Ethical Challenges Presented by Advanced Artificial Intelligence in Diagnostics and Treatment Recommendations
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Abstract
The implementation of advanced artificial intelligence (AI) into the field of medical diagnostics and treatment recommendations brings forth a myriad of ethical challenges that necessitate prompt attention. This research explores six key areas of concern that encompass both technological and human factors. Firstly, the paper examines the need for Accuracy, Reliability, and Continuous Updates, emphasizing the significance of constant reflection of evolving medical knowledge and the prevention of severe consequences due to errors. Secondly, it delves into Data Concerns, such as biases in AI models, privacy, and the necessity for robust security measures. The third segment explores Transparency, Explainability, and Trust, shedding light on the vital role of understanding and faith in AI's decision-making process. Liability, Oversight, and Consent are analyzed as a fourth area, focusing on questions of responsibility, the debate surrounding human oversight, and patient awareness. The fifth section concentrates on Human Aspects, examining the potential negative effects of over-reliance on AI, such as depersonalization of care and economic impacts on the medical profession. Lastly, the paper considers Accessibility, Equity, and Global Reach, addressing the imperative for AI diagnostic tools to be available equitably, without limitation to wealthy institutions. Collectively, the findings of this research emphasize the need for a proactive and comprehensive ethical framework that prioritizes patient well-being and preserves trust in the medical field as AI continues its advancement in healthcare.
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Last updated: 05-02-2023