Doing AI: Algorithmic decision support as a human activity
CoRR(2024)
摘要
Algorithmic decision support (ADS), using Machine-Learning-based AI, is
becoming a major part of many processes. Organizations introduce ADS to improve
decision-making and make optimal use of data, thereby possibly avoiding
deviations from the normative "homo economicus" and the biases that
characterize human decision-making. A closer look at the development process of
ADS systems reveals that ADS itself results from a series of largely
unspecified human decisions. They begin with deliberations for which decisions
to use ADS, continue with choices while developing the ADS, and end with using
the ADS output for decisions. Finally, conclusions are implemented in
organizational settings, often without analyzing the implications of the
decision support. The paper explores some issues in developing and using ADS,
pointing to behavioral aspects that should be considered when implementing ADS
in organizational settings. It points out directions for further research,
which is essential for gaining an informed understanding of the processes and
their vulnerabilities.
更多查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要