Ethics of Artificial Intelligence in Healthcare
Author : Komal Ajaykumar Gond
1. Ethical forethoughts on the use of artificial intelligence in medicine
Adiid,(2023)
This paper focuses on exploring the ethical issues related to using artificial intelligence (AI) in healthcare and suggests ways to make the most of AI without violating ethical standards. It gives an overview of AI’s capabilities, applications, and potential ethical challenges. While AI can improve medical diagnostics, surgery, and healthcare delivery, there are concerns about biases in AI algorithms, lack of transparency, privacy issues, and the risk of reducing healthcare professionals’ skills or affecting the human touch in patient care. The paper emphasizes the need to address these concerns to ensure that AI is used in a way that benefits healthcare without causing harm. The authors, Professor Elhassan and Dr. Arabi, bring together real-world experience and academic expertise to offer valuable insights into these ethical challenges.
2.Artificial intelligence for health care: open ethical challenges
Bassem, et al (2024)
Artificial intelligence (AI) is becoming more popular across many industries because it can help improve resource use and produce better results through the analysis of large amounts of data. AI’s potential is also recognized in healthcare, but this field, more than others, needs to carefully think about the ethical issues involved and what could go wrong if things don’t work out as expected. This essay looks at the main ethical challenges that are currently present, organizes them into different categories based on their function, and suggests a way to prioritize these issues to help solve them.
Darrell (2023)
The use of artificial intelligence (AI) in healthcare has the potential to greatly improve diagnostics, treatment, and patient care. However, as AI advances quickly, there are ethical concerns about patient privacy, data security, and the risk of bias in AI systems. This paper examines these ethical issues, focusing on finding a balance between using AI to drive innovation and protecting patient privacy. It looks closely at the challenges and the rules that are in place to regulate AI in healthcare, aiming to offer useful insights for people working in healthcare, technology, and policy
Destiny, et al (2023)
Although artificial intelligence (AI) has become more common in healthcare over the past ten years, there are still many ethical, legal, and social concerns about how it is used, based on the views of doctors, patients, and the general public. This study looks at existing research to understand how patients, the public, and healthcare professionals feel about AI in healthcare, to get a clearer picture of these concerns from different viewpoints.
Eliseo (2022)
Artificial Intelligence (AI) is changing healthcare by improving personalized medicine, helping detect diseases earlier, customizing treatments for individuals, and managing medical resources more efficiently. However, its use also raises concerns about data privacy, acceptance by healthcare professionals, and the need for clear regulations. This study looks at the benefits and challenges of AI in healthcare, focusing on its role in diagnostics, treatment, and medical workflows while addressing ethical and legal issues. It reviews scientific articles, case studies, and reports from hospitals that have successfully used AI to improve diagnostic accuracy, treatment efficiency, and reduce costs. The findings show that AI improves diagnosis and treatment, lowers costs by preventing late-stage treatments,but challenges like algorithm transparency, bias, and data security still need to be addressed for broader adoption.
6.The Rise of Artificial Intelligence and Machine Learning in HealthCare Industry
Ioana, et al (2025)
This study looks at the recent developments in healthcare due to the rise of artificial intelligence (AI). It reviews existing research to explore how AI is being used in treatments, diagnoses, and disease predictions. As the healthcare industry adopts AI to improve services, machine learning is playing a key role in predicting and diagnosing diseases. While AI creates new opportunities, it also presents challenges. The study examines how AI has impacted healthcare, the technologies used, their limitations, and the future potential of AI in the field. It also looks at the social and ethical issues surrounding AI in healthcare. Overall, the study shows that as AI and machine learning continue to advance, they will improve healthcare efficiency and services.
7.Ethical, legal, and social implications (ELSI) of virtual agents and virtual reality in healthcare
Rudschies, et al (2024)
Virtual agents (VAs) and virtual reality (VR) applications in healthcare offer new ways for people to access medical services, especially for those in remote areas, and provide innovative treatment options. However, using these technologies raises important ethical, social, and legal concerns. Issues include how these technologies affect the doctor-patient relationship, privacy, fairness, access to care, and questions about accountability and safety. This paper reviews existing research to explore these concerns and suggests ways to reduce negative effects while also pointing out areas where more research is needed.
8.AI and Machine Learning in Healthcare – Applications, Challenges and Ethics
Swapna, et al (2024)
This research explores how AI and machine learning are used in healthcare, the challenges of implementing these technologies, and the ethical concerns surrounding their adoption. The study highlights the rapid growth of healthcare data and the need for strong data governance to protect privacy and security. As AI and machine learning are increasingly used to analyze this data and improve patient care, they are transforming the healthcare system. However, more research is needed to ensure these technologies comply with regulations and maintain ethical standards, especially regarding patient security and privacy.
Vo, et al (2023)
The COVID-19 pandemic has led to the rapid adoption of telehealth and AI-driven telemedicine, which offer benefits like better accessibility and efficiency in healthcare. However, this quick rollout highlights the need for thorough evaluation processes to assess their effectiveness and outcomes. This article emphasizes the importance of developing proper evaluation frameworks to ensure these technologies are safe, effective, and aligned with healthcare goals and regulations. It calls for adaptable evaluation methods to optimize the use of telehealth and AI, improve patient care, and address emerging challenges in the healthcare system.
10.Application of ethical AI requirements to an AI solution use-case in healthcare domain
Zohreh, et al (2023)
This paper explores how applying ethical AI standards to a healthcare use case can be effective, using open educational resources for Trustworthy AI. The study used a Hackathon, where eight teams of students and faculty worked together to propose recommendations for the healthcare use case based on what they learned from the resources. The university research team created the use case and evaluated the results. The Hackathon produced a framework of recommendations that met EU Trustworthy AI standards. This study is unique because it’s the first time open educational resources for Trustworthy AI have been used in higher education.
Conclusion:
AI in healthcare has great potential to help detect diseases at an early stage and improve patient care. However, using people’s data raises ethical concerns about privacy, fairness, and bias. If the data used to train AI systems isn’t diverse, it could lead to unfair treatment or misdiagnosis for certain groups. It’s important to protect patient privacy, make sure AI decisions are clear and explainable, and ensure there’s human oversight in the process to maintain trust and care quality. Additionally, clear accountability for AI-driven decisions is necessary, as is maintaining human oversight to preserve the compassionate, personal aspect of healthcare.
The integration of AI into healthcare offers incredible potential for improving patient care, but it also presents significant ethical challenges. One of the primary concerns is ensuring that AI systems are free from bias. If an AI model is trained on data that doesn’t represent diverse populations, it could result in disparities in care. Biases related to race, gender, and socioeconomic status may cause AI to make inaccurate predictions or recommendations, ultimately reinforcing existing inequalities in healthcare.
Another key ethical issue is transparency and accountability. AI systems are often complex, and their decision-making processes can be difficult to understand, even for experts. In healthcare, where decisions directly affect patients’ well-being, it is vital that AI systems are explainable and their predictions can be scrutinized. Medical professionals need to be able to trust and understand the AI’s reasoning, and there must be clear accountability if things go wrong.
Finally, patient privacy and data security are paramount. AI systems rely on vast amounts of sensitive healthcare data to function effectively, which creates concerns over data breaches and unauthorized access. Safeguarding this information while ensuring informed consent from patients is crucial. As AI continues to advance in healthcare, regulations must evolve to address these concerns and protect individuals’ rights while fostering innovation that improves care delivery.
REFERENCES:
1. adiid, hibanan: The Ethical Implications of Artificial Intelligence in Healthcare: Balancing Innovation and Patient Privacy
2. Bassem T. ElHassan&Alya A. Arabi: Ethical forethoughts on the use of artificial intelligence in medicine
3. Darrell Norman Burrell: Dynamic Evaluation Approaches to Telehealth Technologies and Artificial Intelligence (AI) Telemedicine Applications in Healthcare and Biotechnology Organizations
4. Destiny Ogaga&Haoning Zhao: The Rise of Artificial Intelligence and Machine Learning in HealthCare Industry
5. Eliseo Sciarretta: Artificial intelligence for health care: open ethical challenges
6. Ioana-Marcela PÄ‚CURARU &Ciprian-Sorin CHIRVASE &Åžtefan-Ioan TIRITEU: The Role Of Artificial Intelligence In Personalised Medicine: Advancements, Challenges, And Future Perspectives
7. Rudschies, Catharina & Schneider, Ingrid: Ethical, legal, and social implications (ELSI) of virtual agents and virtual reality in healthcare
8. SwapnaNadakuditi& Bhargava Kumar &Tejaswini Kumar: AI and Machine Learning in Healthcare – Applications, Challenges and Ethics
9. Vo, Vinh& Chen, Gang & Aquino, Yves Saint James & Carter, Stacy M. & Do,QuynhNga&Woode, MaameEsi: Multi-stakeholder preferences for the use of artificial intelligence in healthcare: A systematic review and thematic analysis
10. ZohrehPourzolfaghar& Marco Alfano& Markus Helfert : Application of ethical AI requirements to an AI solution use-case in healthcare domain