Grappling With Implicit Social Bias: A Perspective From Memory Research

An Active Inference Agent for Modeling Human Translation Processes

This paper develops an outline for a hierarchically embedded architecture of an artificial agent that models human translation processes based on principles of active inference (AIF) and predictive processing (PP). AIF and PP posit that the mind constructs a model of the environment which guides behavior by continually generating and integrating predictions and sensory input. The proposed model of the translation agent consists of three processing strata: a sensorimotor layer, a cognitive layer, and a phenomenal layer. Each layer consists of a network of states and transitions that interact on different time scales. Following the AIF framework, states are conditioned on observations which may originate from the environment and/or the embedded processing layer, while transitions between states are conditioned on actions that implement plans to optimize goal-oriented behavior. The AIF agent aims at simulating the variation in translational behavior under various conditions and to facilitate investigating the underlying mental mechanisms. It provides a novel framework for generating and testing new hypotheses of the translating mind.

Differences in Implicit Attitudes in West and East Germans as Measured by the Go/NoGo Association Task and Event-related EEG Potentials

BACKGROUND AND OBJECTIVE

Implicit social cognition refers to attitudes and stereotypes that may reside outside conscious awareness and control but that still affect human behavior. In particular, the implicit favoritism of an ingroup, to which an individual belongs, as opposed to an outgroup, to which the individual does not belong, characterized as ingroup bias, is of interest and is investigated here.

METHOD

We used a Go/NoGo association task (GNAT) and behavioral and electroencephalographic (event-related EEG potential [ERP] analysis) measures to investigate the implicit bias toward cities in East Germany, West Germany, and Europe, in 16 individuals each from West and East Germany (mixed gender, M age = 24). The GNAT assesses an individual's Go and NoGo responses for a given association between a target category and either pole (positive or negative) of an evaluative dimension.

RESULTS

Behavioral measures revealed slightly faster reaction times to the combination of European city names and negative, as compared with positive, evaluative words in both groups. ERP analysis showed an increased negativity at 400-800 ms poststimulus in the incongruent conditions of East German city/positive word pairings (in West Germans) and West German city/positive word pairings (in East Germans).

CONCLUSION

An implicitly moderately negative evaluation of Europe by both groups was exhibited based on the behavioral data, and an increased level of conflict arising from the "incongruent" pairings (ie, as manifestation of an implicitly negative attitude toward East Germany in West Germans, and toward West Germany in East Germans) was exhibited based on the electrophysiological data.

Indoor Air Pollution and Decision-Making Behavior: An Interdisciplinary Review

The human brain is constantly exposed to air pollutants, some of which might be disruptive or even lethal to certain neurons implicated in abstract features of cognitive function. In this review, we present new evidence from behavioral and neural studies in humans, suggesting a link between indoor fine particulate matter and decision-making behavior. To illustrate this relationship, we use qualitative sources, such as historical documents of the Vietnam War to develop hypotheses of how aerial transmission of pollutants might obstruct alternative choices during the evaluation of policy decisions. We first describe the neural circuits driving decision-making processes by addressing how neurons and their cognate receptors directly evaluate and transduce physical phenomena into sensory perceptions that allow us to decide the best course of action among competing alternatives. We then raise the possibility that indoor air pollutants might also impact cell-signaling systems outside the brain parenchyma to further obstruct the computational analysis of the social environment. We also highlight how particulate matter might be pathologically integrated into the brain to override control of sensory decisions, and thereby perturb selection of choice. These lines of research aim to extend our understanding of how inhalation of airborne particulates and toxicants in smoke, for example, might contribute to cognitive impairment and negative health outcomes.

Improving Health Equity: The Role of the Oncology Advanced Practitioner in Managing Implicit Bias

Implicit bias (IB) is the involuntary activation of thoughts, feelings, attitudes, or stereotypes that exist outside of conscious awareness. Implicit bias develops early in life and research documents the existence of IB across health-care settings. Negative IB impacts patient-provider interactions, produces inferior patient outcomes, and contributes to health-care disparities. Oncology APs are subject to IB and should be aware of its potential impact on professional practice. This manuscript explores the concept of IB and reviews evidence examining the clinical impact of IB in the oncology setting. Strategies for identifying and mitigating IB are explored. Highlights include the use of the Implicit Association Test and emotional intelligence. Advanced practice implications are discussed and range from self-improvement to organizational transformation.