Understanding and Explaining Automated Decisions
Understanding and Explaining Automated Decisions
复制标题
理解和解释自动化决策
DOI：
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发表时间：
2019
期刊：
影响因子：
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通讯作者：
Annalisa Eichholzer
中科院分区：
文献类型：
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作者：
Alison Powell;Arnav Joshi;Paul;Georgina Bourke;I. Hutchinson;Annalisa Eichholzer
自动化决策，包括简单的算法计算以及机器学习和其他人工智能技术的更复杂的结果可能是不透明的。再加上设计阶段的决策所带来的偏见和不公正的风险，以及与用于训练自动化系统的数据相关的风险，意味着自动化系统可能会重现或加剧社会中已经存在的不平等现象。 “理解自动化决策”项目是由伦敦经济学院媒体与传播研究人员与技术工作室 Projects By IF 的设计师合作开展的，探索了通过设计界面来事前和事后解释自动化决策功能的方法。我们还探讨了征求公众对自动化系统治理和监管反思的方法。
主要发现：有多种方法可以通过简单的界面设计来展示如何使用数据来做出决策；事前和事后的解释方法分别针对系统设计和功能的不同领域，而界面原型可以帮助说明何时以及在什么情况下这些可能对使用或受这些系统影响的人们有所帮助；在某些情况下，这些基于界面的解释无法解决实际上可能对人们产生最大影响的系统元素；强调透明度作为可解释决策的主要基础可能无法解决系统设计的最重大影响；监管机构可能希望指定不同形式的可解释性，但也应该承认，解释作为实现或建立透明度的手段可能无法实现其所有目的。
Automated decisions including straightforward algorithmic calculations and more complex results of machine learning and other AI techniques can be opaque. This, combined with the risk of bias and injustice resulting from decisions taken at the design stage, and in relation to the data used to train automated systems, means that automated systems can reproduce or intensify inequalities already existing in society. The Understanding Automated Decisions project conducted through a partnership between LSE Media and Communication researchers and designers at technology studio Projects By IF, explored ways to explain automated decision function ex ante and ex post by designing interfaces. We also explored ways to solicit public reflection on the governance and regulation of automated systems.
Key Findings: There are ways to present how data are used to make decisions through simple interface design; Ex ante and ex post approaches to explanation each target different areas of system design and function, and interface prototypes can help to illustrate when and under what circumstances these may be helpful to people using or subject to these systems; In some cases these interface-based explanations can’t address the elements of the system that may actually have the greatest impact on people; Stressing transparency as the main underpinning for an explainable decision may not address the most significant impacts of a system design; Regulators may wish to specify different forms of explainability, but should also acknowledge that explanation, as a means of achieving or building on transparency may not achieve all its ends.
可能性的政治：超越可能性的风险和安全
DOI：
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发表时间：
2013
期刊：
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影响因子：
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作者：
Amoore, Louise
通讯作者：
Amoore, Louise