Ethical Dilemmas in AI-Powered Decision-Making: A Deep Dive into Big Data-Driven Ethical Considerations

Abstract

The integration of artificial intelligence (AI) and big data analytics in decision-making processes has ushered in a new era of technological advancements and transformative capabilities across various sectors. However, this burgeoning synergy has also engendered a concomitant rise in ethical dilemmas and considerations. This research article investigates the multifaceted landscape of ethical dilemmas in AI-powered decision-making, with a particular emphasis on the ethical considerations associated with big data-driven decision processes. Drawing from a comprehensive review of the existing literature, this article illuminates the various ethical frameworks applicable to AI and big data ethics. It dissects specific ethical dilemmas that emerge in the context of AI decision-making, including algorithmic bias, transparency, and accountability, while also exploring the intricate ethical considerations entailed in the collection and utilization of big data, such as data privacy, security, and informed consent. The research utilizes a mixed-method approach, combining qualitative and quantitative data analysis, to empirically investigate the extent and implications of these ethical dilemmas. The findings underscore the pressing need to develop and implement ethical frameworks to guide AI and big data decision-making, as well as to offer practical recommendations for mitigating these ethical challenges.