论文标题
关于可解释的AI对自动化偏差的影响
On the Influence of Explainable AI on Automation Bias
论文作者
论文摘要
人工智能（AI）正在增强动力，并且在许多领域（例如医学和银行业）对工作的未来的重要性正在不断上升。但是，对人类和人工智能有效合作的见解仍然很少见。通常，AI通过解决人类局限性来支持人类决策。但是，这也可能引起人类的偏见，尤其是以自动化偏见的形式作为对AI建议的过度依赖。我们的目的是阐明通过可解释的AI（XAI）影响自动化偏见的潜力。在此预测试中，我们得出了一个研究模型并描述了我们的研究设计。随后，我们对酒店审查分类进行了在线实验，并讨论了第一个结果。我们希望我们的研究能够为安全混合情报系统的设计和开发做出贡献。
Artificial intelligence (AI) is gaining momentum, and its importance for the future of work in many areas, such as medicine and banking, is continuously rising. However, insights on the effective collaboration of humans and AI are still rare. Typically, AI supports humans in decision-making by addressing human limitations. However, it may also evoke human bias, especially in the form of automation bias as an over-reliance on AI advice. We aim to shed light on the potential to influence automation bias by explainable AI (XAI). In this pre-test, we derive a research model and describe our study design. Subsequentially, we conduct an online experiment with regard to hotel review classifications and discuss first results. We expect our research to contribute to the design and development of safe hybrid intelligence systems.
