of-the-art machine learning techniques and ethical considerations. The project aligns with the National Science Foundation's (NSF) mandate for supporting innovative, high-impact solutions and involves a diverse team of experts in machine learning, ethics, and fairness-aware AI. Through a series of technical objectives, including data preprocessing, bias identification, algorithmic adjustments, fairness constraints, integration, validation, and ethical compliance, the project aims to demonstrate the feasibility of the GBMF and significantly reduce technical risks. The GBMF's market opportunity lies in addressing gender bias in AI-driven decisions across healthcare, finance, e-commerce, and education, addressing a common pain point. The Layla Martin Center for Sustainability Innovation leads the project, equipped with the expertise and network to drive innovation in AI fairness. Ultimately, this Phase I project seeks to pave the way for equitable AI adoption and align with the growing demand for ethical AI development.