Computer Sciences and Information Technology
Negatives of A.I. in medicine
We are doing a debate in class my side is against. The topic is A.I. I have chosen the task of doing the negatives of A.I. in medicine please produce this essay to be recited in a debate.
Negatives of A.I. in medicine
Use of Artificial Intelligence (AI) has been increasingly employed in medicine resulting in significant challenges. Use of AI in medicine comes with a lot of challenges leading to loss of life, prolonging the healing period or impossibility in the treatment process. Use of AI in medicine entails the supporting medical projects, applications and research use of data or knowledge and intensive computer-based solutions that enhance performance. On the other hand, medical decisions in traditional decision entailed adopting statistical methods to characterize patterns using mathematical equations. The difference arises in that AI brings techniques to eliminate complex associations that cannot be reduced to an equation. Use of AI in medicines have a wide range of range negativities to patients and medical professionals and thus the approaches should be discouraged in favor of traditional approaches in medicine.
To begin with, the use of AI in medicine is ethically and morally wrong (Krittanawong et al., 2017). In this respect, the use of AI in medicine remains to be questionable when human-like robots, androids and recreate intelligence are used in addressing patients’ needs. Health is a gift of nature that should not be recreated but rather patients need to be personally attended by medical professionals. In the case, when medical professionals are used in treating and handling patients the act becomes satisfying as opposed to using robots.
Consequently, using AI in medicine is leads to inflexibility as opposed to using traditional medicine (Pandey, Babita, and Mishra, 2009). In this regard, Robots and Android used in medicine are programmed and they cannot work beyond the program they have. Human used the senses and they utilize them in the course of addressing the patient but in the case that AI is used senses such as memory will not be used. Therefore, utilizing AI in medicine is not as effective as when a human being is handling and helping a patient.
Furthermore, the technological perceptions used in AI lack creativity and emotions that are experienced and seen in human beings while handling patients (Awwalu et al., 2015). In this respect, AI in medicine lacks sympathizing emotions such as those seen in nurses while they are in contact with the patient thus reducing wisdom and understanding. Additionally, despite the AI coding robots with common sense, this cannot be compared with common sense that human use in attending a patient.
Moreover, using AI in medicine does not benefit from improvement with experience as seen in humans (Patel et al., 2009). In this case, artificial intelligence cannot be improved with experience. On the contrary, wear and tear are experienced with time and experience. Instead, AI stores a lot of data but the mode of assessment and use is different from that of human intelligence. Additionally, the AI machines are not in a position to change in relation to changing environment thus replacing humans and machines in medicine is wrong as they do not incorporate passion, human touch, and togetherness in handling patients.
Lastly, the development and use of AI in medicine require huge costs. The high costs are involved in the acquiring and maintaining of the complex machines used in AI (Hmet, Pavet, and Johanne, 2017). Also, the software programs used require frequent graduation and updating to handle the changing environment and such process require a lot of funds. Additionally, breakdowns, processes of recovering lost codes and reinstating the system occur at a cost. Therefore, there are a lot of funds and resources required in acquiring the machines, maintaining and repairing them thus making AI expensive.
In conclusion, it is evident that the use of AI in medicine has many challenges as compared to the traditional approaches used in medicine. In this case, using AI in medicine is impractical, expensive, and impossible in some circumstances. The prevailing criticism of AI in medicine is that there is no human touch in the use of AI as well as the lack of flexibility that disqualifies the approach. Therefore, AI needs to be discouraged and instead use traditional approaches to handling and treating patients.
Awwalu, J., Garba, A. G., Ghazvini, A., & Atuah, R. (2015). Artificial intelligence in personalized medicine application of AI algorithms in solving personalized medicine problems. International Journal of Computer Theory and Engineering, 7(6), 439.
Hamet, P., & Tremblay, J. (2017). Artificial intelligence in medicine. Metabolism, 69, S36-S40.
Krittanawong, C., Zhang, H., Wang, Z., Aydar, M., & Kitai, T. (2017). Artificial intelligence in precision cardiovascular medicine. Journal of the American College of Cardiology, 69(21), 2657-2664.
Pandey, B., & Mishra, R. B. (2009). Knowledge and intelligent computing system in medicine. Computers in biology and medicine, 39(3), 215-230.
Patel, V. L., Shortliffe, E. H., Stefanelli, M., Szolovits, P., Berthold, M. R., Bellazzi, R., & Abu-Hanna, A. (2009). The coming of age of artificial intelligence in medicine. Artificial intelligence in medicine, 46(1), 5-17.