Challenges of using artificial intelligence in healthcare : ethical, legal and regulatory perspectives
Khan, Faisal; Ali, Aftab; Ahmad, Niaz (2025)
2025
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2025112730349
https://urn.fi/URN:NBN:fi:amk-2025112730349
Tiivistelmä
The purpose of the thesis is to explore the ethical, legal and regulatory challenges associated with integration of artificial intelligence in healthcare system. The aim is explored how these challenges impact trust, accountability, and patient safety within clinical practice and to give recommendation for developing trustworthy AI system in healthcare services including diagnosis and treatment.
Descriptive literature review methodology is followed, drawing upon peer reviewed academic sources published between 2019 to 2025. The analysis was conducted systematically using authentic database sources including Google Scholar, Science Direct and PubMed.
The results indicates that AI has considerably advanced diagnostic accuracy and reduced operational workload in healthcare sector. Its integration has highlighted important concerns. These includes patient data safety, transparency, regulation, ethics and algorithm bias. The study highlighted the urgent need for clear ethical governance, strong broad surveillance and development of proper regulatory framework. These approaches support the safe and reliable integration of AI technologies within healthcare system.
Ethical, legal and robust regulation are necessary for ensuring that AI applications align with human values and professional standard in healthcare. The results emphasize the importance of patient centred design and international collaboration to adoptive trustworthy AI.
Descriptive literature review methodology is followed, drawing upon peer reviewed academic sources published between 2019 to 2025. The analysis was conducted systematically using authentic database sources including Google Scholar, Science Direct and PubMed.
The results indicates that AI has considerably advanced diagnostic accuracy and reduced operational workload in healthcare sector. Its integration has highlighted important concerns. These includes patient data safety, transparency, regulation, ethics and algorithm bias. The study highlighted the urgent need for clear ethical governance, strong broad surveillance and development of proper regulatory framework. These approaches support the safe and reliable integration of AI technologies within healthcare system.
Ethical, legal and robust regulation are necessary for ensuring that AI applications align with human values and professional standard in healthcare. The results emphasize the importance of patient centred design and international collaboration to adoptive trustworthy AI.