AI in the hands of imperfect users.

AI in the hands of imperfect users.
复制标题

DOI:
10.1038/s41746-022-00737-z
复制
发表时间:
2022-12-28
影响因子:
15.2
通讯作者:
--
中科院分区:
医学1区
文献类型:
--
作者:

文献摘要

参考文献

被引文献

相似文献

随着人工智能和机器学习(AI/ML)在医疗保健领域的应用不断扩大,人们越来越关注如何减轻算法中的偏见,以确保算法得到公平和透明的使用。较少关注AI/ML人类用户之间的潜在偏见或影响用户依赖的因素。我们主张在使用AI/ML工具时采用系统的方法来识别用户偏见的存在和影响,并呼吁开发嵌入式界面设计功能,借鉴决策科学和行为经济学的见解,以推动用户使用AI/ML进行更关键和反思的决策。
As the use of artificial intelligence and machine learning (AI/ML) continues to expand in healthcare, much attention has been given to mitigating bias in algorithms to ensure they are employed fairly and transparently. Less attention has fallen to addressing potential bias among AI/ML’s human users or factors that influence user reliance. We argue for a systematic approach to identifying the existence and impacts of user biases while using AI/ML tools and call for the development of embedded interface design features, drawing on insights from decision science and behavioral economics, to nudge users towards more critical and reflective decision making using AI/ML.
DOI: 10.1007/s11948-020-00213-5
发表时间: 2020-04-03
影响因子: 3.7
作者:
Floridi, Luciano;Cowls, Josh;Taddeo, Mariarosaria
通讯作者: Taddeo, Mariarosaria
DOI: 10.1080/014492998119526
发表时间: 1998-05-01
影响因子: 3.7
作者:
Dijkstra, JJ;Liebrand, WBG;Timminga, E
通讯作者: Timminga, E
DOI: 10.1016/j.joep.2011.10.009
发表时间: 2012-02-01
影响因子: 3.5
作者:
Dolan, P.;Hallsworth, M.;Vlaev, I.
通讯作者: Vlaev, I.
预测累犯的准确性,公平性和局限性。
DOI: 10.1126/sciadv.aao5580
发表时间: 2018-01
期刊: Science advances
影响因子: 13.6
作者:
Dressel J;Farid H
通讯作者: Farid H
DOI: 10.1111/j.1467-8624.2009.01295.x
发表时间: 2009-05-01
期刊: CHILD DEVELOPMENT
影响因子: 4.6
作者:
Corriveau, Kathleen H.;Harris, Paul L.;de Rosnay, Marc
通讯作者: de Rosnay, Marc