Intentional response distortion during the COVID-19 pandemic

COVID-19 has abruptly and unexpectedly transformed nearly every aspect of work, including but not limited to increased unemployment rates and uncertainty regarding future job prospects. Response distortion has always been a concern given that many organizations rely on information that is self-reported by applicants regarding their potential employability (e.g., responses to self-reported personality instruments, resumes, interview responses). Drawing from the Valence-Instrumentality-Expectancy (VIE) theory of motivation, we propose that the uncertainty surrounding jobs may lead to amplified distorted responses on these measures in areas where COVID-19 was most salient. In a sample of 213 working adults [~50% female, age M = 38.48], the present study shows that increases in response distortion on a measure of conscientiousness were more pronounced as a function of (a) local COVID positivity rates and (b) job type, such that frontline workers distorted their responses the most. Findings are discussed in the context of VIE theory, personality measurement, and challenges with maintaining effective selection procedures.     

Minds and Bodies: Human and Divine

Does God have a mind? Western theism has traditionally construed God as an intentional agent who acts on creation and in relation to humankind. God loves, punishes, and redeems. God's intentionality has traditionally been construed in analogy to human intentionality, which in turn has often presumed a supernatural dualism. Developments in cognitive science, however, render supernatural dualism suspect for explaining the human mind. How, then, can we speak of the mind of God? Borrowing from Daniel Dennett's intentional stance, I suggest that analogical reasoning regarding the mind of God be abandoned in favor of an ontologically agnostic approach that treats God as an intentional system. In this approach, God's purposive action is an explanatory feature of the believer's universe, a real pattern that informs our values and beliefs about the world and our place in it.     

Is community necessary? Quasi-philosophical ruminations

In responding to and examining Mary Anne Raywid's (1989) adoption of community building as an aim for schools, I survey a number of types of communities, including recreational, intentional and language communities. In considering all these communities, I try to show both the power of communities in our personal lives and some idea of why we might be of two minds about promoting community as an ideal in the modern world and in schools in particular.     

结果预期与结果反应对儿童意图认知和道德判断的影响

考察了结果预期与结果反应对儿童意图认知和道德判断的影响。结果表明,结果预期影响幼儿园和小学儿童的意图认知,结果反应仅影响幼儿园儿童的意图认知;结果预期和结果反应显著地影响幼儿园和小学儿童的道德判断,但结果预期对小学儿童道德判断的影响要比结果反应大。     

TEACHING FOSTER GRANDPARENTS TO TRAIN SEVERELY HANDICAPPED PERSONS

Five foster grandparents were taught training skills for use in their daily interactions with severely handicapped persons in an institution. Following baseline, specific teaching procedures consisting of teacher instructions, prompts, modelling, and praise were implemented. The grandparents' frequency of training three skill areas increased as the specific teaching was implemented in multiple-baseline format. The total amount of training continued as teacher instructions, prompts, and modelling were terminated and praise continued, although the grandparents spent their training time emphasizing only two of the three skill areas. Teacher presence was gradually reduced over an 11-week period, with no decrease in grandparents' frequency of training. Four of the foster grandchildren, all profoundly retarded and multiply handicapped, demonstrated progress throughout the study. Results were discussed in light of the available contributions of foster grandparents in institutional settings and maintenance of staff training.     

TRAINING PRESCHOOL CHILDREN TO RECRUIT NATURAL COMMUNITIES OF REINFORCEMENT1

Four normal and four deviant children aged four-to-six years were taught to judge the quality of their academic work in a preschool classroom, and to prompt or cue their teachers to comment about the quality of that work. When these skills did not generalize spontaneously to other teachers in concurrent natural situations, generalized responding was taught by the experimenter, in multiple-baseline design across subjects. This generalization programming enabled the children to contact a sometimes dormant, but readily available natural community of teacher praise and reinforcement, i.e., to recruit an increase in cued praise and schedules of praise for their good work. These behaviors may be important to young children who find themselves bereft of attention in classrooms.     

Learning algorithm for an intelligent decision making system based on multi-agent neurocognitive architectures

The paper presents the formalism of an intelligent decision-making system based on multi-agent neurocognitive architectures, which has an architectural similarity to the human brain. An invariant of the organizational and functional structure of the intellectual decision-making process based on the multi-agent neurocognitive architecture is developed. An algorithm for teaching intelligent decision-making systems based on the self-organization of the invariant of multi-agent neurocognitive architectures is presented. Using this algorithm, an intelligent agent was trained and the architecture of the learning process was built on the basis of an invariant of neurocognitive architecture. Further research is related to training an intelligent agent in more complex behavior and expanding the capabilities of an intelligent decision-making system based on multi-agent neurocognitive architectures.     

Toward ethical cognitive architectures for the development of artificial moral agents

New technologies based on artificial agents promise to change the next generation of autonomous systems and therefore our interaction with them. Systems based on artificial agents such as self-driving cars and social robots are examples of this technology that is seeking to improve the quality of people’s life. Cognitive architectures aim to create some of the most challenging artificial agents commonly known as bio-inspired cognitive agents. This type of artificial agent seeks to embody human-like intelligence in order to operate and solve problems in the real world as humans do. Moreover, some cognitive architectures such as Soar, LIDA, ACT-R, and iCub try to be fundamental architectures for the Artificial General Intelligence model of human cognition. Therefore, researchers in the machine ethics field face ethical questions related to what mechanisms an artificial agent must have for making moral decisions in order to ensure that their actions are always ethically right. This paper aims to identify some challenges that researchers need to solve in order to create ethical cognitive architectures. These cognitive architectures are characterized by the capacity to endow artificial agents with appropriate mechanisms to exhibit explicit ethical behavior. Additionally, we offer some reasons to develop ethical cognitive architectures. We hope that this study can be useful to guide future research on ethical cognitive architectures.