Summary of Towards Clinical Ai Fairness: Filling Gaps in the Puzzle, by Mingxuan Liu et al.
Towards Clinical AI Fairness: Filling Gaps in the Puzzle
by Mingxuan Liu, Yilin Ning, Salinelat Teixayavong, Xiaoxuan Liu, Mayli Mertens, Yuqing Shang, Xin Li, Di Miao, Jie Xu, Daniel Shu Wei Ting, Lionel Tim-Ee Cheng, Jasmine Chiat Ling Ong, Zhen Ling Teo, Ting Fang Tan, Narrendar RaviChandran, Fei Wang, Leo Anthony Celi, Marcus Eng Hock Ong, Nan Liu
First submitted to arxiv on: 28 May 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Computers and Society (cs.CY)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper investigates the concept of fairness in Artificial Intelligence (AI) applied to healthcare. Despite significant technical advancements in AI fairness, there is a disconnect between these advancements and their practical clinical applications. The authors identify deficiencies in both healthcare data and AI fairness solutions, particularly in medical domains where AI technology is increasingly used. They highlight the overemphasis on group fairness, which focuses on equality among demographic groups from a macro healthcare system perspective, while individual fairness, focusing on equity at a more granular level, is often overlooked. To bridge these gaps, the authors propose actionable strategies for both the healthcare and AI research communities. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary AI technology is being used in healthcare, but there’s a big problem: it’s not fair! Imagine if doctors and hospitals made decisions based on who you are, like your age or gender, rather than what’s best for you. This paper talks about how to make sure AI is fair, especially when it comes to making decisions that affect people’s health. Right now, there’s a big gap between the ideas we have about fairness in AI and how we actually use it in hospitals and clinics. The authors of this paper want to change that by giving us some practical steps to follow. |
