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
The Drawbacks of Artificial Intelligence in Medicine
Artificial intelligence (AI) is increasingly being used in medicine, posing significant challenges. The use of AI in medicine poses numerous challenges, including the loss of life, the prolongation of the healing period, and the impossibility of treatment. AI in medicine entails the use of data or knowledge to support medical projects, applications, and research, as well as intensive computer-based solutions that improve performance. Traditional medical decisions, on the other hand, entailed using statistical methods to characterize patterns using mathematical equations. The distinction is that AI employs techniques for removing complex associations that cannot be reduced to an equation. The use of artificial intelligence in medicine has a wide range of negative consequences for patients and medical professionals, and thus the approaches should be discouraged in favor of traditional approaches in medicine.
To begin with, the use of artificial intelligence in medicine is unethical and morally repugnant (Krittanawong et al., 2017). In this regard, when human-like robots, androids, and recreate intelligence are used to address patients’ needs, the use of AI in medicine remains questionable. Health is a natural gift that should not be recreated; instead, patients should be personally attended to by medical professionals. When medical professionals are used to treat and handle patients, the act becomes more satisfying than when robots are used.
As a result, when compared to traditional medicine, using AI in medicine leads to inflexibility (Pandey, Babita, and Mishra, 2009). In this regard, robots and androids used in medicine are programmed and cannot function outside of the program. Humans use their senses and use them when interacting with patients, but when AI is used, senses such as memory are not used. As a result, using AI in medicine is not as effective as when a human is handling and Helping a patient.
Furthermore, the technological perceptions used in AI lack the creativity and emotions that humans experience and see when dealing with patients (Awwalu et al., 2015). In this regard, AI in medicine lacks sympathizing emotions like those seen in nurses while in contact with patients, reducing wisdom and understanding. Furthermore, despite AI coding robots with common sense, this cannot be compared to human common sense when attending to a patient.
Furthermore, unlike humans, AI in medicine does not benefit from improvement with experience (Patel et al., 2009). Artificial intelligence cannot be improved with experience in this case. Wear and tear, on the other hand, occur with time and experience. Instead, AI stores a large amount of data, but its Assessment and application differs from that of human intelligence. Furthermore, AI machines are unable to adapt to changing environments, so replacing humans and machines in medicine is incorrect because they do not incorporate passion, human touch, and teamwork in patient care.
Finally, the development and application of AI in medicine incurs enormous costs. The acquisition and maintenance of the complex machines used in AI incurs significant costs (Hmet, Pavet, and Johanne, 2017). Furthermore, the software programs used require frequent graduation and updating to keep up with the changing environment, which is a costly process. Furthermore, breakdowns, the processes of recovering lost codes, and reinstating the system all come at a cost. As a result, there are a lot of funds and resources needed to acquire the machines, maintain and repair them, making AI expensive.
In conclusion, it is clear that the use of AI in medicine faces numerous challenges when compared to traditional approaches. In this case, using AI in medicine is impractical, expensive, and in some cases impossible. The most common criticism leveled at AI in medicine is that it lacks human touch and flexibility, which disqualifies the approach. As a result, AI should be discouraged in favor of using traditional approaches to handling and treating patients.
References
J. Awwalu, A. G. Garba, A. Ghazvini, and R. Atuah (2015). Artificial intelligence in personalized medicine is the use of AI algorithms to solve problems in personalized medicine. 7(6), 439, International Journal of Computer Theory and Engineering.
P. Hamet and J. Tremblay (2017). Medical applications of artificial intelligence S36-S40 in Metabolism.
C. Krittanawong, H. Zhang, Z. Wang, M. Aydar, and T. Kitai (2017). Precision cardiovascular medicine with artificial intelligence. The American College of Cardiology Journal, 69(21), 2657-2664.
B. Pandey and R. B. Mishra (2009). In medicine, a knowledge and intelligent computing system is used. 215-230 in Computers in Biology and Medicine, 39(3).
V. L. Patel, E. H. Shortliffe, M. Stefanelli, P. Szolovits, M. R. Berthold, R. Bellazzi, and A. Abu-Hanna (2009). The dawn of artificial intelligence in medicine. 5-17 in Artificial Intelligence in Medicine, 46(1).
