Misplaced Trust: Measuring the Interference of Machine Learning in Human Decision-Making

ML decision-aid systems are increasingly common on the web, but their successful integration relies on people trusting them appropriately: they should use the system to fill in gaps in their ability, but recognize signals that the system might be incorrect. We measured how people's trust in ML recommendations differs by expertise and with more system information through a task-based study of 175 adults. We used two tasks that are difficult for humans: comparing large crowd sizes and identifying similar-looking animals. Our results provide three key insights: (1) People trust incorrect ML recommendations for tasks that they perform correctly the majority of the time, even if they have high prior knowledge about ML or are given information indicating the system is not confident in its prediction; (2) Four different types of system information all increased people's trust in recommendations; and (3) Math and logic skills may be as important as ML for decision-makers working with ML recommendations.Comment: 10 page

Structural, item, and test generalizability of the psychopathology checklist - revised to offenders with intellectual disabilities

The Psychopathy Checklist–Revised (PCL-R) is the most widely used measure of psychopathy in forensic clinical practice, but the generalizability of the measure to offenders with intellectual disabilities (ID) has not been clearly established. This study examined the structural equivalence and scalar equivalence of the PCL-R in a sample of 185 male offenders with ID in forensic mental health settings, as compared with a sample of 1,212 male prisoners without ID. Three models of the PCL-R’s factor structure were evaluated with confirmatory factor analysis. The 3-factor hierarchical model of psychopathy was found to be a good fit to the ID PCL-R data, whereas neither the 4-factor model nor the traditional 2-factor model fitted. There were no cross-group differences in the factor structure, providing evidence of structural equivalence. However, item response theory analyses indicated metric differences in the ratings of psychopathy symptoms between the ID group and the comparison prisoner group. This finding has potential implications for the interpretation of PCL-R scores obtained with people with ID in forensic psychiatric settings

A Case for Humans-in-the-Loop: Decisions in the Presence of Erroneous Algorithmic Scores

The increased use of algorithmic predictions in sensitive domains has been accompanied by both enthusiasm and concern. To understand the opportunities and risks of these technologies, it is key to study how experts alter their decisions when using such tools. In this paper, we study the adoption of an algorithmic tool used to assist child maltreatment hotline screening decisions. We focus on the question: Are humans capable of identifying cases in which the machine is wrong, and of overriding those recommendations? We first show that humans do alter their behavior when the tool is deployed. Then, we show that humans are less likely to adhere to the machine's recommendation when the score displayed is an incorrect estimate of risk, even when overriding the recommendation requires supervisory approval. These results highlight the risks of full automation and the importance of designing decision pipelines that provide humans with autonomy.Comment: Accepted at ACM Conference on Human Factors in Computing Systems (ACM CHI), 202

Identifying Causal Risk Factors for Violence among Discharged Patients

This study was funded by the UK National Institute for Health Research (NIHR) under its Programme Grants for Applied Research funding scheme (RP-PG-0407-10500)

Psychopathic Traits of Dutch Adolescents in Residential Care: Identifying Subgroups

The present study examined whether a sample of 214 (52.8% male, M age = 15.76, SD = 1.29) institutionalized adolescents could be classified into subgroups based on psychopathic traits. Confirmatory Factor Analyses revealed a relationship between the subscales of the Youth Psychopathic traits Inventory (YPI) and the three latent constructs of the original model on which it is based. Latent Class Analyses showed that adolescents showing psychopathic traits could be classified into three subgroups. The first group showed low scores on the grandiose/manipulative dimension, the callous/unemotional dimension, and the impulsive/irresponsible dimension (normal group). The second group scored moderate on the grandiose/manipulative dimension and the callous/unemotional dimension and high on the impulsive/irresponsible dimension (impulsive, non-psychopathic-like group). The third group scored high on all three dimensions (psychopathy-like group). The findings revealed that the impulsive, non-psychopathic like group scored significantly higher on internalizing problem behavior compared to the normal group, while the psychopathy-like and the impulsive, non-psychopathic-like group both scored higher on externalizing problem behavior compared to the normal group. Based on a self-report delinquency measure, it appeared that the psychopathy-like group had the highest delinquency rates, except for vandalism. Both the impulsive and psychopathy-like group had the highest scores on the use of soft drugs

As cold as a fish? Relationships between the Dark Triad personality traits and affective experience during the day: A day reconstruction study

The Dark Triad of personality is a cluster of three socially aversive personality traits: Machiavellianism, narcissism and psychopathy. These traits are associated with a selfish, aggressive and exploitative interpersonal strategy. The objective of the current study was to establish relationships between the Dark Triad traits (and their dimensions) and momentary affect. Machiavellianism, grandiose narcissism, vulnerable narcissism and the dimensions of the Triarchic model of psychopathy (namely, boldness, meanness and disinhibition) were examined. We used the Day Reconstruction Method, which is based on reconstructing affective states experienced during the previous day. The final sample consisted of 270 university students providing affective ratings of 3047 diary episodes. Analyses using multilevel modelling showed that only boldness had a positive association with positive affective states and affect balance, and a negative association with negative affective states. Grandiose narcissism and its sub-dimensions had no relationship with momentary affect. The other dark traits were related to negative momentary affect and/or inversely related to positive momentary affect and affect balance. As a whole, our results empirically demonstrated distinctiveness of the Dark Triad traits in their relationship to everyday affective states. These findings are not congruent with the notion that people with the Dark Triad traits, who have a dispositional tendency to manipulate and exploit others, are generally cold and invulnerable to negative feelings. The associations between the Dark Triad and momentary affect were discussed in the contexts of evolutionary and positive psychology, in relation to the role and adaptive value of positive and negative emotions experienced by individuals higher in Machiavellianism, narcissism and psychopathy

Young Offenders’ Emotion Recognition Dysfunction Across Emotion Intensities: Explaining Variation Using Psychopathic Traits, Conduct Disorder and Offense Severity

Antisocial individuals have problems recognizing negative emotions (e.g. Marsh & Blair in Neuroscience and Biobehavioral Reviews 32:454–465, 2009); however, due to issues with sampling and different methods used, previous findings have been varied. Sixty-three male young offenders and 37 age-, IQ- and socio-economic status-matched male controls completed a facial emotion recognition task, which measures recognition of happiness, sadness, fear, anger, disgust, and surprise and neutral expressions across 4 emotional intensities. Conduct disorder (YSR), and psychopathic and callous/unemotional traits (YPI) were measured, and offenders’ offense data were taken from the Youth Offending Service’s case files. Relative to controls, offenders were significantly worse at identifying sadness, low intensity disgust and high intensity fear. A significant interaction for anger was also observed, with offenders showing reduced low- but increased high-intensity anger recognition in comparison with controls. Within the young offenders levels of conduct disorder and psychopathic traits explained variation in sadness and disgust recognition, whereas offense severity explained variation in anger recognition. These results suggest that antisocial youths show specific problems in recognizing negative emotions and support the use of targeted emotion recognition interventions for problematic behavior