Do We Need AI?

In a time with unpresented technological advancements through AI, what aspects of society does it makes sense to implement this futuristic technology?

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Intro:

The goal of this website is to gather various sources of unique perspectives and combine these perspectives into a broad conclusion about the implementation of AI into modern society to attempt to locate common themes that can be applied to the broader perspective of AI in society as its being implemented. Using these themes, we can attempt to predict where AI implementation will fail and where it will succeed in the following years.

The birth of Advanced Radiology – by Joe Janizek

This article offers the perspective of how AI works in its actual deployment especially in an expertise where AI far outperforms its human counterparts. In this article, Dr. Janizek discusses how his job as a radiologist is currently being taken over by AI because of AI’s immense ability to diagnose patients off of radiology images (CT scan, xray, etc.). Dr. Janizek predicts that because of the ease of AI diagnoses, patient imaging frequency should increase greatly. Dr. Janizek predicts that because of this, the radiologist’s job/role would adapt over time to manage the AI algorithms’ imaging reports and ensure their medical accuracy and relevance to their respective patient. Dr. Janizek importantly brings up that current radiologists are not being trained to manage AI algorithms in a clinical setting.

Thanks to the insightful perspective of Dr. Janizek, we can conclude that AI implementation in radiology is a huge upgrade from previous methods. And as we broaden our perspective it is obvious the benefits of AI algorithms in clinical settings outside of radiology improved development of medicines. Furthermore, an addition benefit would be increased frequency of imaging for patients that would lead to earlier diagnosis for the general population. However, despite these benefits, Dr. Janizek addresses many downsides that are unique to his perspective as a radiologist attempting to enter the workforce. As previously mentioned, Dr. Janizek believes that the occupation of radiologist will change drastically as a result of AI implementation, and in the future radiologists will most likely being managing AI imaging analysis for errors instead of diagnosing themselves. The downside of this shift in responsibility is that radiologists are not currently being trained to handle AI algorithms. As these algorithms get implemented into the common routine of medical practice, the likelihood of AI mismanagement effecting patients increases, decreasing the overall benefit of implementing AI algorithms in the first place despite the extraordinary and ultrahuman ability of AI algorithms. Overall, this article importantly demonstrates how the current and future workforce isn’t being trained to manage implemented AI systems in relevance to their occupation and how that can introduce risk and inefficiency in the implementation of AI algorithms.

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