多样性(控制论)
算法
工作(物理)
分析
营销
经济
机器学习
计算机科学
人工智能
业务
数据科学
工程类
机械工程
作者
Arthur S. Jago,Glenn R. Carroll
标识
DOI:10.1177/01461672221149815
摘要
Producers and creators often receive assistance with work from other people. Increasingly, algorithms can provide similar assistance. When algorithms assist or augment producers, does this change individuals’ willingness to assign credit to those producers? Across four studies spanning several domains (e.g., painting, construction, sports analytics, and entrepreneurship), we find evidence that producers receive more credit for work when they are assisted by algorithms, compared with humans. We also find that individuals assume algorithmic assistance requires more producer oversight than human assistance does, a mechanism that explains these higher attributions of credit (Studies 1–3). The greater credit individuals assign to producers assisted by algorithms (vs. other people) also manifests itself in increased support for those producers’ entrepreneurial endeavors (Study 4). As algorithms proliferate, norms of credit and authorship are likely changing, precipitating a variety of economic and social consequences.
科研通智能强力驱动
Strongly Powered by AbleSci AI