Great expectations: minor differences in initial instructions have a major impact on visual search in the absence of feedback

Centering cognitive neuroscience on task demands and generalization

Cognitive neuroscience seeks generalizable theories explaining the relationship between behavioral, physiological and mental states. In pursuit of such theories, we propose a theoretical and empirical framework that centers on understanding task demands and the mutual constraints they impose on behavior and neural activity. Task demands emerge from the interaction between an agent's sensory impressions, goals and behavior, which jointly shape the activity and structure of the nervous system on multiple spatiotemporal scales. Understanding this interaction requires multitask studies that vary more than one experimental component (for example, stimuli and instructions) combined with dense behavioral and neural sampling and explicit testing for generalization across tasks and data modalities. By centering task demands rather than mental processes that tasks are assumed to engage, this framework paves the way for the discovery of new generalizable concepts unconstrained by existing taxonomies, and moves cognitive neuroscience toward an action-oriented, dynamic and integrated view of the brain.

Cue relevance drives early quitting in visual search

Irrelevant salient distractors can trigger early quitting in visual search, causing observers to miss targets they might otherwise find. Here, we asked whether task-relevant salient cues can produce a similar early quitting effect on the subset of trials where those cues fail to highlight the target. We presented participants with a difficult visual search task and used two cueing conditions. In the high-predictive condition, a salient cue in the form of a red circle highlighted the target most of the time a target was present. In the low-predictive condition, the cue was far less accurate and did not reliably predict the target (i.e., the cue was often a false positive). These were contrasted against a control condition in which no cues were presented. In the high-predictive condition, we found clear evidence of early quitting on trials where the cue was a false positive, as evidenced by both increased miss errors and shorter response times on target absent trials. No such effects were observed with low-predictive cues. Together, these results suggest that salient cues which are false positives can trigger early quitting, though perhaps only when the cues have a high-predictive value. These results have implications for real-world searches, such as medical image screening, where salient cues (referred to as computer-aided detection or CAD) may be used to highlight potentially relevant areas of images but are sometimes inaccurate.

Familiarity with ChatGPT Features Modifies Expectations and Learning Outcomes of Dental Students

OBJECTIVES

The number of approvals for AI-based systems is increasing rapidly, although AI clinical trial designs lack consideration of the impact of human-AI interaction. Aim of this work was to investigate how reading of an AI system (ChatGPT) features/descriptions could influence the willingness and expectations for use of this technology as well as dental students' learning performance.

METHODS

Dental students (N = 104) were asked to learn about side effects of drugs used in dental practice via reading recommended literature or ChatGPT. Expectations towards ChatGPT were measured by survey, before and after reading of a system features description, whilst learning outcomes were evaluated via pharmacology quiz.

RESULTS

Students who used ChatGPT (YG group) showed better results on the pharmacology quiz than students who neither read the description nor employed ChatGPT for learning (NN condition). Moreover, students who read the description of ChatGPT features yet did not use it (NG) showed better results on the pharmacology quiz compared with the NN condition, although none of them employed ChatGPT for learning. The NG students compared to the YG students had less trust in AI system assistance in learning, and after the AI system description reading, their expectations changed significantly, showing an association with quiz scores.

CONCLUSIONS

A majority of students in our cohort was reluctant to use ChatGPT. Furthermore, familarity (reading) with ChatGPT features appear to alter the expectations and enhance learning performance of students.suggesting an AI description-related cognitive bias. Hence the content description of ChatGPTshould be reviewed and verified prior to AI system use for educational purposes.

Emphasizing responder speed or accuracy modulates but does not abolish the distractor-induced quitting effect in visual search

When a highly salient distractor is present in a search array, it speeds target absent visual search and increases errors during target present visual search, suggesting lowered quitting thresholds (Moher in Psychol Sci 31(1):31-42, 2020). Missing a critical target in the presence of a highly salient distractor can have dire consequences in real-world search tasks where accurate target detection is crucial, such as baggage screening. As such, the current study examined whether emphasizing either accuracy or speed would eliminate the distractor-generated quitting threshold effect (QTE). Three blocks of a target detection search task which included a highly salient distractor on half of all trials were used. In one block, participants received no instructions or feedback regarding performance. In the remaining two blocks, they received instructions and trial-by-trial feedback that either emphasized response speed or response accuracy. Overall, the distractor lowered quitting thresholds, regardless of whether response speed or response accuracy was emphasized in a block of trials. However, the effect of the distractor on target misses was smaller when accuracy was emphasized. It, therefore, appears that while the distractor QTE is not easily eradicated by explicit instructions and feedback, it can be shifted. As such, future research should examine the applicability of these and similar strategies in real-world search scenarios.

Framing the fallibility of Computer-Aided Detection aids cancer detection

Computer-Aided Detection (CAD) has been proposed to help operators search for cancers in mammograms. Previous studies have found that although accurate CAD leads to an improvement in cancer detection, inaccurate CAD leads to an increase in both missed cancers and false alarms. This is known as the over-reliance effect. We investigated whether providing framing statements of CAD fallibility could keep the benefits of CAD while reducing over-reliance. In Experiment 1, participants were told about the benefits or costs of CAD, prior to the experiment. Experiment 2 was similar, except that participants were given a stronger warning and instruction set in relation to the costs of CAD. The results showed that although there was no effect of framing in Experiment 1, a stronger message in Experiment 2 led to a reduction in the over-reliance effect. A similar result was found in Experiment 3 where the target had a lower prevalence. The results show that although the presence of CAD can result in over-reliance on the technology, these effects can be mitigated by framing and instruction sets in relation to CAD fallibility.

The effect of pre-event instructions on eyewitness identification

Research on eyewitness identification often involves exposing participants to a simulated crime and later testing memory using a lineup. We conducted a systematic review showing that pre-event instructions, instructions given before event exposure, are rarely reported and those that are reported vary in the extent to which they warn participants about the nature of the event or tasks. At odds with the experience of actual witnesses, some studies use pre-event instructions explicitly warning participants of the upcoming crime and lineup task. Both the basic and applied literature provide reason to believe that pre-event instructions may affect eyewitness identification performance. In the current experiment, we tested the impact of pre-event instructions on lineup identification decisions and confidence. Participants received non-specific pre-event instructions (i.e., "watch this video") or eyewitness pre-event instructions (i.e., "watch this crime video, you'll complete a lineup later") and completed a culprit-absent or -present lineup. We found no support for the hypothesis that participants who receive eyewitness pre-event instructions have higher discriminability than participants who receive non-specific pre-event instructions. Additionally, confidence-accuracy calibration was not significantly different between conditions. However, participants in the eyewitness condition were more likely to see the event as a crime and to make an identification than participants in the non-specific condition. Implications for conducting and interpreting eyewitness identification research and the basic research on instructions and attention are discussed.

How one block of trials influences the next: persistent effects of disease prevalence and feedback on decisions about images of skin lesions in a large online study

Using an online, medical image labeling app, 803 individuals rated images of skin lesions as either "melanoma" (skin cancer) or "nevus" (a skin mole). Each block consisted of 80 images. Blocks could have high (50%) or low (20%) target prevalence and could provide full, accurate feedback or no feedback. As in prior work, with feedback, decision criteria were more conservative at low prevalence than at high prevalence and resulted in more miss errors. Without feedback, this low prevalence effect was reversed (albeit, not significantly). Participants could participate in up to four different conditions a day on each of 6 days. Our main interest was in the effect of Block N on Block N + 1. Low prevalence with feedback made participants more conservative on a subsequent block. High prevalence with feedback made participants more liberal on a subsequent block. Conditions with no feedback had no significant impact on the subsequent block. The delay between Blocks 1 and 2 had no significant effect. The effect on the second half of Block 2 was just as large as on the first half. Medical expertise (over the range available in the study) had no impact on these effects, though medical students were better at the task than other groups. Overall, these seem to be robust effects where feedback may be 'teaching' participants how to respond in the future. This might have application in, for example, training or re-training situations.