Ethical AI and Data Integrity: Ensuring Responsible AI Innovation Through Quantum - Resistant Algorithms and Federated Learning Paradigms
Abhijit Joshi · International Journal of Science and Research (IJSR) · 2023
Artificial Intelligence (AI) and machine learning are transforming industries by automating processes, enhancing decisionmaking, and uncovering insights from vast datasets.However, these advancements come with significant ethical challenges, including issues of bias, fairness, transparency, and accountability.This paper explores these ethical challenges and proposes a comprehensive framework for developing and deploying ethical AI systems.By examining case studies and best practices from industry leaders, we provide actionable guidelines for ensuring data integrity and responsible AI innovation.Through detailed methodologies, pseudocode, and visual aids, we aim to equip data engineers with the tools necessary to create AI systems that are both effective and ethically sound.