Course Project - Partial Draft This week, you will draft the first body parts of the essay you outlined last week. Historical Context - Examining history, including important events, controversies, an
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Ethical Implementation of Artificial Intelligence in Healthcare
Brent Boca
DeVry University
LAS432
Pierre Olivier Weiss
09/27/2025
Introduction
Artificial Intelligence (AI) is changing the face of healthcare- enhancing diagnostic accuracy, optimizing treatment, and personalizing care. As an illustration, AI technologies have higher accuracy and sensitivity in mammography than human radiologists (McKinney et al., 2020). There are also ethical and social concerns about the privacy of the information, the bias of the algorithm and accountability that come with this rapid growth too, but in a negative way. The innovation should be socially responsible and ethical in order to make AI more useful to the entire patients. In this paper, we will use a practical approach that focuses on how artificial intelligence in health care on how artificial intelligence will be helpful to the most number of people.
Historical Context
The evolution of AI in health started in 1970s through the creation of simple expert systems like MYCIN which assisted doctors in diagnosing bacterial infections. These systems were based on the application of a series of programmed rules for proposing medical diagnoses: this was an early effort to integrate computer science with clinical decision making. In the 1990s, machines began to become learning technology in which predictors and computers could be employed to work out the details of patients in order to be able to identify whether patients could or could not develop diseases.
The deep learning technology became the healthcare revolution in the 2010s after radically changing how diagnostic images are obtained and drug discoveries are made (Esteva et al., 2019). However, with the addition of the capacities offered by AI, additional ethical and legal controversies also began to appear. In 2017, Google DeepMind data scandal, in which patient data were used without the appropriate consent, improved the necessity to manage data transparently and to ensure better regulations. Although laws like the Health Insurance Portability and Accountability Act (HIPAA) and the General Data Protection Regulation (GDPR) employed in the European Union have provided certain advocacies, they have not developed rapidly to abreast with the rising use of AI in medicine.
Current Situation
Artificial intelligence has gained importance in the health sector. It can be applied to support medical scanning, patient feeding, office efficiency, and even sanity with chat bots and virtual helpers. The major parties of interest include patients, health care experts, artificial intelligence creators, the regulating authorities and health insurance firms (Al Kuwaiti et al., 2023). Google Health and IBM Watson Health are the technology firms that have shown innovation in AI and are implemented by the hospitals and clinics to boost efficiency and patient outcomes. There are grave aspects about which, with the use of AI, an ethical issue arises.
The use of patient data during model training is typically performed without complete understanding of the solution that is threat to privacy and autonomy. Moreover, despite recent technological advances, AI cannot be properly advertised to prevent algorithmic bias, an instance where the software reproduces what society currently views as unequal describes unequal treatment in relation to minority groups (Obermeyer et al., 2019). The aspect of accountability is also unclear because it is not clear to whom one has to direct artificial intelligence misconduct when medical decisions incorporating AI lead to errors. Lastly, the sustainability of healthcare industry ethics-related to the usage of AI relates to the environmental cost to train large models of AI, such as a data center that demands high power usage.
Future Strengths and Requirements.
It is possible to state that the future of AI in healthcare is both promising and quite challenging. The medical sphere can potentially become the area in which AI can be utilized to improve the efficiency of illnesses detection in the acute phase, customized medical approaches, prevent human error, and more medical services to areas with low coverage. Nevertheless, there are certain dangers present in the technology and they should be addressed. Having no appropriate supervision, AI might serve as the cause of healthcare disparities, cybersecurity gaps, and loss of patient’s faith in healthcare facilities.
The health care workers are also becoming burdened with a growing need to educate and train on how medical workers can make fair and competent use of AI in clinical medicine (Sun et al., 2023). Healthcare executives will have to work on comprehensive ethical codes and rules to ensure that AI has an overall positive impact in the long run. Constant checking, openness in the creation of algorithms, and medical education of patients will be essential to the task of ensuring AI supplements, replacing, human judgment and empathy in the medical sphere.
Recommendations
Some significant steps are necessary in order to address the problem of unethical and inappropriate use of AI in healthcare.
Firstly, transparency and accountability ought to be established during the process of AI development and implementation. These developers are supposed to be asked to provide the source of data, logic algorithms, and test processes to gain or provide a source of public confidence, and enable verification by others.
Second, the absence of bias must be cultivated by the brutalities of bias waving and non-representative data sets. This will also assist in avoiding discrimination of lowly populations.
Third, AI tools must be cheaper and easier to use in impoverished, tax-exempt hospitals and developing nations, thereby making them greener and ensuring that more products of the innovation are produced sensitively to ethical concerns and preserving patients and their rights.
Finally, AI tools must be cheaper and easier to use in impoverished, tax-exempt hospitals and developing nations, thereby making them greener and ensuring that more products of the innovation are produced sensitively to ethical concerns and preserving patients and their rights.
Conclusion
Since AI can improve healthcare and healthcare and healthcare in turn, it is the chance of AI to change the world of healthcare specifically and enhance its quality and efficiency. Nevertheless, unscrupulous AI may enhance social disparity and disrupt the three practices. Utilitarian ethics approach is concerned with maximizing benefits to the maximum population and minimizing harm. Therefore, the concepts of transparency, fairness, and accountability of AI systems need to be introduced. With accountable leadership and ethical policymaking, AI will have the potential to be a game changer by making patients, practitioners, and serve the global healthcare system by promoting justice, equity, and sustainability.
References
Al Kuwaiti, A., Nazer, K., Al-Reedy, A., Al-Shehri, S., Al-Muhanna, A., Subbarayalu, A. V., ... & Al-Muhanna, F. A. (2023). A review of the role of artificial intelligence in healthcare. Journal of personalized medicine, 13(6), 951.
Esteva, A., Robicquet, A., Ramsundar, B., Kuleshov, V., DePristo, M., Chou, K., ... & Dean, J. (2019). A guide to deep learning in healthcare. Nature Medicine, 25(1), 24–29. https://doi.org/10.1038/s41591-018-0316-z
McKinney, S. M., Sieniek, M., Godbole, V., Godwin, J., Antropova, N., Ashrafian, H., ... & Suleyman, M. (2020). International evaluation of an AI system for breast cancer screening. Nature, 577(7788), 89–94. https://doi.org/10.1038/s41586-019-1799-6
Sun, L., Yin, C., Xu, Q., & Zhao, W. (2023). Artificial intelligence for healthcare and medical education: a systematic review. American journal of translational research, 15(7), 4820.
Reflection
The most difficult issue I have encountered in the project has been summarization of the complex information about ethics and technical matters in a short, properly-constructed essay. The most significant milestone that I have achieved to date is the establishment of a comprehensible thesis connecting the fulfillment of the promise of AI to the ethical duty of the creators and users of AI. I have considered to be the most interesting part of the project the fact that AI can save lives, on the one hand, and encourage bias, on the other. To ensure the success of my project, I will make rational use of time and maintain my research on peer-reviewed academic sources, as well as underline my recommendations with greater attention to simplicity and ethical validity in the long-run improvement of healthcare.
