The use of AI has increased over the past decades, making it easier for researchers to investigate the most complicated issues. In health care, AI may be employed to analyze sophisticated medical data. What is more, AI allows scientists to estimate conclusions without having to engage humans in their studies. However, along with evident benefits, the use of AI in health care also poses several challenges to healthcare delivery, such as unethicality of AI procedures, the subjectivity of results, and security threats to patient data.
Context
The founder of AI, Alan Turing, defined it as “the science and engineering of making intelligent machines, especially intelligent computer programs” (as cited in Loh, 2018, p. 59). This definition indicates that AI is likely to revolutionize healthcare practice. However, there are many concerns about the use of AI in health care. The questions raised in regard to AI are most frequently associated with ethical and legal issues (Pesapane, Volonté, Codari, & Sardanelli, 2018). Such aspects may include the safety of AI procedures, as well as data privacy. As such, it is necessary to investigate the potential challenges to the use of AI in health care so that it would be possible to find solutions to them.
1st Con-Point
The first issue that should be considered when scrutinizing the use of AI is the subjectivity of results obtained with the help of AI systems. According to Pesapane et al. (2018), the proceedings of research conducted by employing AI cannot be predicted. Thus, serious concerns are raised in relation to such studies. As Pesapane et al. (2018) report, the data exploited in machine learning to develop AI could copy human prejudices in the process of decision making. As a result, one should be cautious about the findings of studies conducted with the help of AI.
2nd Con-Point
The second aspect against the application of AI in health care is related to the possible threat to the security and privacy of patients’ data. As Meinert et al. (2018) notice, it is easy to fall victim of AI research due to the insufficient sustainability of technology and the lack of detailed plans. Additionally, AI studies do not always undergo timely assessments, which increases the likelihood of data leaks (Meinert et al., 2018). To gain the most beneficial results, scientists need to make sure that the systems are protected well and that hackers cannot reach patients’ personal information. So far, the number of cyber-crimes is alarmingly growing, and it is not applicable to consider the application of AI in health care as a safe option.
3rd Con-Point
Finally, the third reason why the AI should be used in health care cautiously is the unethicality of AI systems. Loh (2018) argues that there exists a “false sense of security” in presuming that AI research does not require intellectual input (p. 59). Thus, there is a lack of legal liability that might be required when medical errors arise. Additionally, there is an ethical issue associated with patients’ choices (Loh, 2018). Furthermore, a question of consent may appear since machines do not address this issue conclusively.
Conclusion
The use of AI in health care has some evident advantages, such as the possibility to operate much data within a short period of time. However, scientists and healthcare professionals should also be wary of the pitfalls that may occur on their way to finding successful resolutions to serious problems. Specifically, AI may be unethical, its results are not always objective, and there is a risk of patients’ data being disclosed to third parties.
References
Loh, E. (2018). Medicine and the rise of the robots: A qualitative review of recent advances of artificial intelligence in health. BMJ Leader, 2(2), 59-63.
Meinert, E., Alturkistani, A., Brindley, D., Knight, P., Wells, G., & de Pennington, N. (2018). Weighing benefits and risks in aspects of security, privacy and adoption of technology in a value-based healthcare system. BMC Medical Informatics and Decision Making, 18(1), 100.
Pesapane, F., Volonté, C., Codari, M., & Sardanelli, F. (2018). Artificial intelligence as a medical device in radiology: Ethical and regulatory issues in Europe and the United States. Insights into Imaging, 9(5), 745-753.