Tracking Bias: Using Eye-Tracking To Measure The Effects Of Cognitive Control In Hiring Situations

The use of social media websites such as Facebook, LinkedIn, and Twitter is becoming increasingly popular in both academic and professional research settings. While they are a valuable tool, many have raised ethical concerns about the access to protected class information such as race, gender, and sexual orientation. Although access to this information through a social media page is legal, the use of these discriminatory factors in hiring situations is an illegal and unethical practice. Little research has been done on how to mitigate the effects of biases formed from these factors. The current study used eye-tracking technology to investigate whether a cognitive control message can affect people’s ability to control what they look at during a simulated hiring situation. Overall, I found evidence consistent with the use of cognitive control in simulated hiring situations as seen by fewer fixations on average less frequent average fixations and shorter fixation durations to target words as well as to the profile picture and biographical information section of the profiles. Individuals given a cognitive control inducing message exhibited patterns of oculomotor behavior consistent with the use of cognitive control using top-down information to reduce but not completely prevent fixations to protected class information contained within the profiles

Understanding visual behaviour within the urban environment to optimise lighting

A review of the literature suggests that current guidelines for road lighting lack a clear empirical basis. Where there is evidence, this tends to be based on motorists or pedestrians: there is little, if any, consideration given to the needs of cyclists. This thesis presents an investigation of lighting for cycling after dark within an urban environment. Three empirical investigations were conducted. A field survey was conducted to investigate the influence of the ambient light level on the tendency to cycle. Mobile eye-tracking was used to investigate the gaze behaviour of cyclists in natural settings, using two parallel measurements to reveal the critical of these fixations: performance on an audio dual-task and skin conductance response (SCR), and by that improved the ecological validity of previous similar research. A laboratory experiment was conducted to investigate obstacle detection under variations in the type, location, and level of lighting. The field study revealed that cycling increases when the ambient light level is higher. This suggests that road lighting might be a tool to encourage more cycling. The eye-tracking study suggested that observing the path ahead is a critical task, reflecting a tendency to search for possible obstacles on the road. Post hoc analysis of the eye-tracking data also suggested an influence of ambient light level on gaze towards aesthetic elements (architectural features) of the environment with such elements are suggested by the literature to be associated with positive cycling experience: this suggests that appropriate road lighting motivates the choice to cycle. The detection experiment revealed two significant effects: first; that road lighting and bicycle lighting may conflict. In other words, using bicycle lighting on a lit road may impair detection performance, not improve it. Second; that detection is improved when the front bicycle lamp is located on the wheel hub rather than the handlebar

The impact of sound in people's behaviour in outdoor settings: A study using virtual reality and eye-tracking

This paper presents an analysis of space perception and how visual cues, such as landmarks and sound, are perceived and impact people's behaviour while exploring a given outdoor space. The primary goal of the research is to investigate how auditory sensations and visual stimuli influence people's behaviour in outdoor built environments. Our technique compares people's perception of the built environment in different conditions: the real world and a replicated virtual world. As a case study, a university campus was used, and four experimental conditions were designed. The study followed a between-subjects design, and the data collection included gaze data acquired from an eye-tracking device as well as self-reports. The study concludes that sound influences human behaviour in such settings. More specifically conclusions are that: i) human behaviour in virtual replications of the real space, including both visual and sound stimuli, is tendentially more similar to human behaviour in the real world than in simulations omitting sound; and ii) there is a difference in human behaviour when people explore the same virtually replicated outdoor space, by varying the presence of sound. This study is particularly useful for researchers working on the comparison between human behaviour in virtual and real environments, related to visual and sound stimuli.info:eu-repo/semantics/publishedVersio

Modelling the interpretation of digital mammography using high order statistics and deep machine learning

Visual search is an inhomogeneous, yet efficient sampling process accomplished by the saccades and the central (foveal) vision. Areas that attract the central vision have been studied for errors in interpretation of medical images. In this study, we extend existing visual search studies to understand features of areas that receive direct visual attention and elicit a mark by the radiologist (True and False Positive decisions) from those that elicit a mark but were captured by the peripheral vision. We also investigate if there are any differences between these areas and those that are never fixated by radiologists. Extending these investigations, we further explore the possibility of modelling radiologists’ search behavior and their interpretation of mammograms using deep machine learning techniques. We demonstrated that energy profiles of foveated (FC), peripherally fixated (PC), and never fixated (NFC) areas are distinct. It was shown that FCs are selected on the basis of being most informative. Never fixated regions were found to be least informative. Evidences that energy profiles and dwell time of these areas influence radiologists’ decisions (and confidence in such decisions) were also shown. High-order features provided additional information to the radiologists, however their effect on decision (and confidence in such decision) was not significant. We also showed that deep-convolution neural network can successfully be used to model radiologists’ attentional level, decisions and confidence in their decisions. High accuracy and high agreement (between true and predicted values) in such predictions can be achieved in modelling attentional level (accuracy: 0.90, kappa: 0.82) and decisions (accuracy: 0.92, kappa: 0.86) of radiologists. Our results indicated that an ensembled model for radiologist’s search behavior and decision can successfully be built. Convolution networks failed to model missed cancers however

Performance Validity Assessment Of Bona Fide And Malingered Traumatic Brain Injury Using Novel Eye-Tracking Systems

Purposeful presentation of neurocognitive impairment (i.e., dissimulation) in assessment of brain injury is a primary pitfall to accurate psychological assessment, especially among individuals seeking compensation. Current methods used to evaluate effort test failure (EFT; Webb et al., 2012) and dissimulation in brain injury assessment has advanced over the past few decades, but remains unacceptably inaccurate. In diagnostic decision-making, current methods identify obvious cases of purposefully poor performance, but they are considerably less accurate in subtle cases typically seen clinically; more important, they are vulnerable to coaching. Oculomotor behavior during visual tasks may be a promising avenue in the assessment of performance validity. Oculomotor patterns observed after brain injury have been well documented, and patterns characteristic of normal decision-making have been studied in healthy adults, but findings from these endeavors have not been applied to performance validity assessment. Accordingly, this study evaluated contributions of oculomotor patterns to detection of purposeful poor performance using state-of-the-science eye-tracking equipment by studying the predictive ability of a gold-standard performance validity test: The Test of Memory Malingering (TOMM). The study examined 39 adults with moderate to severe traumatic brain injury (TBI), 42 healthy adults coached to simulate memory impairment (SIM), and 50 healthy adults providing full effort (HC). The results supported the main hypothesis: One index derived using oculomotor patterns of performance provided a reliable increase to the predicative accuracy of the TOMM in differentiating bona fide TBI from simulated TBI. Numerous other oculomotor indexes showed promise, both in their relationships to key cognitive constructs and in their ability to differentiate dissimulation from healthy adults and bona fide TBI. The predicative ability of these measures was insignificant, however, due to an underpowered sample size and violations of the assumptions of pivotal statistical models. As such, future research is needed to replicate these findings and should strive to increase sample sizes to more accurately assess those visual patterns that showed predictive potential

Eye-Tracking in Interactive Virtual Environments: Implementation and Evaluation

Not all eye-tracking methodology and data processing are equal. While the use of eye-tracking is intricate because of its grounding in visual physiology, traditional 2D eye-tracking methods are supported by software, tools, and reference studies. This is not so true for eye-tracking methods applied in virtual reality (imaginary 3D environments). Previous research regarded the domain of eye-tracking in 3D virtual reality as an untamed realm with unaddressed issues. The present paper explores these issues, discusses possible solutions at a theoretical level, and offers example implementations. The paper also proposes a workflow and software architecture that encompasses an entire experimental scenario, including virtual scene preparation and operationalization of visual stimuli, experimental data collection and considerations for ambiguous visual stimuli, post-hoc data correction, data aggregation, and visualization. The paper is accompanied by examples of eye-tracking data collection and evaluation based on ongoing research of indoor evacuation behavior

Change blindness: eradication of gestalt strategies

Arrays of eight, texture-defined rectangles were used as stimuli in a one-shot change blindness (CB) task where there was a 50% chance that one rectangle would change orientation between two successive presentations separated by an interval. CB was eliminated by cueing the target rectangle in the first stimulus, reduced by cueing in the interval and unaffected by cueing in the second presentation. This supports the idea that a representation was formed that persisted through the interval before being 'overwritten' by the second presentation (Landman et al, 2003 Vision Research 43149–164]. Another possibility is that participants used some kind of grouping or Gestalt strategy. To test this we changed the spatial position of the rectangles in the second presentation by shifting them along imaginary spokes (by ±1 degree) emanating from the central fixation point. There was no significant difference seen in performance between this and the standard task [F(1,4)=2.565, p=0.185]. This may suggest two things: (i) Gestalt grouping is not used as a strategy in these tasks, and (ii) it gives further weight to the argument that objects may be stored and retrieved from a pre-attentional store during this task