Ambiguities or the issues we face with AI in medicine
Abstract With AI gradually becoming more relevant to healthcare, we are running into a diverse set of issues related to ambiguous medical data, expert disagreement, and biased outcomes. For AI to make accurate medical predictions, significant improvements in data collection, standardization, and ethical oversight are necessary, which come with their own set of additional challenges. In this thought piece I will lay out the issue of what ambiguities are, how they get to be and why they are so problematic in the medical AI context. Preface This is one text of a collection of essays and thought pieces that lies at the intersection of AI and other topics. I’d highly appreciate to receive ideas, feedback and opinions, as well as engage in meaningful discussions about the topics I cover in this collection of essays, which I seek to publish over the course of the next weeks and months. I am aware that they might have some typos, punctuation or grammatical errors, as I am just an individual writing this is my free time off work. I hope to engage with a community of people who share my passion for AI, and I’d highly appreciate getting some other perspectives on these topics as these texts are based on my understanding of AI, the world and some additional thoughts and notions. I might not explain things to their full extent, or in a way that makes my chain of thoughts a little bit hard to understand if you come from a different domain, so if there are sections within the texts that are not explained sufficiently feel free to reach out. For the sake of not burdening you with too much to read there will also be some over-simplifications in these texts. Please don’t see this as something set in stone. I am open to hearing different perspectives and broadening my view on this matter, as I am sure that there are points of view out there that are so far out of my field of view that I am unable to consider them as of now. Introduction - Ambiguities in the real