Forgiveness in The Arab and Islamic Contexts

This essay explores the current and historical meaning of forgiveness in Arab and Islamic cultural and religious contexts. It also hopes to encourage further empirical research on this understudied topic in both religious and peacebuilding studies. In addition to the perceived meaning of forgiveness in an Arab Islamic context, this essay examines the links between forgiveness and reconciliation. Relying on religious sources including the Qur'an and Hadith, as well as certain events in Islamic history, the essay identifies various ways to conceptualize and explain the meaning of forgiveness. This theoretical and conceptual segment is followed by a section which explores current perceptions of forgiveness among Arab Muslim teachers in five different communities. The empirical data for this analysis is based on a larger comparative regional study that has been completed through surveys and structured interviews with educators from Lebanon, Jordan, Egypt, and Palestinians from the West Bank and Israel. Our study concluded that the teachers' perceptions of forgiveness were mainly derived from religious sources and identities and that Islamic religious discourse provided a solid foundation for framing the meaning of forgiveness.     

Cognitive guidelines for simplifying medical information: Data framing and perception

In this paper, 1 describe psychological guidelines for simplifying medical information — methods to aid the perception and recognition of abnormalities in medical test reports. These techniques resemble natural human editing strategies outlined in prospect theory. The methods pre-edit data as humans do but to reduce human effort. I review empirical studies assessing these techniques and discuss needs for further research.     

Calibration of probability assessments by professional blackjack dealers, statistical experts, and lay people

The question addressed in this study is whether experts are better calibrated than lay people. We investigated how well people are calibrated when they assess the probabilities of card combinations in the game of blackjack. Three groups of subjects were used: professional dealers, statistical experts, and control subjects. The results showed that experience and statistical expertise do not make people better calibrated in this task. It is argued that the concept of calibration is not wholly appropriate to describe the obtained deviations from the normatively correct responses. This is illustrated by a discriminant analysis performed on the signed deviation scores, which resulted in an almost perfect separation of the three groups, although they were overlapping with respect to calibration.     

Towards a model of stress and human performance

An outline is presented of a model that aims to relate energetical and structural mechanisms of human information processing and to incorporate an interactionally defined stress notion in performance research. The first section summarizes objections to unidimensional notions of arousal and stress. It is concluded that further progress requires the analysis of joint cognitive-energetical processing structures. In the second section two current performance models - in terms of linear stages and resources - are briefly reviewed. Despite a number of problems and objections, it is decided to base the model upon linear stage notions of information processing. This is further elaborated in the third section. In accord with Pribram and McGuinness (1975) three energetical supply systems are proposed which are selectively related to specific cognitive processing mechanisms. Stress is defined as a state of imbalance in the energetical supply which is difficult to restore or to compensate. The final section is devoted to the discussion of some lines of evidence and to suggestions for future research.     

Autonomous vehicle safety: Understanding perceptions of pedestrians and bicyclists

Autonomous vehicle (AV) technologies have been rapidly advancing. One benefit of AVs is that the technology could eliminate many driver errors and also mitigate many pedestrian and bicyclist collisions. Real-world AVs have been tested in many cities. Five companies are running around 50 AVs in Pittsburgh, following the autonomous testing guidelines. BikePGH, a non-profit organization located in Pittsburgh, Pennsylvania conducted a follow-up survey in 2019 (the first survey was conducted in 2017) to understand non-motorists’ opinions of AVs. This study examined how pedestrians and bicyclists perceived AV safety based on their understanding and experiences. At first, this study performed a comparison group test to determine which questions vary by participants’ AV safety rating. The responses were later analyzed with a data mining method known as ‘association rules mining.’ A new performance measure, known as the rule power factor, was then used to identify the significant patterns in the form of rules. The participants also provided their thoughts in responses to the open-ended questions. Using Latent Dirichlet Allocation (LDA), a topic modeling algorithm, 40 topic models were developed based on five open-ended questions. The findings show that the non-motorists showed comparatively fewer negative opinions towards AVs than positive assessments. The results also show that perception patterns vary by the participant’s rating on AV safety. Findings of this study would be beneficial for the AV stakeholders in making AVs and roadways safer for non-motorists.     

Evaluating driver comprehension of the roadway environment to retain accountability of safety during driving automation

Driver comprehension is a substantial component of situation awareness that involves the ability of an individual to understand the significance of an object, traffic sign, or hazard while driving. An increase in crashes related to autonomous driving systems has raised a concern regarding the safety of other roadway users due to the diminishing accountability resulting from a general lack of understanding of the limitations or disregard of the safety protocols by users. To keep drivers vigilant when engaged in partial automated systems, a methodology to monitor real-time driver comprehension was proposed. A driving simulator study consisting of 90 participants, equally split between males and females, was executed to establish driver comprehension in six different variations of driving difficulty. Joint probability density functions were created by considering percent time spent gazing, answers to probe questions, and driving performance. Based on these density functions, five levels of comprehension were devised and assigned thresholds. Overall, as task difficulty increased, a non-linear deterioration in driving speed along with an increase in total gaze duration was observed before comprehension was attained. A two-step validation protocol was also proposed to ensure similar levels of comprehension to non-automated driving from the human driver, when engaged in early forms of automation. The proposed real-time driver comprehension monitoring constitutes a first step toward developing a methodology to reinstate the accountability of safety of other roadway users when engaged in driver-in-the-loop automation systems.     

An expanded model for perceptual visual single object recognition system using expectation priming following neuroscientific evidence

Under numerous circumstances, humans recognize visual objects in their environment with remarkable response times and accuracy. Existing artificial visual object recognition systems have not yet surpassed human vision, especially in its universality of application. We argue that modeling the recognition process in an exclusive feedforward manner hinders those systems’ performance. To bridge that performance gap between them and human vision, we present a brief review of neuroscientific data, which suggests that considering an agent’s internal influences (from cognitive systems that peripherally interact with visual-perceptual processes) recognition can be improved. Then, we propose a model for visual object recognition which uses these systems’ information, such as affection, for generating expectation to prime the object recognition system, thus reducing its execution times. Later, an implementation of the model is described. Finally, we present and discuss an experiment and its results.     

Direct social perception of others’ subjective time

In this paper, I deploy Gallagher et al.’s theory of Direct Social Perception (DSP) to help explain how we perceive others’ subjective time. This process of second-person temporal perception plays an important role in interpersonal interaction, yet is often glossed over in discussions of intersubjectivity. Using A.D. Craig (2009) ‘awareness’ model of subjective time to unify converging evidence that subjective time is embodied, affective, and situated, I argue that subjective time cannot be considered as a hidden or invisible aspect of a private mind, but is partially externally visible through our gestures, expressions, and other behaviours as they unfold within a particular context. My central thesis is that, in face to face interactions, we are able to directly perceive these visible components of other people’s subjective time. This is made possible by our “enculturated” (Menary, 2015) and enactive perceptual faculties. The process of social perception is not a passive, unidirectional affair where static information about one person’s subjective time is transmitted to the other, but rather inextricably linked with action (both at the personal and subpersonal level) and interaction effects produced by a dynamic coupling between participants. Such an enactive perspective reveals how others’ subjective time can be perceived in everyday interactions.     

Flexing Gender Perception: Brain Potentials Reveal the Cognitive Permeability of Grammatical Information

A growing body of recent research suggests that verbal categories, particularly labels, impact categorization and perception. These findings are commonly interpreted as demonstrating the involvement of language on cognition; however, whether these assumptions hold true for grammatical structures has yet to be investigated. In the present study, we investigated the extent to which linguistic information, namely, grammatical gender categories, structures cognition to subsequently influence categorical judgments and perception. In a nonverbal categorization task, French–English bilinguals and monolingual English speakers made gender-associated judgments about a set of image pairs while event-related potentials were recorded. The image sets were composed of an object paired with either a female or male face, wherein the object was manipulated for their conceptual gender relatedness and grammatical gender congruency to the sex of the following target face. The results showed that grammatical gender modulated the N1 and P2/VPP, as well as the N300 exclusively for the French–English bilinguals, indicating the inclusion of language in the mechanisms associated with attentional bias and categorization. In contrast, conceptual gender information impacted the monolingual English speakers in the later N300 time window given the absence of a comparable grammatical feature. Such effects of grammatical categories in the early perceptual stream have not been found before, and further provide grounds to suggest that language shapes perception.