Judging Risk

Risk assessment plays an increasingly pervasive role in criminal justice in the United States at all stages of the process, from policing, to pre-trial, sentencing, corrections, and during parole. As efforts to reduce incarceration have led to adoption of risk-assessment tools, critics have begun to ask whether various instruments in use are valid and whether they might reinforce rather than reduce bias in criminal justice outcomes. Such work has neglected how decisionmakers use risk-assessment in practice. In this Article, we examine in detail the judging of risk assessment and we study why decisionmakers so often fail to consistently use such quantitative information

File system modelling for digital triage: An inductive profiling approach

Digital Triage is the initial, rapid screening of electronic devices as a precursor to full forensic analysis. Triage has numerous benefits including resource prioritisation, greater involvement of criminal investigators and the rapid provision of initial outcomes. In traditional scientific forensics and criminology, certain behavioural attributes and character traits can be identified and used to construct a case profile to focus an investigation and narrow down a list of suspects. This research introduces the Triage Modelling Tool (TMT), that uses a profiling approach to identify how offenders utilise and structure files through the creation of file system models. Results from the TMT have proven to be extremely promising when compared to Encase’s similar in-built functionality, which provides a strong justification for future work within this area

Effective CCTV and the challenge of constructing legitimate suspicion using remote visual images

This paper compares the effectiveness of public CCTV systems according to meta-reviews, with what might be expected based upon theoretical predictions. The apparent gulf between practice and prediction is explored in the light of the challenges faced by CCTV operators in terms of effective target selection. In addition, counter-intuitive reactions by members of the public to situational symbols of crime deterrence may also undermine the efficacy of CCTV. Evidence is introduced and reviewed that suggests CCTV operators may employ implicit profiles to select targets. Essentially, young, scruffy males who appear to be loitering are disproportionately targeted compared with their base rate use of surveyed areas. However, the extent to which such a profile is diagnostic of criminal intent or behaviour is unclear. Such profiles may represent little more than ‘pattern matching’ within an impoverished visual medium. Finally, suggestions for future research and effective CCTV operator practice are offered in order to improve target selection.Peer reviewe

Data-driven personalisation and the law - a primer: collective interests engaged by personalisation in markets, politics and law

Interdisciplinary Workshop on â��Data-Driven Personalisation in Markets, Politics and Law' on 28 June 2019Southampton Law School will be hosting an interdisciplinary workshop on the topic of â��Data-Driven Personalisation in Markets, Politics and Law' on Friday 28 June 2019, which will explore the pervasive and growing phenomenon of â��personalisationâ�� â�� from behavioural advertising in commerce and micro-targeting in politics, to personalised pricing and contracting and predictive policing and recruitment. This is a huge area which touches upon many legal disciplines as well as social science concerns and, of course, computer science and mathematics. Within law, it goes well beyond data protection law, raising questions for criminal law, consumer protection, competition and IP law, tort law, administrative law, human rights and anti-discrimination law, law and economics as well as legal and constitutional theory. Weâ��ve written a position paper, https://eprints.soton.ac.uk/428082/1/Data_Driven_Personalisation_and_the_Law_A_Primer.pdf which is designed to give focus and structure to a workshop that we expect will be strongly interdisciplinary, creative, thought-provoking and entertaining. We like to hear your thoughts! Call for papers! Should you be interested in disagreeing, elaborating, confirming, contradicting, dismissing or just reflecting on anything in the paper and present those ideas at the workshop, send us an abstract by Friday 5 April 2019 (Ms Clare Brady [email protected] ). We aim to publish an edited popular law/social science book with the most compelling contributions after the workshop.Prof Uta Kohl, Prof James Davey, Dr Jacob Eisler<br/

Developing a categorisation system for rapists' speech

Case linkage, the linking of crimes into series, is used in policing in the UK and other countries. Previous researchers have proposed using rapists' speech in this practice; however, researching this application requires the development of a reliable coding system for rapists' speech. A system was developed based on linguistic theories of pragmatics which allowed for the categorization of an utterance into a speech act type (e.g. directive). Following this classification, the qualitative properties of the utterances (e.g. the degree of threat it carried) could be captured through the use of rating scales. This system was tested against a previously developed system using 188 rapists' utterances taken from victims' descriptions of rape. The pragmatics-based system demonstrated higher inter-rater reliability whilst enabling the classification of a greater number of rapists' utterances. Inter-rater reliability for the subscales was also tested using a sub-sample of 50 rapists' utterances and inter-item correlations were calculated. Seventy-six per cent of the subscales had satisfactory to high inter-rater reliability. Based on these findings and the inter-item correlations, the classification system was revised. The potential use of this system for the practices of case linkage and offender profiling is discussed

'Algorithmic impropriety' in UK policing?

There are concerns that UK policing could soon be awash with 'algorithmic impropriety'. Big(ger) data and machine learning-based algorithms combine to produce opportunities for better intelligence-led management of offenders, but also creates regulatory risks and some threats to civil liberties - even though these can be mitigated. In constitutional and administrative law terms, the use of predictive intelligence analysis software to serve up 'algorithmic justice' presents varying human rights and data protection problems based on the manner in which the output of the tool concerned is deployed. But regardless of exact context, in all uses of algorithmic justice in policing there are linked fears; of risks around potential fettering of discretion, arguable biases, possible breaches of natural justice, and troubling failures to take relevant information into account. The potential for 'data discrimination' in the growth of algorithmic justice is a real and pressing problem. This paper seeks to set out a number of arguments, using grounds of judicial review as a structuring tool, that could be deployed against algorithmically-based decision making processes that one might conceivably object to when encountered in the UK criminal justice system. Such arguments could be used to enhance and augment data protection and/or human rights grounds of review, in this emerging algorithmic era, for example, if a campaign group or an individual claimant were to seek to obtain a remedy from the courts in relation to a certain algorithmically-based decision-making process or outcome

Linking serial homicide - : towards an ecologically valid application

Purpose Crime linkage analysis (CLA) can be applied in the police investigation-phase to sift through a database to find behaviorally similar cases to the one under investigation and in the trial-phase to try to prove that the perpetrator of two or more offences is the same, by showing similarity and distinctiveness in the offences. Lately, research has moved toward more naturalistic settings, analyzing data sets that are as similar to actual crime databases as possible. One such step has been to include one-off offences in the data sets, but this has not yet been done with homicide. The purpose of this paper is to investigate how linking accuracy of serial homicide is affected as a function of added hard-to-solve one-off offences. Design/methodology/approach A sample (N = 117-1160) of Italian serial homicides (n = 116) and hard-to-solve one-off homicides (n = 1-1044, simulated from 45 cases) was analyzed using a Bayesian approach to identify series membership, and a case by case comparison of similarity using Jaccard's coefficient. Linking accuracy was evaluated using receiver operating characteristics and by examining the sensitivity and specificity of the model. Findings After an initial dip in linking accuracy (as measured by the AUC), the accuracy increased as more one-offs were added to the data. While adding one-offs made it easier to identify correct series (increased sensitivity), there was an increase in false positives (decreased specificity) in the linkage decisions. When rank ordering cases according to similarity, linkage accuracy was affected negatively as a function of added non-serial cases. Practical implications While using a more natural data set, in terms of adding a significant portion of non-serial homicides into the mix, does introduce error into the linkage decision, the authors conclude that taken overall, the findings still support the validity of CLA in practice. Originality/value This is the first crime linkage study on homicide to investigate how linking accuracy is affected as a function of non-serial cases being introduced into the data.Peer reviewe

CRIMINAL PROFILING AND THE CHALLENGES OF CRIMINAL INVESTIGATION IN NIGERIA POLICE FORCE KOGI STATE COMMAND

The study examined criminal profiling and the challenges of criminal investigation in the Nigeria Police Force focusing on Kogi State Command. The specific objectives of the study included examining the mechanisms put in place to aid criminal profiling in the Nigerian criminal justice system, especially in Kogi State Police Command; an evaluation of the effectiveness of the mechanisms; identification of the challenges facing criminal profiling in the Nigerian criminal justice system, especially in Kogi State Police Command; and suggestions on how criminal profiling can be effective in the Nigerian criminal justice system. The Personality Theory of Criminal Behaviour was adopted as a choice of framework to buttress the study. A purposive sampling technique was adopted in which the study participants were purposively and systematically selected from the sample of 382 out of the total population of 9000 personnel of the Nigeria Police Force. To ensure that the research instruments were valid, a pre-test and proper scrutiny were conducted on every question in the questionnaire and the personal interview guides by five experts. The findings of the study revealed that the establishment of a police records management system, a forensic laboratory system where evidence from DNA sources is scientifically examined, and a central database for all Nigerians were the mechanisms put in place to aid criminal profiling in Nigeria. It was also discovered that criminal investigative analysis, behavioural evidence approach, and environmental psychology were approaches to profiling criminals. The study also established that the mechanisms and approaches used for criminal profiling in Nigeria were very relevant to the criminal justice system but appeared to be ineffective, resulting from inherent challenges such as bribery and corruption, computer illiteracy, lack of professionalism, inadequate funding and remuneration of police personnel and uncooperative attitudes of the members of the public, among others. It was recommended that professional psychologists should be recruited and form a separate department in the Nigerian Police Force; the police should be well funded and better remunerated to boost their morale and commitment to profiling, among others

Algorithmic Policing: An exploratory study of the algorithmically mediated construction of individual risk in a UK police force

Predictive policing has captured the imagination of both enthusiasts hoping to improve public safety and opponents raising concerns around algorithmic bias and opacity. Based on seven in-depth interviews with officers in a UK police force, this article examines the dynamics of how automated risk scores institutionalise an individual-focussed threat-harm-risk strategy aimed at preventing repeat offending. Born out of the need to prioritise work given budget cuts, the risk scores alleviate fears of missing opportunities for prevention and render professional decision-making defendable. Rather than replacing professional judgement, the article finds that officers maintain discretion in a process of co-construction by scrutinising the risk scores and weighing them against other priorities and operational constraints. In a climate of austerity, a concern arises from the scores’ potential to drive short-term selective incapacitation rather than prevention through supportive measures