New paradigmatic orientations and research agenda of human factors science in the intelligence era

Our recent research shows that the design philosophy of human factors science in the intelligence age is expanding from "user-centered design" to "human-centered AI". The human-machine relationship presents a trans-era evolution from "human-machine interaction" to "human-machine/AI teaming". These changes have raised new questions and challenges for human factors science. The interdisciplinary field of human factors science includes any work that adopts a human-centered approach, such as human factors, ergonomics, engineering psychology, and human-computer interaction. These changes compel us to re-examine current human factors science's paradigms and research agenda. Existing research paradigms are primarily based on non-intelligent technologies. In this context, this paper reviews the evolution of the paradigms of human factors science. It summarizes the new conceptual models and frameworks we recently proposed to enrich the research paradigms for human factors science, including a human-AI teaming model, a human-AI joint cognitive ecosystem framework, and an intelligent sociotechnical systems framework. This paper further enhances these concepts and looks forward to the application of these concepts. This paper also looks forward to the future research agenda of human factors science in the areas of "human-AI interaction", "intelligent human-machine interface", and "human-AI teaming". It analyzes the role of the research paradigms on the future research agenda. We believe that the research paradigms and agenda of human factors science influence and promote each other. Human factors science in the intelligence age needs diversified and innovative research paradigms, thereby further promoting the research and application of human factors science.Comment: 26 pages, in Chinese languag

Two faces of the other-race effect: Recognition and categorisation of Caucasian and Chinese faces

The other-race effect is a collection of phenomena whereby faces of one's own race are processed differently from those of other races. Previous studies have revealed a paradoxical mirror pattern of an own-race advantage in face recognition and an other-race advantage in race-based categorisation. With a well-controlled design, we compared recognition and categorisation of own-race and other-race faces in both Caucasian and Chinese participants. Compared with own-race faces, other-race faces were less accurately and more slowly recognised, whereas they were more rapidly categorised by race. The mirror pattern was confirmed by a unique negative correlation between the two effects in terms of reaction time with a hierarchical regression analysis. This finding suggests an antagonistic interaction between the processing of face identity and that of face category, and a common underlying processing mechanism

Culture Shapes Efficiency of Facial Age Judgments

Background: Cultural differences in socialization can lead to characteristic differences in how we perceive the world. Consistent with this influence of differential experience, our perception of faces (e.g., preference, recognition ability) is shaped by our previous experience with different groups of individuals. Methodology/Principal Findings: Here, we examined whether cultural differences in social practices influence our perception of faces. Japanese, Chinese, and Asian-Canadian young adults made relative age judgments (i.e., which of these two faces is older?) for East Asian faces. Cross-cultural differences in the emphasis on respect for older individuals was reflected in participants ’ latency in facial age judgments for middle-age adult faces—with the Japanese young adults performing the fastest, followed by the Chinese, then the Asian-Canadians. In addition, consistent with the differential behavioural and linguistic markers used in the Japanese culture when interacting with individuals younger than oneself, only the Japanese young adults showed an advantage in judging the relative age of children’s faces. Conclusions/Significance: Our results show that different sociocultural practices shape our efficiency in processing facia

Three-month-olds, but not newborns, prefer own-race faces

Adults are sensitive to the physical differences that define ethnic groups. However, the age at which we become sensitive to ethnic differences is currently unclear. Our study aimed to clarify this by testing newborns and young infants for sensitivity to ethnicity using a visual preference (VP) paradigm. While newborn infants demonstrated no spontaneous preference for faces from either their own- or other-ethnic groups, 3-month-old infants demonstrated a significant preference for faces from their own-ethnic group. These results suggest that preferential selectivity based on ethnic differences is not present in the first days of life, but is learned within the first 3 months of life. The findings imply that adults’ perceptions of ethnic differences are learned and derived from differences in exposure to own- versus other-race faces during early developmen

An inner face advantage in children’s recognition of familiar peers

Children’s recognition of familiar own-age peers was investigated. Chinese children (4-, 8-, and 14-year-olds) were asked to identify their classmates from photographs showing the entire face, the internal facial features only, the external facial features only, or the eyes, nose, or mouth only. Participants from all age groups were familiar with the faces used as stimuli for 1 academic year. The results showed that children from all age groups demonstrated an advantage for recognition of the internal facial features relative to their recognition of the external facial features. Thus, previous observations of a shift in reliance from external to internal facial features can be attributed to experience with faces rather than to age-related changes in face processing

Providing depth information in the display for pursuit and compensatory tracking and optimization in 3‐D space

Objective The formats of tracking displays exert important influences on tracking performance. Few previous studies explored the 3‐D tracking display formats. The present study aimed to construct the 3‐D formats for the manual pursuit and compensatory tracking displays by adding the depth information. Based on the results of tracking performance, we further optimized the preferable tracking format. Method Three experiments were conducted. Experiment 1 was a confirmatory experiment to compare the effects of the two display formats on 2‐D manual tracking performance with previous studies. Experiment 2 extended the investigation to a 3‐D display by adding a depth cue indicating the relative size of the control marker and target. Experiment 3 was an optimisation experiment in which an improved 3‐D tracking display was modified, i.e., an extra depth cue was complemented to clearly signify the relative position of the target and the control marker. Results Pursuit tracking performance was better than compensatory tracking performance in both 2‐D (Experiment 1) and 3‐D space (Experiment 2). It also found that the extra depth cue significantly improved the tracking success rate and the subjective satisfaction of the pursuit display format in 3‐D space (Experiment 3). Conclusions These findings indicated that the depth cues could be used in tracking display in 3‐D space and have important implications for the design of some motor training and tracking systems

Eye tracking reveals a crucial role for facial motion in recognition of faces by infants.

International audienceCurrent knowledge about face processing in infancy comes largely from studies using static face stimuli, but faces that infants see in the real world are mostly moving ones. To bridge this gap, 3-, 6-, and 9-month-old Asian infants (N ! 118) were familiarized with either moving or static Asian female faces, and then their face recognition was tested with static face images. Eye-tracking methodology was used to record eye movements during the familiarization and test phases. The results showed a developmental change in eye movement patterns, but only for the moving faces. In addition, the more infants shifted their fixations across facial regions, the better their face recognition was, but only for the moving faces. The results suggest that facial movement influences the way faces are encoded from early in development