In settings where users are both time-pressured and need high accuracy, such as doctors working in Emergency Rooms, we want to provide AI assistance that both increases accuracy and reduces time. However, different types of AI assistance have different benefits: some reduce time taken while increasing overreliance on AI, while others do the opposite. We therefore want to adapt what AI assistance we show depending on various properties (of the question and of the user) in order to best tradeoff our two objectives. We introduce a study where users have to prescribe medicines to aliens, and use it to explore the potential for adapting AI assistance. We find evidence that it is beneficial to adapt our AI assistance depending on the question, leading to good tradeoffs between time taken and accuracy. Future work would consider machine-learning algorithms (such as reinforcement learning) to automatically adapt quickly.

翻译：在用户既面临时间压力又需要高准确性的场景中（例如急诊室工作的医生），我们希望提供既能提高准确性又能缩短时间的人工智能辅助。然而，不同类型的人工智能辅助具有不同优势：有些能减少用时但增加对人工智能的过度依赖，而其他则相反。因此，我们需要根据（问题和用户的）不同属性自适应地调整所展示的人工智能辅助，以在两大目标之间实现最佳权衡。我们引入一项研究，要求用户为外星人开具药物处方，并借此探索自适应人工智能辅助的潜力。研究发现，根据问题特性调整人工智能辅助方案是有益的，这能在用时与准确性之间实现良好权衡。未来工作将考虑采用机器学习算法（如强化学习）来自动实现快速自适应调整。