The quest to develop intelligent visual analytics (VA) systems capable of collaborating and naturally interacting with humans presents a multifaceted and intriguing challenge. VA systems designed for collaboration must adeptly navigate a complex landscape filled with the subtleties and unpredictabilities that characterize human behavior. However, it is noteworthy that scenarios exist where human behavior manifests predictably. These scenarios typically involve routine actions or present a limited range of choices. This paper delves into the predictability of user behavior in the context of visual analytics tasks. It offers an evidence-based discussion on the circumstances under which predicting user behavior is feasible and those where it proves challenging. We conclude with a forward-looking discussion of the future work necessary to cultivate more synergistic and efficient partnerships between humans and the VA system. This exploration is not just about understanding our current capabilities and limitations in mirroring human behavior but also about envisioning and paving the way for a future where human-machine interaction is more intuitive and productive.

翻译：开发能够与人协作并自然交互的智能视觉分析系统，是一项兼具多面性与趣味性的挑战。面向协作的视觉分析系统需在人类行为特有的微妙性与不可预测性交织的复杂情境中灵活应对。然而值得注意的是，在某些场景下人类行为会呈现可预测性——这类场景通常涉及常规操作或有限的选项范围。本文聚焦视觉分析任务中用户行为的可预测性，基于实证依据探讨了在何种情境下用户行为可被预测、何时难以预测的边界条件。最后，我们展望了未来研究方向，旨在构建人与视觉分析系统之间更具协同效应与高效性的伙伴关系。此项探索不仅关乎理解当前人类行为刻画的潜力与局限，更着眼于为人机交互迈向更直觉化、更高效的未来铺就道路。