Department of Bioethics, Hospital for Sick Children, Toronto, Ontario, Canada.
Health Team, Vector Institute, Toronto, Ontario, Canada.
BMJ Open. 2020 Oct 28;10(10):e039798. doi: 10.1136/bmjopen-2020-039798.
OBJECTIVES: Given widespread interest in applying artificial intelligence (AI) to health data to improve patient care and health system efficiency, there is a need to understand the perspectives of the general public regarding the use of health data in AI research. DESIGN: A qualitative study involving six focus groups with members of the public. Participants discussed their views about AI in general, then were asked to share their thoughts about three realistic health AI research scenarios. Data were analysed using qualitative description thematic analysis. SETTINGS: Two cities in Ontario, Canada: Sudbury (400 km north of Toronto) and Mississauga (part of the Greater Toronto Area). PARTICIPANTS: Forty-one purposively sampled members of the public (21M:20F, 25-65 years, median age 40). RESULTS: Participants had low levels of prior knowledge of AI and mixed, mostly negative, perceptions of AI in general. Most endorsed using data for health AI research when there is strong potential for public benefit, providing that concerns about privacy, commercial motives and other risks were addressed. Inductive thematic analysis identified AI-specific hopes (eg, potential for faster and more accurate analyses, ability to use more data), fears (eg, loss of human touch, skill depreciation from over-reliance on machines) and conditions (eg, human verification of computer-aided decisions, transparency). There were mixed views about whether data subject consent is required for health AI research, with most participants wanting to know if, how and by whom their data were used. Though it was not an objective of the study, realistic health AI scenarios were found to have an educational effect. CONCLUSIONS: Notwithstanding concerns and limited knowledge about AI in general, most members of the general public in six focus groups in Ontario, Canada perceived benefits from health AI and conditionally supported the use of health data for AI research.
目的:鉴于人们普遍希望将人工智能(AI)应用于健康数据,以改善患者护理和提高医疗体系效率,因此有必要了解公众对在 AI 研究中使用健康数据的看法。
设计:一项涉及 6 个焦点小组的定性研究,参与者为公众成员。首先,参与者讨论了他们对 AI 的总体看法,然后被要求分享他们对三个现实的健康 AI 研究场景的想法。使用定性描述性主题分析对数据进行分析。
地点:加拿大安大略省的两个城市:萨德伯里(多伦多以北 400 公里)和密西沙加(大多伦多地区的一部分)。
参与者:41 名精心挑选的公众成员(21 名男性:20 名女性,25-65 岁,中位数年龄 40 岁)。
结果:参与者对 AI 的先前知识水平较低,对 AI 的总体看法褒贬不一。当健康 AI 研究具有很大的公共利益潜力时,大多数人赞成使用数据,但前提是要解决隐私、商业动机和其他风险问题。归纳主题分析确定了 AI 特有的希望(例如,更快、更准确分析的潜力,能够使用更多数据的能力)、恐惧(例如,失去人机交互,过度依赖机器导致技能贬值)和条件(例如,计算机辅助决策的人工验证,透明度)。对于健康 AI 研究是否需要数据主体同意,存在不同意见,大多数参与者希望知道他们的数据是如何以及由谁使用的。尽管这不是研究的目标,但发现现实的健康 AI 场景具有教育效果。
结论:尽管公众对 AI 普遍存在担忧和有限的了解,但在加拿大安大略省的六个焦点小组中,大多数普通公众认为健康 AI 有好处,并在一定条件下支持使用健康数据进行 AI 研究。
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