Burkhard Schafer

Knowledge based crime scenario modelling

A crucial concern in the evaluation of evidence related to a major crime is the formulation of sufficient alternative plausible scenarios that can explain the available evidence. However, software aimed at assisting human crime investigators by automatically constructing crime scenarios from evidence is difficult to develop because of the almost infinite variation of plausible crime scenarios. This paper introduces a novel knowledge driven methodology for crime scenario construction and it presents a decision support system based on it. The approach works by storing the component events of the scenarios instead of entire scenarios and by providing an algorithm that can instantiate and compose these component events into useful scenarios. The scenario composition approach is highly adaptable to unanticipated cases because it allows component events to match the case under investigation in many different ways. Given a description of the available evidence, it generates a network of plausible scenarios that can then be analysed to devise effective evidence collection strategies. The applicability of the ideas presented here are demonstrated by means of a realistic example and prototype decision support software.

Towards a Financial Fraud Ontology: A Legal Modelling Approach

This document discusses the status of research on detection and prevention of financial fraud undertaken as part of the IST European Commission funded FF POIROT (Financial Fraud Prevention Oriented Information Resources Using Ontology Technology) project. A first task has been the specification of the user requirements that define the functionality of the financial fraud ontology to be designed by the FF POIROT partners. It is claimed here that modeling fraudulent activity involves a mixture of law and facts as well as inferences about facts present, facts presumed or facts missing. The purpose of this paper is to explain this abstract model and to specify the set of user requirements.

Algorithmic governance: Developing a research agenda through the power of collective intelligence

We are living in an algorithmic age where mathematics and computer science are coming together in powerful new ways to influence, shape and guide our behaviour and the governance of our societies. As these algorithmic governance structures proliferate, it is vital that we ensure their effectiveness and legitimacy. That is, we need to ensure that they are an effective means for achieving a legitimate policy goal that are also procedurally fair, open and unbiased. But how can we ensure that algorithmic governance structures are both? This article shares the results of a collective intelligence workshop that addressed exactly this question. The workshop brought together a multidisciplinary group of scholars to consider (a) barriers to legitimate and effective algorithmic governance and (b) the research methods needed to address the nature and impact of specific barriers. An interactive management workshop technique was used to harness the collective intelligence of this multidisciplinary group. This method enabled participants to produce a framework and research agenda for those who are concerned about algorithmic governance. We outline this research agenda below, providing a detailed map of key research themes, questions and methods that our workshop felt ought to be pursued. This builds upon existing work on research agendas for critical algorithm studies in a unique way through the method of collective intelligence.

Probabilistic abductive computation of evidence collection strategies in crime investigation

This paper presents a methodology for integrating two approaches to building decision support systems (DSS) for crime investigation: symbolic crime scenario abduction [16] and Bayesian forensic evidence evaluation [5]. This is achieved by means of a novel compositional modelling technique that allows for automatically generating a space of models describing plausible crime scenarios from given evidence and formally represented domain knowledge. The main benefit of this integration is that the resulting DSS is capable to formulate effective evidence collection strategies useful for differentiating competing crime scenarios. A running example is used to demonstrate the theoretical developments.

“Can It Read My Mind?” – What Do the Public and Experts Think of the Current (Mis)Uses of Neuroimaging?

Emerging applications of neuroimaging outside medicine and science have received intense public exposure through the media. Media misrepresentations can create a gulf between public and scientific understanding of the capabilities of neuroimaging and raise false expectations. To determine the extent of this effect and determine public opinions on acceptable uses and the need for regulation, we designed an electronic survey to obtain anonymous opinions from as wide a range of members of the public and neuroimaging experts as possible. The surveys ran from 1st June to 30 September 2010, asked 10 and 21 questions, respectively, about uses of neuroimaging outside traditional medical diagnosis, data storage, science communication and potential methods of regulation. We analysed the responses using descriptive statistics; 660 individuals responded to the public and 303 individuals responded to the expert survey. We found evidence of public skepticism about the use of neuroimaging for applications such as lie detection or to determine consumer preferences and considerable disquiet about use by employers or government and about how their data would be stored and used. While also somewhat skeptical about new applications of neuroimaging, experts grossly underestimated how often neuroimaging had been used as evidence in court. Although both the public and the experts rated highly the importance of a better informed public in limiting the inappropriate uses to which neuroimaging might be put, opinions differed on the need for, and mechanism of, actual regulation. Neuroscientists recognized the risks of inaccurate reporting of neuroimaging capabilities in the media but showed little motivation to engage with the public. The present study also emphasizes the need for better frameworks for scientific engagement with media and public education.

The brain, the science and the media: The legal, corporate, social and security implications of neuroimaging and the impact of media coverage

Neuroimaging is a powerful research and diagnostic tool and is increasingly used outside clinical or scientific settings. However, many of these non-scientific uses, which often are uncritically covered by the media, are not supported by scientific evidence.

No model behaviour: ontologies for fraud detection

This document discusses the status of research on detection and prevention of financial fraud undertaken as part of the IST European Commission funded FF POIROT (Financial Fraud Prevention Oriented Information Resources using Ontology Technology) project, and in particular the interplay of, and tension between, modelling factual and legal aspects of a case.

Crime risk evaluation within information sharing between the police and community partners

The aim of this paper is to provide profiles for crimes, profiles that can be used to model the context for information-sharing between the police and community partner organisations. This context can then be integrated with information-sharing syntax used by Single Point of Contact (SPoC) agents to process information sharing requests (Uthmani et al., 2010). The questionnaires attempt to classify crimes into categories, with identifying profiles of crime-types, according to the level of information sharing they necessitate between community partner organisations. Crimes are separated into classifications, which are based on the perceived level of necessary information-exchange among police and community partners. The aim of the questionnaire is to gather academic responses to identify the level of risk in order that it can be defined as risk assessment level, which is crucial to enhancing the publics reassurance in the police.

Legal Transplants and Legal Downloads

Online legal education has the potential to address a global audience. But little attention has been paid so far to the question of how teaching methods developed in one jurisdiction interact with the substantive law of another legal system. This paper challenges the assumption of the independence of substantive law and law teaching on the basis of a comparative evaluation of online law tutorials in Scotland and Germany. It concludes that the transplanting legal education, as transplanting substantive law, can have unpredictable consequences.

Interagency data exchange protocols as computational data protection law

The paper describes a collaborative project between computer scientists, lawyers, police officers, medical professionals and social workers to develop a communication infrastructure that allows information sharing while observing Data Protection law “by design”, through a formal representation of legal rules in a firewall type system.