RUI: Causes and consequences of early quitting in visual search: Investigating the role of distractors

RUI：视觉搜索中提前退出的原因和后果：调查干扰因素的作用

• 批准号: 2218384
• 负责人: Jeff Moher
• 金额: $ 22.31万
• 依托单位: Connecticut College
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-01-01 至 2024-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2218384&HistoricalAwards=false
• 关键词: RUI; Causes; consequences; early; quitting

Distractions are everywhere in modern life, and they bring consequences ranging from the mundane to the deadly. It is well established that distracting objects can attract attention when a viewer first looks at a scene. For example, a flashing roadside billboard may take a driver’s eyes off the road for a moment. But might distractions change behavior in other, more subtle but equally critical ways? Another key aspect of visual attention arises when a person searches for something that may or may not be present and must decide whether or not they’ve found what they are looking for. An important illustration of this is that when a radiologist searches a medical image, there may or may not be an area of concern present in the scan. In these searches, there is a strategic decision component in which the searcher must decide that they’ve looked thoroughly enough to be confident that indeed no “target” is present. However, there is a gap in our knowledge – there has been little research on how distracting objects might affect this decision component. In the current project, the investigators explore the phenomenon of distractor-induced quitting, in which distracting objects alter this decision process and cause people to terminate search earlier than they otherwise would. This early quitting causes people to entirely miss targets that they would otherwise likely find. Knowledge gained from this project will advance our understanding of how distractions are processed, leading to new insights into human behavior in the fields of attention, distraction, and decision-making. Furthermore, these results have potential real-world implications for tasks that involve high-stakes searches for targets, such as medical image screening or x-ray baggage inspection. In particular, it is worth considering that the use of salient signals (e.g., from artificial intelligence) to convey information to a human observer may inadvertently trigger this exact problematic situation. For example, if a computer system is trained to scan images and highlight potential areas of interest for a radiologist (or security personnel) by using a salient signal, these quitting effects might offset any benefits the computer guidance system might otherwise afford. Finally, undergraduate students participate in the design of these experiments, collection of data, and the presentation of results at conferences including those focused on medical imaging. Some of these students are recruited from the Science Leaders program at Connecticut College, a program dedicated to providing opportunities in the sciences for students from historically excluded identities.Salient signals can alter search strategies when people are looking for targets. More precisely, in recent work, the investigators have discovered that task-irrelevant distractors can cause people to quit searching early. As a result, people more frequently miss targets when these distractors are present. In this project, the investigators use a variety of experimental protocols to explore the impact of salient distractors on visual search in tasks where targets may or may not be present. Participants search for simple targets in visual displays with multiple non-targets and press a key to indicate whether a target is present or not. Eye-tracking is employed to investigate the specific mechanisms that cause participants to quit early as a result of visual distraction – for example, when a distractor is present, does it cause participants to scan the display less exhaustively? Or does it cause participants to look at each item for a shorter time, making them more likely to look at a target but fail to process it correctly? Next, the investigators establish factors that can modulate and potentially eliminate this distractor-induced quitting, such as giving participants control over the appearance and disappearance of a salient cue that may or may not highlight the target. Finally, the investigators examine how the information content of salient signals can impact distractor-induced quitting – in other words, if salient signals sometimes draw attention to the target, do those signals cause as much (or perhaps more) disruption on the occasions where they do not draw attention to the target? Results from these studies may aid our understanding of human visual attention and visual search. Findings are shared with the scientific community at large, but also (more specifically) with colleagues in radiology in order to spark new discussion on how the investigators might apply this research to help improve communications from artificial intelligence systems to human observers in medical settings.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

现代生活中干扰无处不在，它们会带来从平凡到致命的各种后果。众所周知，当观看者第一次看到某个场景时，分散注意力的物体可能会吸引驾驶员的注意力。但是，当一个人寻找可能存在或不存在的东西并必须决定它们是否存在时，注意力是否会以其他更微妙但同样重要的方式改变行为？我找到了它们是什么一个重要的例子是，当放射科医生搜索医学图像时，扫描中可能存在也可能不存在关注区域，搜索者必须在其中进行战略决策。确定他们已经足够彻底地检查，确信确实不存在“目标”。然而，我们的知识存在差距——在当前的项目中，关于分散注意力的物体如何影响这个决策部分的研究很少。研究人员探讨了分心导致的戒烟现象，其中分心物体改变了这个决策过程，导致人们比其他情况更早地终止搜索，这种提前退出会导致人们完全错过他们本来可能找到的目标，从这个项目中获得的知识将增进我们对如何处理干扰的理解。此外，这些结果对涉及高风险目标搜索的任务（例如医学图像筛查或 X 射线行李检查）具有潜在的现实意义。特别值得考虑的是，使用例如，如果计算机系统被训练来扫描图像并突出显示放射科医生（或保安人员）感兴趣的潜在区域，则向人类观察者传达信息的显着信号（例如来自人工智能）可能会无意中触发这种确切的问题情况。如果以其他方式使用显着信号，这些退出效应可能会抵消计算机引导系统可能提供的任何好处。最后，本科生参与这些实验的设计、数据收集以及在会议上展示结果，包括那些关注医学成像的会议。 .其中一些学生被录取来自康涅狄格学院的科学领袖项目，该项目致力于为历史上被排除在外的身份的学生提供科学机会。更准确地说，研究人员在最近的工作中发现，显着信号可以改变人们寻找目标的策略。与任务无关的干扰因素会导致人们提前停止搜索，因此，当这些干扰因素存在时，人们更容易错过目标。在这个项目中，研究人员使用各种实验方案来探索显着干扰因素对视觉搜索的影响。目标可能会或可能不会的任务参与者在具有多个非目标的视觉显示中搜索简单目标，并按下一个键来指示目标是否存在，以调查导致参与者提前退出的具体机制。视觉干扰——例如，当存在干扰物时，是否会导致参与者不太彻底地扫描显示器？或者是否会导致参与者查看每个项目的时间较短，从而使他们更有可能看到目标但无法看到？接下来，研究人员确定可以调节的因素并有可能消除这种由干扰因素引起的戒烟，例如让参与者控制可能会或可能不会突出目标的显着提示的出现和消失。最后，研究人员研究了显着信号的信息内容如何影响干扰因素引起的戒烟。 – 换句话说，如果显着信号有时会引起对目标的注意，那么这些信号是否会在它们不引起对目标的注意的情况下造成同样多（或者可能更多）的干扰？这些研究的结果可能有助于我们对人类的理解？视觉注意力和视觉搜索的发现是共享的。与整个科学界，而且（更具体地说）与放射学领域的同事一起，以引发新的讨论，反思研究人员如何应用这项研究来帮助改善医疗环境中人工智能系统与人类观察者的通信。该奖项 NSF法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。