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Ethical Issues of Artificial Intelligence (AI) in the Healthcare

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Journal of Science, Technology and Innovation Policy

https://doi.org/10.11113/JOSTIP.V9N1.129
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7 pages

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Abstract

The idea of integrating ethics into artificial intelligence (AI) increased globally, and it became an important policy objective in many countries. The ethics of AI has seen significant press coverage in recent years, which supports related research, but also may end up undermining it.  The issues under discussion were just predictions of what future technology will bring, and we already know what would be most ethical and how to achieve that. This paper is a literature review in nature; it analyzes previous studies related to implementation of ethics in AI. The literature results indicate that between 2010 and 2021, there were 150 AI ethical incidents; including data privacy and security risks, safety concerns, bias diagnosis, the possibility of hostile entities taking control of AI, a lack of interpersonal communication or a humanistic perspective, wealth concentration around an AI business and job losses. The findings obtained from this literature review can help to propose metho...

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The term "AI" (AI) refers to a broad field that encom; business, engineering, biology, psychology, mathematics, infiltrating the healthcare sector and playing crucial ro allocation to the automation of time-consuming and characterized as machines imitating human cognitive Intelligence Incident Database (AIID), between 2010 and that from 2010 to 2016, the number of AI ethics issues c passes several academic fields, including computer science, statistics, logic, philosophy, and linguistics. AI is rapidly es in everything from patient management and resource standard tasks in medical practice. AI in healthcare is processes (Jha & Topol, 2016). According to Artificial 2021, there were 150 AI ethics incidents. Figure | shows ontinuously rose, peaking in 2016. The rapid growth of AI during that period could be connected to the trend of AI ad vancement technology (Wei & Zhou, 2022). Figure 1: Statistic of AI ethical incidents from 2010 to 2016 (Wei & Zhou, 2022)
The term "AI" (AI) refers to a broad field that encom; business, engineering, biology, psychology, mathematics, infiltrating the healthcare sector and playing crucial ro allocation to the automation of time-consuming and characterized as machines imitating human cognitive Intelligence Incident Database (AIID), between 2010 and that from 2010 to 2016, the number of AI ethics issues c passes several academic fields, including computer science, statistics, logic, philosophy, and linguistics. AI is rapidly es in everything from patient management and resource standard tasks in medical practice. AI in healthcare is processes (Jha & Topol, 2016). According to Artificial 2021, there were 150 AI ethics incidents. Figure | shows ontinuously rose, peaking in 2016. The rapid growth of AI during that period could be connected to the trend of AI ad vancement technology (Wei & Zhou, 2022). Figure 1: Statistic of AI ethical incidents from 2010 to 2016 (Wei & Zhou, 2022)
Figure 2: Statistic of AI ethical issues in healthcare in the United States as of 2021(Statista, 2022) Al incorporates the fundamentals of sensing, recognizing, and object identification to enable machines to perform as well as or even better than humans. As developers create AI systems to carry out these tasks, several risks and challenges appear, including data privacy and security risks, safety concerns, bias diagnosis, the possibility of hostile entities taking control of AI, a lack of interpersonal communication or a humanistic perspective, wealth concentration around an AI business and job losses (Statista, 2022)
Figure 2: Statistic of AI ethical issues in healthcare in the United States as of 2021(Statista, 2022) Al incorporates the fundamentals of sensing, recognizing, and object identification to enable machines to perform as well as or even better than humans. As developers create AI systems to carry out these tasks, several risks and challenges appear, including data privacy and security risks, safety concerns, bias diagnosis, the possibility of hostile entities taking control of AI, a lack of interpersonal communication or a humanistic perspective, wealth concentration around an AI business and job losses (Statista, 2022)

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