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Artificial Intelligence in Healthcare Innovation

Updated: Mar 15

Artificial intelligence is on the rise, and with its introduction, the face of healthcare may change drastically if the right precautions are not enforced. (The opinions expressed in this article are those of the individual author.)


By the year 2025, artificial intelligence (AI) is expected to replace 85 million jobs around the world. While these statistics may encourage fear in everyday workers, we must also think about the implications of this technology in the development of future employment opportunities. In the healthcare industry, for example, technological innovations have allowed for increased efficiency, improved relations between patients and professionals, and optimized the overall execution of critical tasks. The commercial success of medical robots may serve to highlight the benefits of automated devices, including AI.


Since the first robotic-assisted surgery in 1985, in which a brain biopsy procedure was performed under the supervision of Dr. Yik San Kwoh of California’s Memorial Medical Center, it is clear that the objective of this technology is not to replace humans but to overcome the issue of human error. The robot (PUMA 560) was an experimental innovation created and perfected over the course of three years with the interest of eliminating tremors and unwanted movement.


This particular case is raised to demonstrate that technological evolutions in the medical sector are not an outright consequence of the emergence of artificial intelligence. However, AI systems have the capacity to advance the operations of the healthcare industry to new heights. It is arguable though that far greater than the concern of massive unemployment is a lack of regulation.


According to a recent study conducted by MIT, generative AI technology contributed to a roughly 37% increase in white-collar productivity. With the introduction of new AI-powered applications, like ChatGPT for writing and Midjourney for art, humans have become reliant on technology to meet varying demands. This trend, while seemingly innocuous, brings about the dilemma as to whether AI poses a potential risk.


These sentiments are echoed by members of Congress, major companies, and federal agencies alike. The consensus is that the growth of artificial intelligence is coupled by ethical challenges. For the future of healthcare, improving AI transparency may ensure moral principles are upheld.


Recent literature discussing AI transparency in healthcare predominantly focuses on the aspects of privacy and security. In some events, patient privacy and data protection have been mishandled by AI. This completely violates the intention of their design, which is to be resilient and reliable.


Yet, in more prolific instances, the technology proves promising: after successfully programming the artificial intelligence model ChatGPT to take (and pass) the United States Medical Licensing Exam, researchers from Massachusetts General Hospital and AnsibleHealth discovered ChatGPT has practical uses in the field of medical education. In addition to other supportive roles, there is also the opportunity for artificial intelligence to detect diseases faster and to diagnose patients by analyzing their symptoms. It can even one day be trained to interpret medical codes or prepare billing reports, reducing the workload of coders and medical billers.


There are abundant advantages to the implementation of AI technology in healthcare, but the possibility of unlawful interception and malicious usage still looms. Lawmakers warn that responses to the technology should not be blindly expedited: understanding the problems imposed by AI is more essential than devising congressional strategies as a band-aid solution. To that effect, it is most likely necessary to temporarily halt the formation of artificial intelligence at this time. Doing so would help to address what exactly AI is capable of and what this means for our country, our healthcare system, and society.


The opinions expressed in this article are those of the individual author.


Sources


Kaldi, Ben. “Expert Reaction: Chatgpt Can (Almost) Pass the US Medical Licensing Exam.” Scimex, 10 Feb. 2023, https://www.scimex.org/newsfeed/chatgpt-can-almost-pass-the-us-medical-licensing-exam.


Noy, Shakked, and Whitney Zhang. “Experimental Evidence on the Productivity Effects of Generative Artificial Intelligence.” SSRN Electronic Journal, 2023,https://doi.org/10.2139/ssrn.4375283.


Patel, Vipul R. Robotic Urologic Surgery. Springer, 2022.

“Recession and Automation Changes Our Future of Work, but There Are Jobs Coming, Report Says.” World Economic Forum, https://www.weforum.org/press/2020/10/recession-and-automation-changes-our-future-of-work-but-there-are-jobs-coming-report-says-52c5162fce/.


Spatharou, Angela, et al. “Transforming Healthcare with AI: The Impact on the Workforce and Organizations.” McKinsey & Company, McKinsey & Company, 10 Mar. 2020,https://www.mckinsey.com/industries/healthcare/our-insights/transforming-healthcare-with-ai.

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