Daniel Kahneman's legacy is best understood in light of developments in economic theory in the early-mid-20th century, when economists were eager to put utility functions on a firm mathematical foundation. The axiomatic system that provided this foundation was not originally intended to be normative in a prescriptive sense but later came to be seen that way. Kahneman took the axioms seriously, tested them for descriptive accuracy, and found them wanting. He did not view the axioms as necessarily prescriptive. Nevertheless, in the research program he conceived, factual discoveries about real decision-making were stated as deviations from the axioms and thus deemed ‘errors’. This was an unfortunate turn that needs to be corrected for the psychological enrichment of economics to proceed in a productive direction.

The gradual digitization of EU migration policies is turning external borders into AI-driven filters that limit access to fundamental rights for people from third countries according to risk indicators. An unshakeable confidence in the reliability of technological devices and their ability to predict the future behaviour of incoming foreigners is leading towards the datafication of EU external frontiers. What happens if the supposedly infallible algorithms are wrong? The article aims to understand the consequences of algorithmic errors on the lives of migrants, refugees and asylum seekers arriving in the European Union. This contribution investigates the socio-political implications of deploying data-driven solutions at the borders in an attempt to problematize the techno-solutionist approach of EU migratory policies and its fundamental rights impact on affected individuals.

User models that can directly use and learn how to do tasks with unmodified interfaces would be helpful in system design to compare task knowledge and times between interfaces. Including user errors can be helpful because users will always make mistakes and generate errors. We compare three user models: an existing validated model that simulates users’ behavior in the Dismal spreadsheet in Emacs, a newly developed model that interacts with an Excel spreadsheet, and a new model that generates and fixes user errors. These models are implemented using a set of simulated eyes and hands extensions. All the models completed a 14-step task without modifying the system that participants used. These models predict that the task in Excel is approximately 20% faster than in Dismal, including suggesting why, where, and how much Excel is a better design. The Excel model predictions were compared to newly collected human data (N = 23). The model’s predictions of subtask times correlate well with the human data (r2 = .71). We also present a preliminary model of human error and correction based on user keypress errors, including 25 slips. The predictions to data comparison suggest that this interactive model that includes errors moves us closer to having a complete user model that can directly test interface design by predicting human behavior and performing the task on the same interface as users. The errors from the model’s hands also allow further exploration of error detection, error correction, and different knowledge types in user models.

Birnbaum (2020) reanalyses the data from Butler and Pogrebna (2018) using his ‘true and error’ test of choice patterns. His results generally support the evidence we presented in that paper. Here we reiterate the reasons for our agnosticism as to the direction any cycles might take, even though the paradox that motivated our study takes a ‘probable winner’ direction. We conclude by returning to the potential significance of predictably intransitive preferences for decision theory generally.

Introduction: Trauma resuscitations are plagued with high stress and require time sensitive and intensive interventions. It is a landscape that is a perfect hot bed for clinical errors and adverse events for patients. We sought to describe the adverse events and errors that occur during trauma resuscitation and any associated outcomes. Methods: Medline was searched for a combination of key terms involving trauma resuscitation, adverse events and errors from January 2000 to May 2019. Studies that described adverse events or errors in initial adult trauma resuscitations were included. Two reviewers analyzed papers for inclusion and exclusion criteria with a third reviewer for any discrepancies. Descriptions of errors, adverse events and associated outcomes were collated and presented. Results: A total of 3,462 papers were identified by our search strategy. 18 papers met our inclusion and exclusion criteria and were selected for full review. Adverse events and errors reported in trauma resuscitation included missed injuries, aspiration, failed airway, and deviation from protocol. Rates of adverse events and errors were reported where applicable. Mortality outcomes or length of stay were not directly correlated to adverse events or errors experienced in the trauma resuscitation. Conclusion: Our study highlights the predominance of adverse events and errors experienced during initial trauma resuscitation. We described a multitude of adverse events and errors and their rates but further study is needed to determine outcome differences for patients and possibility for quality improvement.

Introduction: Trauma care is highly complex and prone to medical errors. Accordingly, several studies have identified adverse events and conditions leading to potentially preventable or preventable deaths. Depending on the availability of specialized trauma care and the trauma system organization, between 10 and 30% of trauma-related deaths worldwide could be preventable if optimal care was promptly delivered. This narrative review aims to identify the main determinants and areas for improvements associated with potentially preventable trauma mortality. Methods: A literature review was performed using Medline, Embase and Cochrane Central Register of Controlled Trials from 1990 to a maximum of 6 months before submission for publication. Experimental or observational studies that have assessed determinants and areas for improvements that are associated with trauma death preventability were considered for inclusion. Two researchers independently selected eligible studies and extracted the relevant data. The main areas for improvements were classified using the Joint Commission on Accreditation of Healthcare Organizations patient event taxonomy. No statistical analyses were performed given the data heterogeneity. Results: From the 3647 individual titles obtained by the search strategy, a total of 37 studies were included. Each study included between 72 and 35311 trauma patients who had sustained mostly blunt trauma, frequently following a fall or a motor vehicle accident. Preventability assessment was performed for 17 to 2081 patients using either a single expert assessment (n = 2, 5,4%) or an expert panel review (n = 35, 94.6%). The definition of preventability and the taxonomy used varied greatly between the studies. The rate of potentially preventable or preventable death ranged from 2.4% to 76.5%. The most frequently reported areas for improvement were treatment delay, diagnosis accuracy to avoid missed or incorrect diagnosis and adverse events associated with the initial procedures performed. The risk of bias of the included studies was high for 32 studies because of the retrospective design and the panel review preventability assessment. Conclusion: Deaths occurring after a trauma remain often preventable. Included studies have used unstandardized definitions of a preventable death and various methodologies to perform the preventability assessment. The proportion of preventable or potentially preventable death reported in each study ranged from 2.4% to 76.5%. Delayed treatment, missed or incorrect initial diagnosis and adverse events following a procedure were commonly associated with preventable trauma deaths and could be targeted to develop quality improvement and monitoring projects.

Reasons-responsiveness theories of moral responsibility are currently among the most popular. Here, I present the fallibility paradox, a novel challenge to these views. The paradox involves an agent who is performing a somewhat demanding psychological task across an extended sequence of trials and who is deeply committed to doing her very best at this task. Her action-issuing psychological processes are outstandingly reliable, so she meets the criterion of being reasons-responsive on every single trial. But she is human after all, so it is inevitable that she will make rare errors. The reasons-responsiveness view, it is claimed, is forced to reach a highly counterintuitive conclusion: she is morally responsible for these rare errors, even though making rare errors is something she is powerless to prevent. I review various replies that a reasons-responsiveness theorist might offer, arguing that none of these replies adequately addresses the challenge.

In the usage-based approach to children’s language learning, language is seen as emerging from children’s preverbal communicative and cognitive skills. Children construct more abstract linguistic representations only gradually, and show uneven development in all aspects of their language learning. I will present results that show the relationship between children’s emerging linguistic structures and patterns in the speech addressed to them, and demonstrate the effects played by the consistency of markers, the complexity of the construction in question, and relative type and token frequencies within and across constructions. I highlight the contribution made by research that employs naturalistic, experimental, and modelling methodologies, and that is applied to a range of languages and to variability in the errors that children make. Finally, I will outline the outstanding issues for this approach, and how we might address them.

In interpreting radiocarbon dating results, it is important that archaeologists distinguish uncertainties derived from random errors and those from systematic errors, because the two must be dealt with in different ways. One of the problems that archaeologists face in practice, however, is that when receiving dating results from laboratories, they are rarely able to critically assess whether differences between multiple 14C dates of materials are caused by random or systematic errors. In this study, blind tests were carried out to check four possible sources of errors in dating results: repeatability of results generated under identical field and laboratory conditions, differences in results generated from the same sample given to the same laboratory submitted at different times, interlaboratory differences of results generated from the same sample, and differences in the results generated between inner and outer rings of wood. Five charred wood samples, collected from the Namgye settlement and Hongreyonbong fortress, South Korea, were divided into 80 subsamples and submitted to five internationally recognized 14C laboratories on a blind basis twice within a 2-month interval. The results are generally in good statistical accordance and present acceptable errors at an archaeological scale. However, one laboratory showed a statistically significant variance in ages between batches for all samples and sites. Calculation of the Bayesian partial posterior predictive p value and chi-squared tests rejected the null hypothesis that the errors randomly occurred, although the source of the error is not specifically known. Our experiment suggests that it is necessary for users of 14C dating to establish an organized strategy for dating sites before submitting samples to laboratories in order to avoid possible systematic errors.

The current study examined the use of biographical data to predict errors, tardiness, policy violations, overall job performance, and turnover among nurses. The results of the study indicate that biodata measures are valid selection devices for nurses and effective at predicting nurse errors, tardiness, policy violations, and overall job performance, but the instrument was not an effective predictor of turnover, voluntary or involuntary. Additionally, examination of group differences revealed that White subjects scored significantly higher on the biodata instrument compared to Black subjects but produced group differences considerably smaller than typically found with measures of cognitive ability. Future research directions and implications for practice are discussed.

Numerous studies have demonstrated that prospective memory (PM) abilities are impaired following traumatic brain injury (TBI). PM refers to the ability to remember to complete a planned action following a delay. PM post-TBI has been shown to be related to performance on neuropsychological tests of executive functioning and retrospective episodic memory (RM). However, the relative influence of impairments in RM versus executive functioning on PM performance post-TBI remains uninvestigated. In the current study, PM and neuropsychological test performance were examined in 45 persons with a history of moderate to severe TBI at least 1 year before enrollment. Regression analyses examined the relative contributions of RM and executive functioning in the prediction of PM performance on the Rivermead Behavioral Memory Test (RBMT). Results indicated that scores on tests of delayed RM and rule monitoring (i.e., ability to avoid making errors on executive measures) were the strongest predictors of PM. When the interaction between RM impairment and rule monitoring was examined, a positive relationship between PM and rule monitoring was found only in TBI participants with impaired RM. Results suggest that PM performance is dependent upon rule monitoring abilities only when RM is impaired following TBI. (JINS, 2014, 20, 1–11)