People over trust AI-generated medical responses and view them to be as valid as doctors, despite low accuracy

心理学 社会心理学 人工智能 计算机科学
作者
Shruthi Shekar,Pat Pataranutaporn,Chethan Sarabu,Guillermo Cecchi,Pattie Maes
出处
期刊:Cornell University - arXiv [Cornell University]
被引量:4
标识
DOI:10.48550/arxiv.2408.15266
摘要

This paper presents a comprehensive analysis of how AI-generated medical responses are perceived and evaluated by non-experts. A total of 300 participants gave evaluations for medical responses that were either written by a medical doctor on an online healthcare platform, or generated by a large language model and labeled by physicians as having high or low accuracy. Results showed that participants could not effectively distinguish between AI-generated and Doctors' responses and demonstrated a preference for AI-generated responses, rating High Accuracy AI-generated responses as significantly more valid, trustworthy, and complete/satisfactory. Low Accuracy AI-generated responses on average performed very similar to Doctors' responses, if not more. Participants not only found these low-accuracy AI-generated responses to be valid, trustworthy, and complete/satisfactory but also indicated a high tendency to follow the potentially harmful medical advice and incorrectly seek unnecessary medical attention as a result of the response provided. This problematic reaction was comparable if not more to the reaction they displayed towards doctors' responses. This increased trust placed on inaccurate or inappropriate AI-generated medical advice can lead to misdiagnosis and harmful consequences for individuals seeking help. Further, participants were more trusting of High Accuracy AI-generated responses when told they were given by a doctor and experts rated AI-generated responses significantly higher when the source of the response was unknown. Both experts and non-experts exhibited bias, finding AI-generated responses to be more thorough and accurate than Doctors' responses but still valuing the involvement of a Doctor in the delivery of their medical advice. Ensuring AI systems are implemented with medical professionals should be the future of using AI for the delivery of medical advice.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
实验室发布了新的文献求助200
1秒前
牧青发布了新的文献求助30
1秒前
1秒前
1秒前
冷傲迎梦发布了新的文献求助10
2秒前
蓝天的应助被王明初采纳,获得10
2秒前
3秒前
3秒前
Improve完成签到,获得积分10
3秒前
情怀的应助被2323142578采纳,获得10
3秒前
3秒前
鱼鱼完成签到,获得积分20
4秒前
ynwa发布了新的文献求助10
4秒前
小学三年级完成签到,获得积分10
4秒前
4秒前
hudie9206完成签到,获得积分10
4秒前
Kadirya发布了新的文献求助10
4秒前
没有名字完成签到 ,获得积分10
4秒前
郭雨非的学弟完成签到,获得积分20
5秒前
daihia7完成签到,获得积分10
5秒前
鲁万仇完成签到,获得积分10
6秒前
6秒前
棒棒的红红完成签到,获得积分10
6秒前
淡然白风发布了新的文献求助10
6秒前
一颗大葡萄完成签到,获得积分10
7秒前
冷傲迎梦完成签到,获得积分20
7秒前
8秒前
某叶完成签到 ,获得积分20
8秒前
大模型的应助被LITAO采纳,获得10
8秒前
秋风的应助被温暖的紫文采纳,获得10
8秒前
Willer完成签到,获得积分10
8秒前
轻松煎饼完成签到,获得积分10
9秒前
共享精神的应助被zzzzzz采纳,获得10
9秒前
9秒前
Shao_Jq完成签到 ,获得积分10
10秒前
LordAsriel完成签到,获得积分10
10秒前
11秒前
wanci的应助被WN采纳,获得10
11秒前
秋风的应助被迅速的青亦采纳,获得10
11秒前
11秒前
高分求助中
(应助此贴封号)通过应助OA文献获取积分 10000
Rosenblum, Global Change Biology 800
Computational Chemical Reaction Engineering: Modeling, Simulation, and Design with MATLAB 600
Organizational Behavior 510
Management and the Arts 510
Deformation and Fracture of the Lumbar Vertebral End Plate 500
CLSI C56QG Examples of Hemolyzed, Icteric, and Lipemic/Turbid Samples Quick Guide 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 计算机科学 工程类 纳米技术 内科学 物理 有机化学 化学工程 生物化学 复合材料 光电子学 细胞生物学 心理学 量子力学 催化作用 物理化学 电极
热门帖子
关注 科研通微信公众号,转发送积分 7802889
求助须知:如何正确求助?哪些是违规求助? 9336963
关于积分的说明 20483709
捐赠科研通 7394699
什么是DOI,文献DOI怎么找? 3326966
关于科研通互助平台的介绍 2474103
邀请新用户注册赠送积分活动 2345103