Statistical learning of anomalous regions in complex faux X-ray images does not transfer between detection and discrimination

The (Im)perfect Automation Schema: Who Is Trusted More, Automated or Human Decision Support?

OBJECTIVE

This study's purpose was to better understand the dynamics of trust attitude and behavior in human-agent interaction.

BACKGROUND

Whereas past research provided evidence for a perfect automation schema, more recent research has provided contradictory evidence.

METHOD

To disentangle these conflicting findings, we conducted an online experiment using a simulated medical X-ray task. We manipulated the framing of support agents (i.e., artificial intelligence (AI) versus expert versus novice) between-subjects and failure experience (i.e., perfect support, imperfect support, back-to-perfect support) within subjects. Trust attitude and behavior as well as perceived reliability served as dependent variables.

RESULTS

Trust attitude and perceived reliability were higher for the human expert than for the AI than for the human novice. Moreover, the results showed the typical pattern of trust formation, dissolution, and restoration for trust attitude and behavior as well as perceived reliability. Forgiveness after failure experience did not differ between agents.

CONCLUSION

The results strongly imply the existence of an imperfect automation schema. This illustrates the need to consider agent expertise for human-agent interaction.

APPLICATION

When replacing human experts with AI as support agents, the challenge of lower trust attitude towards the novel agent might arise.

The impact of clock timing on VDT visual search performance under time constraint

Introduction

Conducting Visual Display Terminal (VDT) visual search tasks under time constraint has broad applications in fields such as security checks, medical diagnostics, and rescue operations. While excessive time pressure can impair performance, moderate time pressure can motivate individuals to complete tasks and increase productivity. Investigating the positive impact of time pressure on visual search tasks has become a crucial area of study. Clock timing plays a vital role in the visual interface, influencing the perception of time pressure and impacting visual search performance. However, existing research has paid little attention to the induction of time pressure and the impact of clock timing in VDT visual interfaces on visual search performance. Hence, the objective of this study is to investigate the impact of clock timing on VDT visual search performance under time constraint.

Methods

The content of the experimental tasks was determined through a pilot experiment. The formal experiment was conducted in two phases over six sessions. Participants were tasked with locating the letter "E" embedded within the distractor letter "F," displayed with a clock area above the interface. The first phase of experiments included conditions of no clock, 4-min clock timing, and 4-min countdown clock timing. In the second phase of the experiment, the clock display method was a countdown clock, with three experiments conducted featuring long time, medium time, and short time. Search speed and accuracy were used as primary performance evaluation metrics to examine the impact of clock timing methods and duration on visual search performance. Twenty-one undergraduate students participated in the formal experiment.

Results

In the first phase of experiments, participants demonstrated significantly faster reaction times (RTs) in tasks where a clock display was present compared to tasks without (ANOVA, F(2, 60) = 4.588, P = 0.014). However, there were no significant differences in accuracy rates across different timing conditions (ANOVA, F(2, 60) = 0.146, P = 0.865), and no significant correlation between RTs and accuracy was found (Kendall's R = 0.11, P = 0.914). During the second phase, RTs decreased significantly as time constraints became more stringent (ANOVA, F(2, 60) = 7.564, P < 0.05). Conversely, accuracy rates decreased significantly under shorter time constraints (ANOVA, F(2, 60) = 4.315, P < 0.05), with a negative correlation observed between RTs and accuracy (Kendall's R = 0.220, P < 0.01).

Discussion

Compared to conditions without clock displays, having clock displays significantly improved the speed of the visual search task, although the difference in accuracy was not statistically significant. In the context of shorter clock countdown limits, Shorter timing constraints resulted in faster search speeds but also led to reduced accuracy and increased fatigue. Overall, a correlation exists between search speed and accuracy in visual tasks, where higher speed often correlates with lower accuracy. These findings provide valuable insights into clock timing design for visual search interfaces under time pressure.

Stability of individual differences in implicitly guided attention

Daily activities often occur in familiar environments, affording us an opportunity to learn. Laboratory studies have shown that people readily acquire an implicit spatial preference for locations that frequently contained a search target in the past. These studies, however, have focused on group characteristics, downplaying the significance of individual differences. In a pre-registered study, we examined the stability of individual differences in two variants of an implicit location probability learning (LPL) task. We tested the possibility that individual differences were stable in variants that shared the same search process, but not in variants involving different search processes. In Experiment 1, participants performed alternating blocks of T-among-Ls and 5-among-2s search tasks. Unbeknownst to them, the search target appeared disproportionately often in one region of space; the high-probability regions differed between the two tasks. LPL transferred between the two tasks. In addition, individuals who showed greater LPL in the T-task also did so in the 5-task and vice versa. In Experiment 2, participants searched for either a camouflaged-T against background noise or a well-segmented T among well-segmented Ls. These two tasks produced task-specific learning that did not transfer between tasks. Moreover, individual differences in learning did not correlate between tasks. Thus, LPL is associated with stable individual differences across variants, but only when the variants share common search processes.

Understanding the Impact of Time Pressure and Automation Support in a Visual Search Task

OBJECTIVE

To understand the impact of time pressure and automated decision support systems (DSS) in a simulated medical visual search task.

BACKGROUND

Time pressure usually impairs manual performance in visual search tasks, but DSS support might neutralize this negative effect. Moreover, understanding the impact of time pressure and DSS support seems relevant for many real-world applications of visual search.

METHOD

We used a visual search paradigm where participants had to search for target letters in a simulated medical image. Participants performed the task either manually or with support of a highly reliable DSS. Time pressure was varied within-subjects by either a trialwise time-pressure manipulation (Experiment 1) or a blockwise manipulation (Experiment 2). Performance was assessed based on signal detection measures. To further analyze visual search behavior, a mouse-over approach was used.

RESULTS

In both experiments, results showed impaired sensitivity under high compared to low time pressure in the manual condition, but no negative effect of time pressure when working with a highly reliable DSS. Moreover, participants searched less under time pressure and when receiving DSS support, indicating participants followed the automation without thoroughly checking recommendations. However, the human-DSS team's sensitivity was always worse than that of the DSS alone, independent of the strength of time pressure.

CONCLUSION

Negative effects of time pressure can be ameliorated when receiving support by a DSS, but joint overall performance remains below DSS-alone performance.

APPLICATION

Highly reliable DSS seem capable of ameliorating the negative impact of time pressure in complex detection tasks.

Contribution of peripheral vision to attentional learning

Attention is tuned towards locations that frequently contain a visual search target (location probability learning; LPL). Peripheral vision, covering a larger field than the fovea, often receives information about the target. Yet what is the role of peripheral vision in attentional learning? Using gaze-contingent eye tracking, we examined the impact of simulated peripheral vision loss on location probability learning. Participants searched for a target T among distractor Ls. Unbeknownst to them, the T appeared disproportionately often in one quadrant. Participants searched with either intact vision or "tunnel vision," restricting the visible search items to the central 6.7º (in diameter) of the current gaze. When trained with tunnel vision, participants in Experiment 1 acquired LPL, but only if they became explicitly aware of the target's location probability. The unaware participants were not faster finding the target in high-probability than in low-probability locations. When trained with intact vision, participants in Experiment 2 successfully acquired LPL, regardless of whether they were aware of the target's location probability. Thus, whereas explicit learning may proceed with central vision alone, implicit LPL is strengthened by peripheral vision. Consistent with Guided Search (Wolfe, 2021), peripheral vision supports a nonselective pathway to guide visual search.

A global and local perspective of interruption frequency in a visual search task

We investigated the impact of frequency of interruptions in a simulated medical visual search task. Participants (N = 150) performed the visual search task during which they were interrupted by a number-classification task in 25, 50, or 75% of all trials, respectively, reflecting the frequency conditions (i.e., low, mid, high). Target presence (i.e., present vs. absent) and interruption (i.e., uninterrupted vs. interrupted) were varied within-subjects, and interruption frequency was varied between-subjects. Globally, on a frequency condition level, participants in the low frequency condition had longer mean response times (RT) for the primary visual search task than in the high condition, but there were no other performance differences between the three frequency conditions. Locally, on the level of specific interruption effects, accuracy decreased directly after interruptions for target present but not for target absent trials. Furthermore, interruptions caused significant interruption costs, reflected in slower overall RTs in interrupted than in uninterrupted trials. The combined findings show that especially for critical visual search tasks as in the medical field, interruptions—regardless of frequency—should be avoided.

Is probabilistic cuing of visual search an inflexible attentional habit? A meta-analytic review

In studies on probabilistic cuing of visual search, participants search for a target among several distractors and report some feature of the target. In a biased stage the target appears more frequently in one specific area of the search display. Eventually, participants become faster at finding the target in that rich region compared to the sparse region. In some experiments, this stage is followed by an unbiased stage, where the target is evenly located across all regions of the display. Despite this change in the spatial distribution of targets, search speed usually remains faster when the target is located in the previously rich region. The persistence of the bias even when it is no longer advantageous has been taken as evidence that this phenomenon is an attentional habit. The aim of this meta-analysis was to test whether the magnitude of probabilistic cuing decreases from the biased to the unbiased stage. A meta-analysis of 42 studies confirmed that probabilistic cuing during the unbiased stage was roughly half the size of cuing during the biased stage, and this decrease persisted even after correcting for publication bias. Thus, the evidence supporting the claim that probabilistic cuing is an attentional habit might not be as compelling as previously thought.

Visual search behavior and performance in luggage screening: effects of time pressure, automation aid, and target expectancy

Visual inspection of luggage using X-ray technology at airports is a time-sensitive task that is often supported by automated systems to increase performance and reduce workload. The present study evaluated how time pressure and automation support influence visual search behavior and performance in a simulated luggage screening task. Moreover, we also investigated how target expectancy (i.e., targets appearing in a target-often location or not) influenced performance and visual search behavior. We used a paradigm where participants used the mouse to uncover a portion of the screen which allowed us to track how much of the stimulus participants uncovered prior to their decision. Participants were randomly assigned to either a high (5-s time per trial) or a low (10-s time per trial) time-pressure condition. In half of the trials, participants were supported by an automated diagnostic aid (85% reliability) in deciding whether a threat item was present. Moreover, within each half, in target-present trials, targets appeared in a predictable location (i.e., 70% of targets appeared in the same quadrant of the image) to investigate effects of target expectancy. The results revealed better detection performance with low time pressure and faster response times with high time pressure. There was an overall negative effect of automation support because the automation was only moderately reliable. Participants also uncovered a smaller amount of the stimulus under high time pressure in target-absent trials. Target expectancy of target location improved accuracy, speed, and the amount of uncovered space needed for the search.Significance Statement Luggage screening is a safety-critical real-world visual search task which often has to be done under time pressure. The present research found that time pressure compromises performance and increases the risk to miss critical items even with automation support. Moreover, even highly reliable automated support may not improve performance if it does not exceed the manual capabilities of the human screener. Lastly, the present research also showed that heuristic search strategies (e.g., areas where targets appear more often) seem to guide attention also in luggage screening.

Perceptual learning in the identification of lung cancer in chest radiographs

Extensive research has shown that practice yields highly specific perceptual learning of simple visual properties such as orientation and contrast. Does this same learning characterize more complex perceptual skills? Here we investigated perceptual learning of complex medical images. Novices underwent training over four sessions to discriminate which of two chest radiographs contained a tumor and to indicate the location of the tumor. In training, one group received six repetitions of 30 normal/abnormal images, the other three repetitions of 60 normal/abnormal images. Groups were then tested on trained and novel images. To assess the nature of perceptual learning, test items were presented in three formats – the full image, the cutout of the tumor, or the background only. Performance improved across training sessions, and notably, the improvement transferred to the classification of novel images. Training with more repetitions on fewer images yielded comparable transfer to training with fewer repetitions on more images. Little transfer to novel images occurred when tested with just the cutout of the cancer region or just the background, but a larger cutout that included both the cancer region and some surrounding regions yielded good transfer. Perceptual learning contributes to the acquisition of expertise in cancer image perception.

Redundancy gain in visual search of simulated X-ray images

Cancer diagnosis frequently relies on the interpretation of medical images such as chest X-rays and mammography. This process is error prone; misdiagnoses can reach a rate of 15% or higher. Of particular interest are false negatives-tumors that are present but missed. Previous research has identified several perceptual and attentional problems underlying inaccurate perception of these images. But how might these problems be reduced? The psychological literature has shown that presenting multiple, duplicate images can improve performance. Here we explored whether redundant image presentation can improve target detection in simulated X-ray images, by presenting four identical or similar images concurrently. Displays with redundant images, including duplicates of the same image, showed reduced false-negative rates, compared with displays with a single image. This effect held both when the target's prevalence rate was high and when it was low. Eye tracking showed that fixating on two or more images in the redundant condition speeded target detection and prolonged search, and that the latter effect was the key to reducing false negatives. The redundancy gain may result from both perceptual enhancement and an increase in the search quitting threshold.