21 research outputs found
Assessing Graphical Robot Aids for Interactive Co-working
The shift towards more collaborative working between humans and robots increases the need for improved interfaces. Alongside robust measures to ensure safety and task performance, humans need to gain the confidence in robot co-operators to enable true collaboration. This research investigates how graphical signage can support human–robot co-working, with the intention of increased productivity. Participants are required to co-work with a KUKA iiwa lightweight manipulator on a manufacturing task. The three conditions in the experiment differ in the signage presented to the participants – signage relevant to the task, irrelevant to the task, or no signage. A change between three conditions is expected in anxiety and negative attitudes towards robots; error rate; response time; and participants’ complacency, suggested by facial expressions. In addition to understanding how graphical languages can support human–robot co-working, this study provides a basis for further collaborative research to explore human–robot co-working in more detail
Language-free graphical signage improves human performance and reduces anxiety when working collaboratively with robots
As robots become more ubiquitous, and their capabilities extend, novice users will require intuitive instructional information related to their use. This is particularly important in the manufacturing sector, which is set to be transformed under Industry 4.0 by the deployment of collaborative robots in support of traditionally low-skilled, manual roles. In the first study of its kind, this paper reports how static graphical signage can improve performance and reduce anxiety in participants physically collaborating with a semi-autonomous robot. Three groups of 30 participants collaborated with a robot to perform a manufacturing-type process using graphical information that was relevant to the task, irrelevant, or absent. The results reveal that the group exposed to relevant signage was significantly more accurate in undertaking the task. Furthermore, their anxiety towards robots significantly decreased as a function of increasing accuracy. Finally, participants exposed to graphical signage showed positive emotional valence in response to successful trials. At a time when workers are concerned about the threat posed by robots to jobs, and with advances in technology requiring upskilling of the workforce, it is important to provide intuitive and supportive information to users. Whilst increasingly sophisticated technical solutions are being sought to improve communication and confidence in human-robot co-working, our findings demonstrate how simple signage can still be used as an effective tool to reduce user anxiety and increase task performance
Alcohol consumers’ attention to warning labels and brand information on alcohol packaging: Findings from cross-sectional and experimental studies
Background
Alcohol warning labels have a limited effect on drinking behavior, potentially because people devote minimal attention to them. We report findings from two studies in which we measured the extent to which alcohol consumers attend to warning labels on alcohol packaging, and aimed to identify if increased attention to warning labels is associated with motivation to change drinking behavior.
Methods
Study 1 (N = 60) was an exploratory cross-sectional study in which we used eye-tracking to measure visual attention to brand and health information on alcohol and soda containers. In study 2 (N = 120) we manipulated motivation to reduce drinking using an alcohol brief intervention (vs control intervention) and measured heavy drinkers’ attention to branding and warning labels with the same eye-tracking paradigm as in study 1. Then, in a separate task we experimentally manipulated attention by drawing a brightly colored border around health (or brand) information before measuring participants’ self-reported drinking intentions for the subsequent week.
Results
Study 1 showed that participants paid minimal attention to warning labels (7% of viewing time). Participants who were motivated to reduce drinking paid less attention to alcohol branding and alcohol warning labels. Results from study 2 showed that the alcohol brief intervention decreased attention to branding compared to the control condition, but it did not affect attention to warning labels. Furthermore, the experimental manipulation of attention to health or brand information did not influence drinking intentions for the subsequent week.
Conclusions
Alcohol consumers allocate minimal attention to warning labels on alcohol packaging and even if their attention is directed to these warning labels, this has no impact on their drinking intentions. The lack of attention to warning labels, even among people who actively want to cut down, suggests that there is room for improvement in the content of health warnings on alcohol packaging
Dynamic Graphical Signage Improves Response Time and Decreases Negative Attitudes towards Robots in Human-Robot Co-working
Collaborative robots, or ‘co-bots’, are a transformational technology that bridge traditionally segregated manual and automated manufacturing processes. However, to realize its full potential, human operators need confidence in robotic co-worker technologies and their capabilities. In this experiment we investigate the impact of screen-based dynamic instructional signage on 39 participants from a manufacturing assembly line. The results provide evidence that dynamic signage helps to improve response time for the experimental group with task-relevant signage compared to the control group with no signage. Furthermore, the experimental group’s negative attitudes towards robots decreased significantly with increasing accuracy on the task
Quantifying Age-Related Differences in Information Processing Behaviors When Viewing Prescription Drug Labels
Adverse drug events (ADEs) are a significant problem in health care. While effective warnings have the potential to reduce the prevalence of ADEs, little is known about how patients access and use prescription labeling. We investigated the effectiveness of prescription warning labels (PWLs, small, colorful stickers applied at the pharmacy) in conveying warning information to two groups of patients (young adults and those 50+). We evaluated the early stages of information processing by tracking eye movements while participants interacted with prescription vials that had PWLs affixed to them. We later tested participants’ recognition memory for the PWLs. During viewing, participants often failed to attend to the PWLs; this effect was more pronounced for older than younger participants. Older participants also performed worse on the subsequent memory test. However, when memory performance was conditionalized on whether or not the participant had fixated the PWL, these age-related differences in memory were no longer significant, suggesting that the difference in memory performance between groups was attributable to differences in attention rather than differences in memory encoding or recall. This is important because older adults are recognized to be at greater risk for ADEs. These data provide a compelling case that understanding consumers’ attentive behavior is crucial to developing an effective labeling standard for prescription drugs
All models are wrong, some are useful, but are they reproducible? Commentary on Lee et al. (2019)
Lee et al. (2019) make several practical recommendations for replicable and useful cognitive modeling. They also point out that the ultimate test of the usefulness of a cognitive model is its ability to solve practical problems. Solution-oriented modeling requires engaging practitioners who understand the relevantly applied domain but may lack extensive modeling expertise. In this commentary, we argue that for cognitive modeling to reach practitioners, there is a pressing need to move beyond providing the bare minimum information required for reproducibility and instead aim for an improved standard of transparency and reproducibility in cognitive modeling research. We discuss several mechanisms by which reproducible research can foster engagement with applied practitioners. Notably, reproducible materials provide a starting point for practitioners to experiment with cognitive models and evaluate whether they are suitable for their domain of expertise. This is essential because solving complex problems requires exploring a range of modeling approaches, and there may not be time to implement each possible approach from the ground up. Several specific recommendations for best practice are provided, including the application of containerization technologies. We also note the broader benefits of adopting gold standard reproducible practices within the field