The role of information systems in the prevention and detection of transnational and international crime

© Cambridge University Press 2014. All around the world criminal activity remains at the forefront of governmental concerns, not only as a problem that distorts the very fabric of society within the confines of national jurisdictions, but also as a problem that cuts across national borders to exhibit a global dimension. The international dimension of criminal activity remains critical and is generally characterized by a complexity that is unique and requires action on many different levels. Criminals set out to mask their illegal activities and deliberately generate complexity as a means of concealment. In doing so, they exploit new developments in technology that assist them in achieving their ends. This criminality exhibits forms of innovation that stretch far beyond traditional criminal activity (e.g., drug and human trafficking) and manages to attach itself within the broader fabric of society by exploiting the very latest developments. This evolution is necessary as criminals seek not only to escape arrest, prosecution and conviction, but also to enjoy the fruits of their criminality (mostly financial gains). Thus, they seek to develop ways of exploiting the various diffuse norms of social interaction (e.g., trust), financial modes of conduct (e.g., cash-based economies), technological and communication developments (e.g., Internet), and thereby minimize the possibility for detection. By limiting the resources that can be made available for prevention (or making them obsolete when developing new criminal behaviour), they participate in this co-evolution actively; and this they achieve by generating complexity

Algorithms and Autonomy

Algorithms influence every facet of modern life. However, delegating important decisions to machines gives rise to deep moral concerns about responsibility, transparency, fairness, and democracy. This book examines these concerns by connecting them to the human value of autonomy. This title is also available as Open Access on Cambridge Core

The Algorithm Decides : Unintentional Agency Laundering & Explanation

In this paper I explore a situation under-explored by AI researchers where those who deploy decision-making algorithms unintentionally launder their moral agency to algorithms through anthropomorphic ascriptions of their underlying architecture. Often, this kind of agency laundering occurs rather innocently, by attempting to render an otherwise opaque system transparent through simplified and analogous explanations intended to enhance the decision subject’s understanding. Consequently, when unintentional agency laundering happens, the decision subject’s agency to seek recourse for adverse outcomes is undermined in the process of laundering the data controller’s moral agency to a non-agent. This paper explores this situation as it pertains to traditional philosophical accounts of responsibility, explanation, and knowledge and engages in recent literature from AI ethics. The paper proposes that explanation can be a mechanism that closes responsibility gaps in AI. However, only if explanations do not invoke unintentional agency laundering

Can Machine Learning, as a RegTech Compliance Tool, lighten the Regulatory Burden for Charitable Organisations in the United Kingdom?

Purpose: The purpose of this article is to explore the extent to which machine learning can be used as solution to lighten the compliance and regulatory burden on charitable organisations in the United Kingdom. Design/methodology/approach: The subject is approached through the analysis of data, literature, and domestic and international regulation. The first part of the article summarises the extent of current regulatory obligations faced by charities, these are then, in the second part, set against the potential technological solutions provided by machine learning as at July 2021. Findings: It is suggested that charities can utilise machine learning as a smart technological solution to ease the regulatory burden they face in a growing and impactful sector. Originality: The work is original because it is the first to specifically explore how machine learning as a technological advance can assist charities in meeting the regulatory compliance challenge

Multi-sited ethnography of digital security technologies

This chapter will help researchers explore how they can study complex digital security technologies. The chapter delineates a multi-sited ethnographic approached around 'sites of experimentation'. It offers two methodological starting points: (i) following technology from design to use, and (ii) observing human-computer interaction

Electronic fraud detection in the U.S. Medicaid Healthcare Program: lessons learned from other industries

It is estimated that between $600 and$850 billion annually is lost to fraud, waste, and abuse in the US healthcare system,with $125 to$175 billion of this due to fraudulent activity (Kelley 2009). Medicaid, a state-run, federally-matchedgovernment program which accounts for roughly one-quarter of all healthcare expenses in the US, has been particularlysusceptible targets for fraud in recent years. With escalating overall healthcare costs, payers, especially government-runprograms, must seek savings throughout the system to maintain reasonable quality of care standards. As such, the need foreffective fraud detection and prevention is critical. Electronic fraud detection systems are widely used in the insurance,telecommunications, and financial sectors. What lessons can be learned from these efforts and applied to improve frauddetection in the Medicaid health care program? In this paper, we conduct a systematic literature study to analyze theapplicability of existing electronic fraud detection techniques in similar industries to the US Medicaid program

When humans using the IT artifact becomes IT using the human artifact

Following Demetis & Lee (2016) who showed how systems theorizing can be conducted on the basis of a few systems principles, in this conceptual paper, we apply these principles to theorize about the systemic character of technology and investigate the role reversal in the relationship between humans and technology. By applying systems-theoretical requirements outlined by Demetis & Lee, we examine conditions for the systemic character of technology and, based on our theoretical discussion, we argue that humans can now be considered artifacts shaped and used by the (system of) technology rather than vice versa. We argue that the role reversal has considerable implications for the field of information systems that has thus far focused only on the use of the IT artifact by humans. We illustrate these ideas with empirical material from a well-known case from the financial markets: the collapse (“Flash Crash”) of the Dow Jones Industrial Average