Hermeneutics as impediment to AI in medicine.

Theoretical medicine and bioethics Pub Date : 2025-02-01 Epub Date: 2025-02-26 DOI:10.1007/s11017-025-09701-w
Kyle Karches
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Abstract

Predictions that artificial intelligence (AI) will become capable of replacing human beings in domains such as medicine rest implicitly on a theory of mind according to which knowledge can be captured propositionally without loss of meaning. Generative AIs, for example, draw upon billions of written sources to produce text that most likely responds to a user's query, according to its probability heuristic. Such programs can only replace human beings in practices such as medicine if human language functions similarly and, like AI, does not rely on meta-textual resources to convey meaning. In this essay, I draw on the hermeneutic philosophy of Hans-Georg Gadamer to challenge this conception of human knowledge. I follow Gadamer in arguing that human understanding of texts is an interpretive process relying on previously received judgments that derive from the human person's situatedness in history, and these judgments differ from the rules guiding generative AI. Human understanding is also dialogical, as it depends on the 'fusion of horizons' with another person to the extent that one's own prejudices may come under question, something AI cannot achieve. Furthermore, artificial intelligence lacks a human body, which conditions human perception and understanding. I contend that these non-textual sources of meaning, which must remain obscure to AI, are important in moral practices such as medicine, particularly in history-taking, physical examination, diagnostic reasoning, and negotiating a treatment plan. Although AI can undoubtedly aid physicians in certain ways, it faces inherent limitations in replicating these core tasks of the physician-patient relationship.

诠释学是医学人工智能的障碍。
人工智能(AI)将有能力在医学等领域取代人类的预测,隐含地建立在一种心智理论的基础上,根据这种理论,知识可以在不失去意义的情况下被命题地捕获。例如,生成式人工智能根据其概率启发式,利用数十亿的书面资源来生成最有可能回应用户查询的文本。只有在人类语言功能类似的情况下,这些程序才能在医学等实践中取代人类,并且像人工智能一样,不依赖元文本资源来传达意义。在这篇文章中,我借鉴了汉斯-乔治·伽达默尔的解释学哲学来挑战这种人类知识的概念。我遵循伽达默尔的观点,认为人类对文本的理解是一个依赖于先前接受的判断的解释过程,这些判断源于人类在历史中的处境,这些判断与指导生成式人工智能的规则不同。人类的理解也是对话的,因为它依赖于与另一个人的“视野融合”,以至于一个人自己的偏见可能会受到质疑,这是人工智能无法做到的。此外,人工智能缺乏人体,人体制约着人类的感知和理解。我认为,这些非文本的意义来源对人工智能来说必须是模糊的,但在医学等道德实践中是重要的,特别是在记录历史、体检、诊断推理和协商治疗计划方面。尽管人工智能无疑可以在某些方面帮助医生,但在复制医患关系的这些核心任务时,它面临着固有的限制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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