The impact of variability and prechoice experience on taking safety measures: The case of security updates

The goal of this research is to clarify the conditions that trigger reluctance to take cost-effective safety measures. We present three experiments. In two of the experiments, the participants were asked to operate a simulated system for 20 periods, each with 10 trials. They could “update the system” to eliminate the risk of a “security failure” that led to a loss of 100 points. The updating cost was either fixed (at 10 points) or variable (initially 10 points, and some probability of free—0 points—updates). The optimal strategy prescribed updating at the first opportunity. Another experiment focused on one-shot decision under risk. The results highlight two factors that reduce the tendency to update and impair performance: cost variability and prechoice experience. Importantly, we show that the negative impact of cost variability is the product of two tendencies. First, experiencing periods with free updates slowed learning to select the optimal policy. Second, in many cases, the participants behaved as if they plan to update when the cost of updating is low but forget to do so. The results suggest that security can be enhanced by asking users to select a default updating policy before gaining experience and by replacing “free updates” with automatic updates. Information concerning the existence of automatic updates reduced manual updating, but this effect was eliminated by experience.     

Tools for remote usability evaluation of Web applications through browser logs and task models

The dissemination of Web applications is extensive and still growing. The great penetration of Web sites raises a number of challenges for usability evaluators. Video-based analysis can be rather expensive and may provide limited results. In this article, we discuss what information can be provided by automatic tools able to process the information contained in browser logs and task models. To this end, we present a tool that can be used to compare log files of user behavior with the task model representing the actual Web site design, in order to identify where users’ interactions deviate from those envisioned by the system design.     

Object‐Label‐Order Effect When Learning From an Inconsistent Source

Learning in natural environments is often characterized by a degree of inconsistency from an input. These inconsistencies occur, for example, when learning from more than one source, or when the presence of environmental noise distorts incoming information; as a result, the task faced by the learner becomes ambiguous. In this study, we investigate how learners handle such situations. We focus on the setting where a learner receives and processes a sequence of utterances to master associations between objects and their labels, where the source is inconsistent by design: It uses both “correct” and “incorrect” object‐label pairings. We hypothesize that depending on the order of presentation, the result of the learning may be different. To this end, we consider two types of symbolic learning procedures: the Object‐Label (OL) and the Label‐Object (LO) process. In the OL process, the learner is first exposed to the object, and then the label. In the LO process, this order is reversed. We perform experiments with human subjects, and also construct a computational model that is based on a nonlinear stochastic reinforcement learning algorithm. It is observed experimentally that OL learners are generally better at processing inconsistent input compared to LO learners. We show that the patterns observed in the learning experiments can be reproduced in the simulations if the model includes (a) an ability to regularize the input (and also to do the opposite, i.e., undermatch) and (b) an ability to take account of implicit negative evidence (i.e., interactions among different objects/labels). The model suggests that while both types of learners utilize implicit negative evidence in a similar way, there is a difference in regularization patterns: OL learners regularize the input, whereas LO learners undermatch. As a result, OL learners are able to form a more consistent system of image‐utterance associations, despite the ambiguous learning task.     

The origins of belief representation: Monkeys fail to automatically represent others’ beliefs

Young infants’ successful performance on false belief tasks has led several researchers to argue that there may be a core knowledge system for representing the beliefs of other agents, emerging early in human development and constraining automatic belief processing into adulthood. One way to investigate this purported core belief representation system is to examine whether non-human primates share such a system. Although non-human primates have historically performed poorly on false belief tasks that require executive function capacities, little work has explored how primates perform on more automatic measures of belief processing. To get at this issue, we modified Kovács et al. (2010)’s test of automatic belief representation to examine whether one non-human primate species—the rhesus macaque (Macaca mulatta)—is automatically influenced by another agent’s beliefs when tracking an object’s location. Monkeys saw an event in which a human agent watched an apple move back and forth between two boxes and an outcome in which one box was revealed to be empty. By occluding segments of the apple’s movement from either the monkey or the agent, we manipulated both the monkeys’ belief (true or false) and agent’s belief (true or false) about the final location of the apple. We found that monkeys looked longer at events that violated their own beliefs than at events that were consistent with their beliefs. In contrast to human infants, however, monkeys’ expectations were not influenced by another agent’s beliefs, suggesting that belief representation may be an aspect of core knowledge unique to humans.     

Affordances as constraints on the control of stance

In this article we present an ecological treatment of the control of stance by multi-segment organisms. We treat the organism as a black box, and the organism-environment interaction as a closed-loop system. We argue that different ways of controlling stance can have differing utility (affordances) for perception and action. We further argue that the affordances of a particular control strategy are in part determined by (a) the mechanical properties of the organism, (b) the mechanical properties of the surface on which stance takes place, and (c) the goals of behavior. Our conclusion is that the control of stance is based on, or constrained by, perception of the kinematic consequences, or affordances, of control actions. Finally, we argue that the relationship between affordances and constraints on control actions should be investigated using geometrical methods.     

Common-sense reasoning as proto-scientific agent activity

We wish to model common-sense reasoning in situations where it contains some of the ingredients typical of proto-scientific reasoning, with a view to future elaboration and proof of concept. To model this proto-scientific narrative, we employ the integrative formal computational machinery we have been developing and implementing for rational cooperative epistemic agents. In our logic-based framework, agents can update their own and each other's theories, which are comprised of knowledge, active rules, integrity constraints, queries, abducibles, and preferences; they can engage in abductive reasoning involving updatable preferences; set each other queries; react to circumstances; plan and carry out actions; and revise their theories and preferences by means of concurrent updates on self and others.     

A motor isolation effect: When object manipulability modulates recall performance

Previous studies suggested that the language production architecture is recruited during verbal retention, and others proposed that spatial memory relies on the oculomotor system. The objective of the present study was to investigate the role of the motor system in object memory, by examining the effect of objects' affordances on retention. In a serial recall task, we manipulated the manipulability of objects to retain in memory. We used an isolation paradigm where we isolated the manipulability level of one object from the list. We showed that recall performance improved for the isolated object (Experiment 1) and that this advantage was abolished when participants were required to perform motor suppression during the task (Experiment 2). In Experiment 3, we showed that the abolition of the motor isolation effect in Experiment 2 was not due to an effect of distraction since motor suppression was shown not to interfere with a semantic isolation effect. It is argued that motor affordances play a role in object memory, but only when the motor characteristics of an object allow discriminating it from the other objects in the list.     

Getting it right by getting it wrong: When learners change languages

When natural language input contains grammatical forms that are used probabilistically and inconsistently, learners will sometimes reproduce the inconsistencies; but sometimes they will instead regularize the use of these forms, introducing consistency in the language that was not present in the input. In this paper we ask what produces such regularization. We conducted three artificial language experiments, varying the use of determiners in the types of inconsistency with which they are used, and also comparing adult and child learners. In Experiment 1 we presented adult learners with scattered inconsistency - the use of multiple determiners varying in frequency in the same context - and found that adults will reproduce these inconsistencies at low levels of scatter, but at very high levels of scatter will regularize the determiner system, producing the most frequent determiner form almost all the time. In Experiment 2 we showed that this is not merely the result of frequency: when determiners are used with low frequencies but in consistent contexts, adults will learn all of the determiners veridically. In Experiment 3 we compared adult and child learners, finding that children will almost always regularize inconsistent forms, whereas adult learners will only regularize the most complex inconsistencies. Taken together, these results suggest that regularization processes in natural language learning, such as those seen in the acquisition of language from non-native speakers or in the formation of young languages, may depend crucially on the nature of language learning by young children.     

Tracking Fluctuations in Psychological States Using Social Media Language: A Case Study of Weekly Emotion

Personality psychologists are increasingly documenting dynamic, within-person processes. Big data methodologies can augment this endeavour by allowing for the collection of naturalistic and personality-relevant digital traces from online environments. Whereas big data methods have primarily been used to catalogue static personality dimensions, here we present a case study in how they can be used to track dynamic fluctuations in psychological states. We apply a text-based, machine learning prediction model to Facebook status updates to compute weekly trajectories of emotional valence and arousal. We train this model on 2895 human-annotated Facebook statuses and apply the resulting model to 303 575 Facebook statuses posted by 640 US Facebook users who had previously self-reported their Big Five traits, yielding an average of 28 weekly estimates per user. We examine the correlations between model-predicted emotion and self-reported personality, providing a test of the robustness of these links when using weekly aggregated data, rather than momentary data as in prior work. We further present dynamic visualizations of weekly valence and arousal for every user, while making the final data set of 17 937 weeks openly available. We discuss the strengths and drawbacks of this method in the context of personality psychology's evolution into a dynamic science. © 2020 European Association of Personality Psychology     

An EMG-driven musculoskeletal model of the shoulder

This paper aims to develop an EMG-driven model of the shoulder that can consider possible muscle co-contractions. A musculoskeletal shoulder model (the original model) is modified such that measured EMGs can be used as model-inputs (the EMG-driven model). The model is validated by using the in-vivo measured glenohumeral-joint reaction forces (GH-JRFs). Three patients carrying instrumented hemi-arthroplasty were asked to perform arm abduction and forward-flexion up to maximum possible elevation, during which motion data, EMG, and in-vivo GH-JRF were measured. The measured EMGs were normalized and together with analyzed motions served as model inputs to estimate the GH-JRF. All possible combinations of input EMGs ranging from a single signal to all EMG signals together were tested. The 'best solution' was defined as the combination of EMGs which yielded the closest match between the model and the experiments. Two types of inconsistencies between the original model and the measurements were observed including a general GH-JRF underestimation and a GH-JRF drop above 90° elevation. Both inconsistencies appeared to be related to co-contraction since inclusion of EMGs could significantly (p<.05) improve the predicted GH-JRF (up to 45%). The developed model has shown the potential to successfully take the existent muscle co-contractions of patients into account.     

Synesthesia Affects Verification of Simple Arithmetic Equations

To investigate the effects of color–digit synesthesia on numerical representation, we presented a synesthete, called SE, in the present study, and controls with mathematical equations for verification. In Experiment 1, SE verified addition equations made up of digits that either matched or mismatched her color–digit photisms or were in black. In Experiment 2A, the addends were presented in the different color conditions and the solution was presented in black, whereas in Experiment 2B the addends were presented in black and the solutions were presented in the different color conditions. In Experiment 3, multiplication and division equations were presented in the same color conditions as in Experiment 1. SE responded significantly faster to equations that matched her photisms than to those that did not; controls did not show this effect. These results suggest that photisms influence the processing of digits in arithmetic verification, replicating and extending previous findings.     

不同条件下拟合指数的表现及临界值的选择

在本模拟研究中设计了6种样本容量,6种因子载荷,和4种评分等级,并考察了正态和非正态分布两种情况。采用的错误模型为参数误置（真模型中每个因子各由5个题目来测量,错误模型中则是第一个因子由6个题测量,另两个因子各由4个和5个题来测量,即有一个因子载荷被误置）模型。结果发现（1）样本量、载荷量、评分等级数和分布形态都对GOF的取值确有影响。其中分布形态的影响最大。NNFI、IFI在不同条件下的平均值是最稳定的,其次是CFI、RMSEA和SRMR。它们都算是值得推荐的GOF,尤其是NNFI和IFI。（2）在正态分布中,当样本量≥1000时,根据NNFI、IFI、CFI、RMSEA、SRMR对模型是否拟合做出判断时有很低的两类错误率,在样本量<1000时则不理想。在偏态条件下无论选择哪个GOF两类错误率都很高。（3）采用2指数策略在很多情况下也不能显著降低两类错误率。（4）由于在数据分布非正态,或正态但样本量<1000时是难判断模型是否拟合的。因此我们提出了2界值策略。即为每个GOF确定上下两个界值。低于下界值时可判断模型是不正确的,而高于上界值时则可判断模型是正确的。GOF取值处于上下界值之间时难以判断模型是否拟合,只能说越高拟合的可能性越大。这时就要通过跨样本验证和增加样本量来确定模型是否正确     

Black Box Arguments

“Black box argument” is a metaphor for modular components of argumentative discussion that are, within a particular discussion, not open to expansion. In public policy debate such as the controversy over abstinence-only sex education, scientific conclusions enter the discourse as black boxes consisting of a result returned from an external and largely impenetrable process. In one way of looking at black box arguments, there is nothing fundamentally new for the argumentation theorist: A black box argument is very like any other appeal to authority, and what might be said about any particular form of black box will turn out to be a particularized version of what might be said about evaluating arguments based on authority. But in another way of looking at black box arguments, they are a constantly evolving technology for coming to conclusions and making these conclusions broadly acceptable. Black boxes are to argumentation what material inventions are to engineering and related sciences. They are anchored in and constrained by fundamental natural processes, but they are also new things that require theoretical explication and practical assessment.     

Automatic and effortful processing after severe closed head injury

To investigate the automatic versus effortful distinction following severe closed head injury (CHI), we administered free recall and frequency of occurrence tasks to patients and controls. In Experiment 1 we found that both free recall (an effortful task) and judgment of relative frequency of occurrence (an automatic task) were impaired in 15 CHI patients as compared to 14 controls. In Experiment 2 we corroborated this finding and showed that absolute estimates of frequency were also impaired in new samples of 16 patients and 16 controls. We infer that cognitive tasks which normal individuals can perform without practice, feedback, or instructions may demand more effortful strategies following severe CHI.     

Direct and indirect effects of action on object classification

We report three experiments in which name verification responses to either objects (Experiments 1 and 2) or hand movements (Experiment 3) were compared with action decisions, where participants verified whether an object is typically used in the way described by a verbal label. In Experiments 1 and 2, we report that action decisions show more consistent and larger effects of the congruency of either a handgrip or a type of movement than do name verification responses, although there was some effect of the congruency of the handgrip on name verification. In Experiment 3, we demonstrate that the congruency of the object being moved affects both action and name verification responses to hand movements. We discuss the]data relative to accounts of how actions and names are accessed by visually presented objects and in relation to work on the information called upon in classification tasks.     

Reputation blackboard systems

Blackboard systems are motivated by the popular view of task forces as brainstorming groups in which specialists write promising ideas to solve a problem in a central blackboard. Here we study a minimal model of blackboard system designed to solve cryptarithmetic puzzles, where hints are posted anonymously on a public display (standard blackboard) or are posted together with information about the reputations of the agents that posted them (reputation blackboard). We find that the reputation blackboard always outperforms the standard blackboard, which, in turn, always outperforms the arrangement where the agents work independently. The asymptotic distribution of the computational cost of the search, which is proportional to the total number of agent updates required to find the solution of the puzzle, is an exponential distribution for those three search heuristics. Only for the reputation blackboard we find a nontrivial dependence of the mean computational cost on the system size and, in that case, the optimal performance is achieved by a single agent working alone, indicating that, though the blackboard organization can produce impressive performance gains when compared with the independent search, it is not very supportive of cooperative work.     

Judgment is not color blind: The impact of automatic color preference on product and advertising preferences

This research examines the colors white and black and highlights the importance of automatic preference for the color white over black in product choice and advertising contexts. Across three studies, we incorporate multiple Implicit Association Tests to assess automatic preferences for colors, products, races, and advertisements. In Study 1, we demonstrate an automatic color preference for white over black, show that this preference holds for Caucasian-Americans and African-Americans, and find that automatic color preference predicts automatic product preference of white over black-colored products. Study 2 extends these findings by showing that actual behavioral product choice is best predicted by a combination of automatic and explicit color preferences. In the advertising domain, Study 3 demonstrates how automatic color preference influences advertising responses and how it explains the lack of in-group preference by African-Americans in previous implicit studies of racial preference. Collectively, our research draws attention to the need to disentangle white and black as designation of colors versus racial groups, and offers significant and novel contributions to the work on color and race in consumer psychology.     

Working memory components and imagery instructions in the elaboration of a spatial mental model

The paper investigates the involvement of verbal and visuo-spatial working memory during the processing of spatial texts via a dual-task paradigm. Subjects were presented with three texts describing locations from a route perspective, and had either to imagine themselves moving along a route in surroundings or to rehearse verbal information. Concurrently they had to perform a spatial tapping task, an articulatory task, or no secondary task. Performance on a verification test used to assess the product of comprehension showed that the concurrent tapping task impaired performance in the imagery instructions group but not in the repetition instructions group, and caused the beneficial effect of imagery instructions to vanish. This result was not observed with the articulatory task, where interference effects were similar in both instructions groups. Performance on the concurrent tasks confirmed the pattern obtained with the verification test. In addition, results seem partly dependent on the capacity of spatial working memory as measured by the Corsi Blocks Test. We argue that these results clarify the processes of the construction of a spatial mental model, and confirm that the visuo-spatial working memory is involved in mental imagery.     

Enumeration: Experts take their time

Previous research has demonstrated that grouping information enhances enumeration, and that this advantage is significantly greater for observers with expertise in dynamic visuospatial tasks (e.g. air traffic controllers). We sought to elucidate whether this advantage is the result of over‐learned, automated responding in an enumeration experiment where many of the stimuli were incongruent as to canonical arrangement and numerosity. If so, we predicted that experts' performance would be more severely affected than novices'; if not, and experts continued to perform better than novices, we predicted that their response times should increase, reflective of the additional cognitive load needed. We demonstrated the latter is so. Experts continued to out‐perform novices but their response times were significantly slower suggesting that expertise is not rigid and automatic but, rather, is flexible and responsive to the specific situation, allowing experts to switch between strategies. Copyright © 2010 John Wiley & Sons, Ltd.