Ethical and Sustainable AI: Frameworks for Fairness, Transparency, and Human-Centric Applications
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The rapid integration of Artificial Intelligence (AI) into critical sectors of society has brought forth significant ethical challenges, demanding robust frameworks to ensure fairness, transparency, and accountability. This chapter provides a comprehensive exploration of Ethical and Sustainable AI, presenting a structured approach to developing and deploying AI systems that are not only technologically advanced but also aligned with human-centric values. We introduce a novel framework that integrates bias detection, fairness metrics, and explainable AI (XAI) techniques throughout the AI lifecycle. Through a detailed case study using a synthetic dataset modeled on real-world socio-economic data, we demonstrate the practical application of this framework. The chapter presents simulation results that quantify the trade-offs between model accuracy and fairness, offering insights into the effectiveness of various bias mitigation strategies. Furthermore, we address the growing concern of AI’s environmental impact by incorporating sustainability metrics into our evaluation. The findings underscore the necessity of a multi-faceted approach to ethical AI, one that balances performance with principles of equity, transparency, and environmental responsibility, providing a blueprint for the next generation of intelligent applications.
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