随着乳腺筛查服务转向使用医疗保健人工智能 (HCAI) 进行屏幕阅读，对公众对 HCAI 看法的研究可以为更多以人为本的实施提供信息。我们综合了公众对 HCAI 的总体看法，并回顾了女性对乳腺筛查中 AI 看法的初步研究。尽管存在广泛的担忧，但人们普遍对 HCAI 及其潜在好处持开放态度；同样，由于潜在的好处，女性对乳房筛查中的人工智能持开放态度，但也担心广泛的风险。女性希望放射科医生保持核心地位；监督、评估和绩效、关怀、公平和偏见、透明度和问责制是关键问题；女性对人工智能错误的容忍度可能低于对人为错误的容忍度。利用我们最近的澳大利亚初步研究，我们说明了在收集数据之前告知参与者的价值以及女性的观点。本研究对40名筛查年龄的女性规定了乳腺筛查AI实施的四个主要条件：1）保持人的控制； 2）强有力的绩效证据； 3）支持熟悉AI； 4）提供引入人工智能的充分理由。提供了三种解决方案来支持熟悉：透明度和信息；缓慢且分阶段的实施；并允许女性选择退出人工智能阅读。我们提供建议来指导人工智能在医疗保健领域的实施以及公众对 HCAI 观点的研究。乳腺筛查服务应该对人工智能的使用保持透明，并与女性分享有关乳腺筛查人工智能的信息。实施应该缓慢且分阶段进行，如果可能的话提供退出选项。筛查服务应展示强有力的治理以维持临床医生的控制，展示出色的人工智能系统性能，确保数据保护和偏见缓解，并给出充分的理由来证明实施的合理性。当这些措施落实到位时，女性更有可能认为 HCAI 在乳房筛查中的使用是合法且可接受的。版权所有 © 2024 作者。由爱思唯尔有限公司出版。保留所有权利。

As breast screening services move towards use of healthcare AI (HCAI) for screen reading, research on public views of HCAI can inform more person-centered implementation. We synthesise reviews of public views of HCAI in general, and review primary studies of women's views of AI in breast screening. People generally appear open to HCAI and its potential benefits, despite a wide range of concerns; similarly, women are open towards AI in breast screening because of the potential benefits, but are concerned about a wide range of risks. Women want radiologists to remain central; oversight, evaluation and performance, care, equity and bias, transparency, and accountability are key issues; women may be less tolerant of AI error than of human error. Using our recent Australian primary study, we illustrate both the value of informing participants before collecting data, and women's views. The 40 screening-age women in this study stipulated four main conditions on breast screening AI implementation: 1) maintaining human control; 2) strong evidence of performance; 3) supporting familiarisation with AI; and 4) providing adequate reasons for introducing AI. Three solutions were offered to support familiarisation: transparency and information; slow and staged implementation; and allowing women to opt-out of AI reading. We provide recommendations to guide both implementation of AI in healthcare and research on public views of HCAI. Breast screening services should be transparent about AI use and share information about breast screening AI with women. Implementation should be slow and staged, providing opt-out options if possible. Screening services should demonstrate strong governance to maintain clinician control, demonstrate excellent AI system performance, assure data protection and bias mitigation, and give good reasons to justify implementation. When these measures are put in place, women are more likely to see HCAI use in breast screening as legitimate and acceptable.Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.