The Artificial Intelligence Dilemma: Navigating Ethics in Healthcare

The integration of Artificial Intelligence (AI) into healthcare represents a transformative shift towards more accurate and efficient patient care, highlighted by advancements in disease detection, treatment adherence, and patient interaction. However, this technological evolution introduces significant ethical dilemmas, including concerns over empathetic care provision, data security, and bias in clinical decision-making. This literature review critically examines these ethical challenges and proposes potential solutions to ensure AI's beneficial integration into healthcare without compromising patient well-being. The exploration into AI's capacity for empathetic care reveals its limitations to cognitive empathy, suggesting a complementary role to human providers rather than a replacement. Data privacy concerns underscore the imperative for secure handling and consent mechanisms in the utilization of patient information, amidst the risk of misuse by large corporations. Furthermore, the review addresses AI-induced biases, advocating for diverse data representation and algorithmic transparency to mitigate discrimination and enhance treatment efficacy across varied populations. While acknowledging the potential of AI to revolutionize healthcare, this paper advocates for a cautious and ethically informed approach to its adoption, emphasizing the need for comprehensive legislation, stakeholder engagement, and ongoing scrutiny to safeguard against the erosion of trust and equity in patient care.

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Publication Details

Journal
University of Waterloo Journal of Undergraduate Health Research
Published
2024-12-30
DOI
https://doi.org/10.15353/juhr.v1i3.6106
Citations
3
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.36
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article

The Artificial Intelligence Dilemma: Navigating Ethics in Healthcare

Elen Mullaj
3 citations
University of Waterloo Journal of Undergraduate Health Research
Artificial Intelligence in Healthcare and Education
0.36
article

The Artificial Intelligence Dilemma: Navigating Ethics in Healthcare

Elen Mullaj
article en
3 citations

Abstract

The integration of Artificial Intelligence (AI) into healthcare represents a transformative shift towards more accurate and efficient patient care, highlighted by advancements in disease detection, treatment adherence, and patient interaction. However, this technological evolution introduces significant ethical dilemmas, including concerns over empathetic care provision, data security, and bias in clinical decision-making. This literature review critically examines these ethical challenges and proposes potential solutions to ensure AI's beneficial integration into healthcare without compromising patient well-being. The exploration into AI's capacity for empathetic care reveals its limitations to cognitive empathy, suggesting a complementary role to human providers rather than a replacement. Data privacy concerns underscore the imperative for secure handling and consent mechanisms in the utilization of patient information, amidst the risk of misuse by large corporations. Furthermore, the review addresses AI-induced biases, advocating for diverse data representation and algorithmic transparency to mitigate discrimination and enhance treatment efficacy across varied populations. While acknowledging the potential of AI to revolutionize healthcare, this paper advocates for a cautious and ethically informed approach to its adoption, emphasizing the need for comprehensive legislation, stakeholder engagement, and ongoing scrutiny to safeguard against the erosion of trust and equity in patient care.

University of Waterloo Journal of Undergraduate Health ResearchVol. 1(3)
University of Waterloo (CA)
Peace, Justice and strong institutions
Openalex Percentile: Top 34%
Artificial Intelligence in Healthcare and Education
0.36
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The Artificial Intelligence Dilemma: Navigating Ethics in Healthcare — Elen Mullaj · University of Waterloo Journal of Undergraduate Health Research (2024) | TGRS Research Map | TGRS