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Investigating the Ethical Implications of Artificial Intelligence (AI) in Medicine

Domaine:

healthcare

Type de record:

paper
Créateur:
MarOluOluOlu
Éditeur:
Dep
Hôte:
This study investigates the multifaceted ethical implications of Artificial Intelligence (AI) in medicine. Since its introduction in the 1950s, AI has revolutionized healthcare, offering unprecedented opportunities for improved diagnosis, personalized treatment and enhanced patient outcomes due to increasing processing power and vast digital data. While this technological advancement holds immense potential to improve patient care, it also raises significant concerns about issues such as data privacy, informed consent and the potential for biases and errors in AI systems. This research aims to investigate these ethical implications, focusing on the intersection of technological innovation and human values and to provide recommendations for the responsible and safe use of AI in healthcare. The study employs a mixed-methods approach, combining a comprehensive qualitative narrative review of existing literature with a quantitative descriptive survey of 32 healthcare professionals and patients at Sane Plus Diagnostics, Ibadan, Nigeria. The findings from this study reveal a complex and nuanced perspective, affirming that while participants see AI as a valuable tool, their trust is conditional and does not extend to full autonomy. The research identified and analyzed ethical challenges such as overreliance on AI for diagnosis, inadequate data privacy protection and the potential for bias. It also highlights a notable disconnect between individual ethical awareness and the effectiveness of institutional reporting mechanisms. The examination of these ethical implications provides a deeper understanding of the complex interplay between technology and human values. The successful and responsible integration of AI in medicine requires a balanced approach that prioritizes robust governance frameworks, fosters human-AI collaboration and actively addresses concerns regarding bias and transparency to ensure that AI-driven advancements prioritize patient well-being, safety and dignity.

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doi.org

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