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虚拟助手是否值得信赖获取医疗保险信息:准确性和可靠性的检验。

Are Virtual Assistants Trustworthy for Medicare Information: An Examination of Accuracy and Reliability.

机构信息

Department of Psychology, Florida State University, Tallahassee, Florida, USA.

出版信息

Gerontologist. 2024 Aug 1;64(8). doi: 10.1093/geront/gnae062.

DOI:10.1093/geront/gnae062
PMID:38832398
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11258897/
Abstract

BACKGROUND AND OBJECTIVES

Advances in artificial intelligence (AI)-based virtual assistants provide a potential opportunity for older adults to use this technology in the context of health information-seeking. Meta-analysis on trust in AI shows that users are influenced by the accuracy and reliability of the AI trustee. We evaluated these dimensions for responses to Medicare queries.

RESEARCH DESIGN AND METHODS

During the summer of 2023, we assessed the accuracy and reliability of Alexa, Google Assistant, Bard, and ChatGPT-4 on Medicare terminology and general content from a large, standardized question set. We compared the accuracy of these AI systems to that of a large representative sample of Medicare beneficiaries who were queried twenty years prior.

RESULTS

Alexa and Google Assistant were found to be highly inaccurate when compared to beneficiaries' mean accuracy of 68.4% on terminology queries and 53.0% on general Medicare content. Bard and ChatGPT-4 answered Medicare terminology queries perfectly and performed much better on general Medicare content queries (Bard = 96.3%, ChatGPT-4 = 92.6%) than the average Medicare beneficiary. About one month to a month-and-a-half later, we found that Bard and Alexa's accuracy stayed the same, whereas ChatGPT-4's performance nominally decreased, and Google Assistant's performance nominally increased.

DISCUSSION AND IMPLICATIONS

LLM-based assistants generate trustworthy information in response to carefully phrased queries about Medicare, in contrast to Alexa and Google Assistant. Further studies will be needed to determine what factors beyond accuracy and reliability influence the adoption and use of such technology for Medicare decision-making.

摘要

背景与目的

人工智能 (AI) 为老年人在健康信息查询方面使用这项技术提供了潜在机会。关于对 AI 的信任的元分析表明,用户会受到 AI 受托人的准确性和可靠性的影响。我们评估了这些维度对医疗保险查询的响应。

研究设计与方法

在 2023 年夏天,我们评估了 Alexa、Google Assistant、Bard 和 ChatGPT-4 在医疗保险术语和大型标准化问题集中的一般内容方面的准确性和可靠性。我们将这些 AI 系统的准确性与二十年前接受过查询的大量代表性医疗保险受益人的准确性进行了比较。

结果

与医疗保险受益人的平均准确率(术语查询准确率为 68.4%,一般医疗保险内容查询准确率为 53.0%)相比,Alexa 和 Google Assistant 的准确率非常低。Bard 和 ChatGPT-4 回答医疗保险术语查询时完全正确,并且在一般医疗保险内容查询方面表现更好(Bard = 96.3%,ChatGPT-4 = 92.6%),高于平均医疗保险受益人。大约一个月到一个半月后,我们发现 Bard 和 Alexa 的准确性保持不变,而 ChatGPT-4 的性能略有下降,Google Assistant 的性能略有上升。

讨论与启示

与 Alexa 和 Google Assistant 不同,基于 LLM 的助手可以在针对医疗保险进行精心措辞的查询时生成可靠的信息。需要进一步研究来确定除了准确性和可靠性之外,还有哪些因素会影响对这类技术在医疗保险决策中的采用和使用。