论文标题
利用解释桥接AI和人类
Harnessing Explanations to Bridge AI and Humans
论文作者
论文摘要
由于它们的出色预测能力，机器学习模型越来越多地整合到社会批判性的应用中，例如累犯预测和医学诊断。但是，在这些应用中，由于道德和法律问题，通常不希望完全自动化。因此，研究界已经冒险开发可解释的方法来解释机器预测。尽管这些解释旨在帮助人类理解机器预测，从而允许人类做出更好的决策，但在许多最近的研究中不支持这一假设。为了通过AI援助改善人类决策，我们提出了未来的方向，以结束解释功效与改善人类绩效之间的差距。
Machine learning models are increasingly integrated into societally critical applications such as recidivism prediction and medical diagnosis, thanks to their superior predictive power. In these applications, however, full automation is often not desired due to ethical and legal concerns. The research community has thus ventured into developing interpretable methods that explain machine predictions. While these explanations are meant to assist humans in understanding machine predictions and thereby allowing humans to make better decisions, this hypothesis is not supported in many recent studies. To improve human decision-making with AI assistance, we propose future directions for closing the gap between the efficacy of explanations and improvement in human performance.
