Ethical AI and Responsible Data Science in Critical Applications

Abstract

The increasing deployment of AI across industries such as healthcare, finance, and defense requires a sound ethical framework that tackles issues surrounding fairness, transparency, accountability, and bias within algorithms. The industries all pose specific challenges regarding the application of ethical AI strategies. This research will contrast the application of ethical AI practices between these industries regarding their compliance level with ethical aspects and outline an industry-specific framework towards enhancing the ethical deployment of AI. The study employs a comparative analysis method to evaluate ethical areas like fairness, transparency, accountability, and bias control against healthcare, finance, and defense using sector-specific standards. The results indicate that healthcare performs better in people-oriented ethics, like ethical awareness, stakeholder engagement, and human control, while finance reflects robust compliance with regulation. Conversely, defense has critical shortcomings, especially regarding transparency and algorithmic bias control. The research underlines the need for domain-specific ethical standards, and the framework presented provides valuable contributions towards better AI governance, especially in the context of healthcare, and towards shaping future policy making.

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