Analysis of public perceptions on the use of artificial intelligence in genomic medicine.

IF 3.8 3区医学 Q2 GENETICS & HEREDITY

Human Genomics Pub Date : 2024-11-18 DOI:10.1186/s40246-024-00686-6

Jack E Harrison, Fiona Lynch, Zornitza Stark, Danya F Vears

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引用次数: 0

Abstract

Purpose: Next generation sequencing has led to the creation of large pools of genomic data with analysis rather than data generation now the limiting factor. Artificial intelligence (AI) may be required to optimize the benefits of these data, but little is known about how the public feels about the use of AI in genomics.

Methods: We conducted focus groups with members of the Australian public. Participants were recruited via social media advertisements. We explored potential uses of AI in genomic medicine, the benefits, risks, and the possible social implications of its use.

Results: Participants (n = 34) largely felt comfortable with AI analysing their own genomic data and generally agreed about its benefits. Concerns were raised over data security, the potential for misdiagnosis, and bias AI may perpetuate. Many participants wanted checking mechanisms for when results were generated using AI.

Conclusions: The insights gained from these discussions help to understand public concerns around the use of AI in genomic medicine. Our findings can help to inform both policies around genomic AI and how to educate the public on its use.

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分析公众对人工智能在基因组医学中应用的看法。

目的：下一代测序技术产生了大量的基因组数据，现在限制因素是分析而不是数据生成。要优化这些数据的效益，可能需要人工智能（AI），但公众对在基因组学中使用人工智能的看法却知之甚少：我们与澳大利亚公众进行了焦点小组讨论。我们通过社交媒体广告招募参与者。我们探讨了人工智能在基因组医学中的潜在用途、使用人工智能的益处、风险以及可能产生的社会影响：结果：参与者（n = 34）对人工智能分析自己的基因组数据基本感到满意，并普遍认同人工智能的好处。但也有人对数据安全、误诊的可能性以及人工智能可能造成的偏见表示担忧。许多与会者希望在使用人工智能生成结果时能有检查机制：从这些讨论中获得的见解有助于了解公众对人工智能在基因组医学中应用的担忧。我们的发现有助于为有关基因组人工智能的政策以及如何教育公众使用人工智能提供信息。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Human Genomics GENETICS & HEREDITY-

CiteScore

6.00

自引率

2.20%

发文量

审稿时长

11 weeks

期刊介绍： Human Genomics is a peer-reviewed, open access, online journal that focuses on the application of genomic analysis in all aspects of human health and disease, as well as genomic analysis of drug efficacy and safety, and comparative genomics. Topics covered by the journal include, but are not limited to: pharmacogenomics, genome-wide association studies, genome-wide sequencing, exome sequencing, next-generation deep-sequencing, functional genomics, epigenomics, translational genomics, expression profiling, proteomics, bioinformatics, animal models, statistical genetics, genetic epidemiology, human population genetics and comparative genomics.