ETHICAL REFLECTIONS ON DATA-CENTRIC AI: BALANCING BENEFITS AND RISKS
Keywords:
Data-Centric AI, Bias, Transparency, Accountability, Privacy, Regulatory Frameworks, Bias Mitigation, Algorithmic Fairness, StakeholdersAbstract
This paper delves into the ethical dimensions of data-centric artificial intelligence (AI), a domain where the quality, management, and use of data play a pivotal role in the development and functioning of AI systems. As AI continues to permeate various sectors including healthcare, finance, and transportation, it becomes increasingly important to balance the substantial benefits of these technologies against potential ethical risks and challenges. The main objectives of this study are to identify and analyze the ethical issues inherent in data-centric AI, propose strategies for balancing these issues with the benefits, and examine existing and potential frameworks for ethical governance. The methodology encompasses a comprehensive literature review, analysis of case studies, and synthesis of ethical frameworks and principles. Key findings reveal that data-centric AI poses unique ethical challenges, particularly concerning privacy, bias, fairness, transparency, and accountability. Real-world case studies illustrate how these challenges manifest and the consequences they entail. The paper highlights the significant advantages of data-centric AI, such as improved efficiency, accuracy, and new capabilities in various domains, while stressing that these benefits often come with ethical trade-offs. Strategies for balancing benefits and risks include the development of robust ethical frameworks, enhanced regulatory and governance mechanisms, and the active engagement of diverse stakeholders in ethical decision-making processes. The paper emphasizes the importance of principles like transparency, fairness, and accountability, proposing their integration into the lifecycle of AI systems. In conclusion, this study underscores the necessity of ongoing ethical reflections in the advancement of data-centric AI. It advocates for a proactive approach in addressing ethical challenges, ensuring that AI development is aligned with societal values and human rights. The paper concludes with a call to action for continued research and collaborative efforts in fostering ethical AI practices.
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