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使用人工智能thanabots作为"thanatobots"来协助解剖学学习和专业发展:伪装成机会的幽灵?

Jon Cornwall¹, Sabine Hildebrandt²

¹Centre for Early Learning in Medicine, Otago Medical School, University of Otago, Dunedin, New Zealand.

Anatomical sciences education

|December 21, 2025

概括

以人工智能驱动的已故个体的数字表现Thanabots为解剖学教育提供了潜在的好处,但也带来了重大的心理和道德风险. 在实施之前,仔细考虑它们对人文参与和学习成果的影响至关重要.

科学领域:

医学教育医学教育
人工智能的人工智能
数字人文学科数字人文学科

背景情况:

人工智能 (AI) 技术的出现为医学教育提供了新的工具.
萨纳机器人 (Thanabots) 是人工智能生成的已故个体的数字表现,是解剖学教育的假设创新.

研究的目的:

为解剖学教育工作者提供关于机器人技术的概述.
探索在解剖教育中使用thanabots的实用和伦理考虑.
批判性地检查机器人集成的潜在好处和风险.

主要方法:

本文介绍了一个关于在解剖教育中使用机器人的思想实验.
讨论仅限于在捐赠者医疗记录上训练的thanabots,并由解剖学教育软件支持.
对潜在的心理,道德和教学挑战进行了审查.

主要成果:

潜在的好处包括通过将病史与解剖学和个性化的教学联系起来来增强学习.
风险包括不良心理影响,人文参与度下降以及潜在的AI错误影响学习准确性.
伦理问题包括数据管理,同意,文化敏感性和立法漏洞.

结论:

在解剖学教育中使用Thanabot需要仔细评估心理和社会影响.
在采用之前,必须批判性地检查道德,文化和教育方面的挑战.
负责任的实施需要对机器人的能力和局限性有充分的了解.

关键词:

器官供体器官供体器官供体器官提供者死亡机器人死亡机器人伦理学伦理伦理学悲伤的机器人悲伤的机器人人文主义人文主义人文主义医学教育医学教育

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