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

Criminal and Noncriminal Psychopathy: The Devil is in the Detail

Brooks, NS ORCiD: 0000-0003-1784-099XPsychopathy is prevalent and problematic in criminal populations, but is also found to be present in noncriminal populations. In 1992, Robert Hare declared that psychopaths may also “be found in the boardroom”, which has since been followed by an interest in the issue of noncriminal, or even successful, psychopathy. In this chapter, the paradox of criminal and noncriminal psychopathy is discussed with specific attention given to the similarities and differences that account for psychopathic personality across contexts. That psychopathy is a condition typified by a constellation of traits and behaviours requires wider research across diverse populations, and thus the streams of research related to criminal and noncriminal psychopathy are presented and the implications of these contrasting streams are explored

The Triarchic Psychopathy Measure (TriPM): alternative to the PCL-R?

Psychopathic personality disorder is the subject of many research papers and in particular in the context of forensic settings, where its link to risk of future violence has been established. This topic is well examined but there is still considerable debate about the nature of the construct and how psychopathy is measured. Contemporary models such as the triarchic theory (Patrick, Fowles & Krueger, 2009) have been put forward yet the research into psychopathy tends to rely on one assessment tool, the Psychopathy Checklist-Revised (PCL-R; Hare, 2003) that is argued not to capture elements of psychopathy such as boldness. The Triarchic Psychopathy Measure (TriPM; Patrick, 2010) is a measure that is based on the triarchic theory, and it places an equal focus on boldness when measuring psychopathy. It is however a self-report instrument, and this approach has many limitations. This paper aims to review the scientific support for the TriPM and to discuss its potential application to clinical practice. It concludes that the TriPM may not yet be a contender for the PCL-R throne as the sole tool of choice for psychopathy measurement, but the research into the application of the TriPM is expanding our understanding of psychopathy as a construct

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

Characteristics of mentally ill offenders from 100 psychiatric court reports

<p>Abstract</p> <p>Background</p> <p>There is an increasing probability that the psychiatrist will, willingly or not, come into contact with mentally ill offenders in the course of their practice. There are increasing rates of violence, substance abuse and other psychiatric disorders that are of legal importance. Therefore, the aim of this work was to investigate the rates of different mental disorders in 100 court reports and to investigate the characteristics of mentally ill offenders.</p> <p>Methods</p> <p>All cases referred from different departments of the legal system to the forensic committee for assessment of legal accountability over 13-months duration were included. A specially designed form was prepared for data collection. Cases were classified into five groups: murder, robbery, financial offences, violent and simple offences and a group for other offences. Data were subjected to statistical analysis and comparisons between different groups of subjects were performed by analysis of variance (ANOVA).</p> <p>Results</p> <p>Men constituted 93% of cases. In all, 73% of offenders were younger than 40 years old. Schizophrenia cases made up 13% of the total, substance related cases constituted 56% and amphetamine cases alone made up 21%; 10% of cases were antisocial personality disorders, and 51% of cases were classified as having a low education level. Unemployment was found in 34% of cases. The final decision of the forensic committee was full responsibility in 46% of cases and partial responsibility in 11% of cases, with 33% considered non-responsible. A total of 58% of cases had had contact with psychiatric healthcare prior to the offence and in 9% of cases contact had been in the previous 12 weeks. A history of similar offences was found in 32% of cases. In all, 14% of the offences were murders, 8% were sexual crimes, and 31% were violent/simple crimes.</p> <p>Conclusions</p> <p>The ability of the legal system to detect cases was good, while the ability of the healthcare system to predict crimes and offences was weak, as 58% of cases had had previous contact with the healthcare system previously. Substance abuse, especially amphetamine abuse, played an important role.</p

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