Abstract
In the realm of healthcare, the exponential growth of Artificial Intelligence has precipitated a need to scrutinize its ethical implications. This research undertakes a comprehensive survey to unravel the intricate tapestry of AI ethics within the healthcare landscape. Objective is to delineate the multifaceted challenges that arise from the symbiotic relationship between AI and healthcare and proposing viable solutions for mitigation. A pivotal focus of this study is to bridge the divide between medical practitioners and AI developers, thus addressing a conspicuous research gap. This gap pertains to fostering seamless collaboration between these stakeholders, ensuring that AI systems align with the actual requirements of healthcare providers. The paper explores strategies to establish an effective dialogue, facilitating the design and implementation of ethically sound AI applications. The paper also delves into the moral conundrums engendered by AI's lack of emotional intelligence in sensitive healthcare contexts. The absence of human emotional comprehension has, in certain instances, led to grievous outcomes, necessitating a nuanced approach to machine autonomy. This study advocates for an equilibrium where intelligent machines operate under prudent human oversight, striking a harmonious balance between precision and compassion. Furthermore, the research evaluates prevailing systems and their attendant challenges, emphasizing the advantages of integrating ethically guided, intelligent systems. The paper contemplates governance structures, protocols and strategies to counteract biases inherent in AI algorithms. By dissecting the principles of fairness, accountability and transparency, this study paves the way for a cogent framework that governs AI deployment within healthcare. In essence, this paper charts an uncharted course through the unexplored terrain of AI ethics in healthcare. It not only recognizes the inherent challenges but also underscores the imperative for ethical introspection. The insights herein have far reaching implications for shaping a future where AI and healthcare coalesce ethically, ultimately benefiting both patients and practitioners.
| Original language | English (US) |
|---|---|
| Title of host publication | Proceedings - 2023 IEEE 23rd International Conference on Software Quality, Reliability, and Security Companion, QRS-C 2023 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 826-833 |
| Number of pages | 8 |
| ISBN (Electronic) | 9798350359398 |
| DOIs | |
| State | Published - 2023 |
| Event | 23rd IEEE International Conference on Software Quality, Reliability, and Security Companion, QRS-C 2023 - Chiang Mai, Thailand Duration: Oct 22 2023 → Oct 26 2023 |
Publication series
| Name | Proceedings - 2023 IEEE 23rd International Conference on Software Quality, Reliability, and Security Companion, QRS-C 2023 |
|---|
Conference
| Conference | 23rd IEEE International Conference on Software Quality, Reliability, and Security Companion, QRS-C 2023 |
|---|---|
| Country/Territory | Thailand |
| City | Chiang Mai |
| Period | 10/22/23 → 10/26/23 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
All Science Journal Classification (ASJC) codes
- Computer Vision and Pattern Recognition
- Software
- Safety, Risk, Reliability and Quality
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