清晨好,您是今天最早来到科研通的研友!由于当前在线用户较少,发布求助请尽量完整的填写文献信息,科研通机器人24小时在线,伴您科研之路漫漫前行!

Human and Machine: The Impact of Machine Input on Decision Making Under Cognitive Limitations

人类多任务处理 计算机科学 机器学习 人工智能 认知 灵活性(工程) 过程(计算) 人机系统 风险分析(工程) 认知心理学 心理学 医学 统计 数学 神经科学 操作系统
作者
Tamer Boyacı,Caner Canyakmaz,Francis de Véricourt
出处
期刊:Management Science [Institute for Operations Research and the Management Sciences]
卷期号:70 (2): 1258-1275 被引量:24
标识
DOI:10.1287/mnsc.2023.4744
摘要

The rapid adoption of artificial intelligence (AI) technologies by many organizations has recently raised concerns that AI may eventually replace humans in certain tasks. In fact, when used in collaboration, machines can significantly enhance the complementary strengths of humans. Indeed, because of their immense computing power, machines can perform specific tasks with incredible accuracy. In contrast, human decision makers (DMs) are flexible and adaptive but constrained by their limited cognitive capacity. This paper investigates how machine-based predictions may affect the decision process and outcomes of a human DM. We study the impact of these predictions on decision accuracy, the propensity and nature of decision errors, and the DM’s cognitive efforts. To account for both flexibility and limited cognitive capacity, we model the human decision-making process in a rational inattention framework. In this setup, the machine provides the DM with accurate but sometimes incomplete information at no cognitive cost. We fully characterize the impact of machine input on the human decision process in this framework. We show that machine input always improves the overall accuracy of human decisions but may nonetheless increase the propensity of certain types of errors (such as false positives). The machine can also induce the human to exert more cognitive efforts, although its input is highly accurate. Interestingly, this happens when the DM is most cognitively constrained, for instance, because of time pressure or multitasking. Synthesizing these results, we pinpoint the decision environments in which human-machine collaboration is likely to be most beneficial. This paper was accepted by Jeannette Song, operations management. Supplemental Material: The data files and online appendices are available at https://doi.org/10.1287/mnsc.2023.4744 .
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
大幅提高文件上传限制,最高150M (2024-4-1)

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
2秒前
10秒前
Lorin完成签到 ,获得积分10
54秒前
1分钟前
1分钟前
1分钟前
1分钟前
1分钟前
1分钟前
1分钟前
1分钟前
2分钟前
2分钟前
老张完成签到 ,获得积分10
2分钟前
2分钟前
2分钟前
2分钟前
2分钟前
3分钟前
3分钟前
紫熊发布了新的文献求助10
3分钟前
3分钟前
3分钟前
3分钟前
3分钟前
3分钟前
3分钟前
谦也静熵完成签到,获得积分10
3分钟前
紫熊发布了新的文献求助20
3分钟前
3分钟前
3分钟前
方白秋完成签到,获得积分10
3分钟前
3分钟前
3分钟前
3分钟前
Richard完成签到 ,获得积分10
3分钟前
3分钟前
3分钟前
physicalproblem完成签到,获得积分10
3分钟前
4分钟前
高分求助中
The Oxford Handbook of Social Cognition (Second Edition, 2024) 1050
Kinetics of the Esterification Between 2-[(4-hydroxybutoxy)carbonyl] Benzoic Acid with 1,4-Butanediol: Tetrabutyl Orthotitanate as Catalyst 1000
The Young builders of New china : the visit of the delegation of the WFDY to the Chinese People's Republic 1000
Rechtsphilosophie 1000
юрские динозавры восточного забайкалья 800
English Wealden Fossils 700
Handbook of Qualitative Cross-Cultural Research Methods 600
热门求助领域 (近24小时)
化学 医学 生物 材料科学 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 基因 遗传学 催化作用 物理化学 免疫学 量子力学 细胞生物学
热门帖子
关注 科研通微信公众号,转发送积分 3139610
求助须知:如何正确求助?哪些是违规求助? 2790479
关于积分的说明 7795348
捐赠科研通 2446958
什么是DOI,文献DOI怎么找? 1301526
科研通“疑难数据库(出版商)”最低求助积分说明 626259
版权声明 601176