FW-HTF-R: Impact of Artificial Intelligence Aids on Clinical Skill Acquisition, Atrophy and Adaptation

FW-HTF-R：人工智能辅助对临床技能习得、萎缩和适应的影响

• 批准号: 2129072
• 负责人: Soumya Ray
• 金额: $ 200万
• 依托单位: Case Western Reserve University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-10-01 至 2025-09-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2129072&HistoricalAwards=false
• 关键词: FW; HTF; Impact; Artificial; Intelligence

Medical professionals learn many complex work skills. In future, artificial intelligence computer assistants will help these workers accomplish their work, and even take over some skilled tasks. When artificial intelligence aids assume skilled tasks, workers may adapt to rely on the aids, and their skills, if once learned, could atrophy. This project is investigating how learning and use of professional skills are changed by artificial intelligence assistants. The project is also studying how different assistant designs might affect learning and atrophy. Understanding these issues could lead to re-design of artificial intelligence aids and how they are used, with ultimate impact on workplace safety, training protocols, and patient care.To address these questions, the investigators are focusing on two critical skills used by clinical professionals: visual search, used by radiologistsexamining medical images, and spatial navigation under misalignedvisuomotor spaces, which is necessary to surgeons performing roboticlaparoscopic surgeries. For each skill, human participant experiments aredesigned to evaluate the impact of artificial intelligence assistance on skill learning, adaptation, and atrophy. The investigators are collecting data from participants without prior experience with these skills, as they learn and use the skills, and from medical residents, as they use these skills. Different artificial intelligence designs are being tested to understand their comparative impact on these participants' perceptual and spatial navigation skills. These skills are useful in many other work contexts, and the findings may generalize beyond these clinical professions.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

医学专业人员学习许多复杂的工作技能。在未来，人工智能计算机助理将帮助这些工人完成他们的工作，甚至接管一些需要技能的任务。当人工智能辅助工具承担技术任务时，工人可能会适应依赖辅助工具，他们的技能一旦学会，可能会萎缩。该项目正在研究人工智能助理如何改变专业技能的学习和使用。该项目还研究了不同的辅助设计如何影响学习和萎缩。了解这些问题可能会导致人工智能辅助工具的重新设计及其使用方式，最终影响工作场所安全，培训协议和患者护理。为了解决这些问题，研究人员正在关注临床专业人员使用的两项关键技能：视觉搜索，用于放射科医生检查医学图像，以及在错位视觉空间下的空间导航，这对外科医生进行机器人腹腔镜手术是必要的。对于每项技能，人类参与者实验旨在评估人工智能辅助对技能学习，适应和萎缩的影响。研究人员正在从没有这些技能经验的参与者那里收集数据，因为他们学习和使用这些技能，以及从医疗居民那里收集数据，因为他们使用这些技能。正在测试不同的人工智能设计，以了解它们对这些参与者的感知和空间导航技能的比较影响。这些技能在许多其他工作环境中也很有用，研究结果可能会推广到这些临床专业之外。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。