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- All Subjects: healthcare
- Resource Type: Text
This thesis explores the ethical implications of using facial recognition artificial intelligence (AI) technologies in medicine, with a focus on both the opportunities and challenges presented by the use of this technology in the diagnosis and treatment of rare genetic disorders. We highlight the positive outcomes of using AI in medicine, such as accuracy and efficiency in diagnosing rare genetic disorders, while also examining the ethical concerns including bias, misdiagnosis, the issues it may cause within patient-clinician relationships, misuses outside of medicine, and privacy. This paper draws on the opinions of medical providers and other professionals outside of medicine, which finds that while many are excited about the potential of AI to improve medicine, concerns remain about the ethical implications of these technologies. We discuss current legislation controlling the use of AI in healthcare and its ambiguity. Overall, this thesis highlights the need for further research and public discourse to address the ethical implications of using facial recognition and AI technologies in medicine, while also providing recommendations for its future use in medicine.
This thesis explores the ethical implications of using facial recognition artificial intelligence (AI) technologies in medicine, with a focus on both the opportunities and challenges presented by the use of this technology in the diagnosis and treatment of rare genetic disorders. We highlight the positive outcomes of using AI in medicine, such as accuracy and efficiency in diagnosing rare genetic disorders, while also examining the ethical concerns including bias, misdiagnosis, the issues it may cause within patient-clinician relationships, misuses outside of medicine, and privacy. This paper draws on the opinions of medical providers and other professionals outside of medicine, which finds that while many are excited about the potential of AI to improve medicine, concerns remain about the ethical implications of these technologies. We discuss current legislation controlling the use of AI in healthcare and its ambiguity. Overall, this thesis highlights the need for further research and public discourse to address the ethical implications of using facial recognition and AI technologies in medicine, while also providing recommendations for its future use in medicine.
In the US, underrepresented racial and ethnic minorities receive less than adequate health care in comparison to White Americans. This is attributed to multiple factors, including the long history of structural racism in the US and in the medical field in particular. A factor that is still prevalent today is the lack of diversity within the healthcare workforce. Racial and ethnic minorities are underrepresented in most healthcare occupations. Moreover, many physicians may continue to harbor implicit biases that may interfere with giving adequate care to patients of different backgrounds. We propose that diversity in healthcare should be increased through educational programs and a revamp of existing systems such as medical schools. The increased diversity would mitigate some of the health disparities that exist amongst minorities, as medical professionals are more likely to give adequate care to those who are members of the same community. Increased diversity would also help to increase the cultural competency of physicians as a whole.