Producing evidence that can be used in court is a central goal of criminal investigations. Forensic science focuses with considerable success on the production of pieces of evidence from specific sources. However, less is known about how a team of investigating police officers progressively produces a body of evidence during the course of a criminal investigation. This literature review uses Weickian sensemaking to analyse what is known about this process in criminal investigations into organised crime. Focusing on the criminal investigation team, collective sensemaking is used as a lens through which to place the reasoning processes used in constructing evidence in a social context. In addition to describing three constituent parts of collective sensemaking relevant for criminal investigations, six factors are identified that influence the quality of collective sensemaking. Building on these results, nine focal points are presented for analysing the sensemaking processes in a criminal investigation team, aimed at advancing knowledge about the production of evidence in criminal investigations of organised crime. Furthermore, a definition of evidence is developed that is suitable for studying sensemaking in the context of an ongoing criminal investigation.
Forensic and behavioural science are often seen as two different disciplines. However, there is a growing realization that the two disciplines should be more strongly integrated. Incorporating psychological theories on human behaviour in forensic science could help solving investigative problems, especially at the crime scene. At the crime scene it is not just about applying scientific methods to analyse traces; these traces must first be perceived and categorized as relevant. At the crime scene, the behavioural perspective of an investigative psychologist could play an important role. In this study, we examine to what extent (1) investigative psychologists detect deviant behavioural cues compared to forensic examiners when investigating a crime scene, (2) forensic examiners can find the relevant traces that can be associated with this behaviour and (3) the availability of a psychological report highlighting these behavioural cues helps forensic examiners in finding more relevant traces. To this end, a total of 14 investigative psychologists and 40 forensic examiners investigated a virtual 3D mock crime scene. The results of this study show that investigative psychologists see significantly more deviant behavioural cues than forensic examiners, and that forensic examiners who receive a psychological report on these cues recognize and collect significantly more traces that can be linked to deviant behaviour and have a high evidential value than examiners who did not receive this information. However, the study also demonstrates that behavioural information is likely to be ignored when it contradicts existing beliefs.
Currently, promising new tools are under development that will enable crime scene investigators to analyze fingerprints or DNA-traces at the crime scene. While these technologies could help to find a perpetrator early in the investigation, they may also strengthen confirmation bias when an incorrect scenario directs the investigation this early. In this study, 40 experienced Crime scene investigators (CSIs) investigated a mock crime scene to study the influence of rapid identification technologies on the investigation. This initial study shows that receiving identification information during the investigation results in more accurate scenarios. CSIs in general are not as much reconstructing the event that took place, but rather have a “who done it routine.” Their focus is on finding perpetrator traces with the risk of missing important information at the start of the investigation. Furthermore, identification information was mostly integrated in their final scenarios when the results of the analysis matched their expectations. CSIs have the tendency to look for confirmation, but the technology has no influence on this tendency. CSIs should be made aware of the risks of this strategy as important offender information could be missed or innocent people could be wrongfully accused.
Wildlife crime is an important driver of biodiversity loss and disrupts the social and economic activities of local communities. During the last decade, poaching of charismatic megafauna, such as elephant and rhino, has increased strongly, driving these species to the brink of extinction. Early detection of poachers will strengthen the necessary law enforcement of park rangers in their battle against poaching. Internationally, innovative, high tech solutions are sought after to prevent poaching, such as wireless sensor networks where animals function as sensors. Movement of individuals of widely abundant, non-threatened wildlife species, for example, can be remotely monitored ‘real time’ using GPS-sensors. Deviations in movement of these species can be used to indicate the presence of poachers and prevent poaching. However, the discriminative power of the present movement sensor networks is limited. Recent advancements in biosensors led to the development of instruments that can remotely measure animal behaviour and physiology. These biosensors contribute to the sensitivity and specificity of such early warning system. Moreover, miniaturization and low cost production of sensors have increased the possibilities to measure multiple animals in a herd at the same time. Incorporating data about within-herd spatial position, group size and group composition will improve the successful detection of poachers. Our objective is to develop a wireless network of multiple sensors for sensing alarm responses of ungulate herds to prevent poaching of rhinos and elephants.
The increase in the number and complexity of crime activities in our nation together with shortage in human resources in the safety and security domain is putting extra pressure on emergency responders. The emergency responders are constantly confronted with sophisticated situations that urgently require professional, safe, and rapid handling to contain and conclude the situation to minimize the danger to public and the emergency responders. Recently, Dutch emergency responders have started to experiment with various types of robots to improve the responsiveness and the effectiveness of their responses. One of these robots is the Boston Dynamic’s Spot Robot Dog, which is primarily appealing for its ability to move in difficult terrains. The deployment of the robot in real emergencies is at its infancy. The main challenge that the robot dog operators are facing is the high workload. It requires the full attention to operate the robot itself. As such, the professional acts entirely as a robot operator rather than a domain expert that critically examines and addresses the main safety problems at hand. Therefore, there is an urgent request from these emergency response professionals to develop and integrate key technologies that enable the robot dog to operate more autonomously. In this project, we explore on how to increase the autonomy level of the robot dog in order to reduce the workload of the operator, and eventually help the operator remain domain expert. Therefore, we will explore the ability of the robot to autonomously 3D-map unknown confined areas. The results of this project will lead to new practical knowledge and a follow-up project that will focus on further developing the technologies that increase the autonomy of the robot for eventual deployment in operational environments. This project will also have direct contribution to education through involvement of students and lecturers.
