Matthias Leese


Last Name

Leese

First Name

Matthias

ORCID

0000-0002-7153-7783

Organisational unit

09785 - Leese, Matthias / Leese, Matthias

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2013 - 2019272020 - 202639
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Publications1 - 10 of 66
  • Bulletin 2018 zur schweizerischen Sicherheitspolitik
    Item type: Edited Volume
    Zogg, Benno; Leese, Matthias; Merz, Fabien; et al. (2018)
    The 2018 edition of the CSS’s annual “Bulletin on Swiss Security Policy” includes chapters on Switzerland’s engagement in Ukraine, Belarus, and Moldavia (Benno Zogg), predictive policing in Switzerland (Matthias Leese), cyber security in Israel (Fabien Merz), as well as the role of religion and conflict in Swiss peace policy (Angela Ullmann). The publication also features an interview on Swiss security policy with Chief of the Armed Forces Philippe Rebord. Finally, the Bulletin presents three studies on responsible conduct in cyber space, arms procurement in European states and the Shanghai Cooperation Organisation (SCO).
  • Predictive Policing: Proceed, but with Care
    Item type: Other Publication
    Leese, Matthias (2020)
    CSS Policy Perspectives
    Data-driven analytics can increase the effectiveness and efficiency of police work and crime prevention. Police departments should however proceed with care, as tools such as predictive policing raise a number of concerns regarding human rights and civil liberties, argues Matthias Leese in this CSS Policy Perspective. More specifically, tools such as predictive policing can potentially undermine civil liberties and impair the relationship between the police and the population. In order to ensure responsible use, policy-makers and police chiefs should critically reflect questions of data, automation, decision-making, communication, and operative measures in algorithmically supported police work.
  • Exploring the Security/Facilitation Nexus: Foucault at the 'Smart' Border
    Item type: Journal Article
    Leese, Matthias (2016)
    Global society
  • Data curation: A conceptual framework for the study of data quality
    Item type: Working Paper
    Leese, Matthias (2023)
    CURATE Working Paper
    This Working Paper introduces the concept of data curation as a framework for the study of data quality from a social science perspective. Data curation can be understood as a specific set of data practices that is geared towards making and maintaining the trustworthiness of data and explicates how data require continuous care-taking. Analytically, it offers several advantages to the study of data quality. First of all, it draws attention to the fact that data quality is predicated on distributed forms of labour among various social actors and technical means. Secondly, it explicates the multiple interaction points between humans and data along the lives of data and their journeys through the world. And finally, it introduces a terminology that speaks to the needs of practitioners as well as to academic theory -building.
  • Towards systematic data governance in law enforcement
    Item type: Working Paper
    Leese, Matthias (2026)
    CURATE Working Paper
    As police work becomes increasingly data-driven, data quality has emerged as a key operational and ethical concern. This Working Paper explores how police organizations can improve data governance by addressing recurring structural, technical, and procedural problems. Drawing on findings from the CURATE Project, including a large survey and an in-depth case study on European law enforcement and border control, it identifies persistent challenges such as fragmented IT systems, inconsistent data entry, and unclear responsibility for data quality. To address these issues, the paper proposes the creation of a dedicated Data Stewardship Un it (DSU) within police organizations. Such a unit could standardize data practices, strengthen legal and ethical compliance, and improve coordination across units. While establishing a DSU requires political will, resources, and some IT reform, the Working Paper argues that growing awareness of data quality makes this a timely and necessary step to ensure both effective and legitimate policing.
  • Politics of creep: Latent development, technology monitoring, and the evolution of the Schengen Information System
    Item type: Journal Article
    Leese, Matthias; Ugolini, Vanessa (2024)
    European Journal of International Security
    The Schengen Information System for law enforcement, border control, and judicial cooperation in the European Union has over the years seen a considerable expansion of the amount and types of data stored and its functionalities, as well as its user base. In light of this transformation from a simple information-sharing tool to a full-blown investigative database, there has, however, been surprisingly little public debate and pushback against the growing surveillance and control capacities that the system enables. This article proposes to understand the largely uncontested evolution of the SIS through the concept of 'creep', i.e. the incremental, unforeseen, and/or stealthy development of a technological system beyond what it was originally introduced for. More specifically, it retraces how creep has in the case of the SIS been enabled and facilitated through (1) latent development principles, i.e. the rationale of building dormant features into a system that can be activated at a later point in time once technology has sufficiently matured and/or legal foundations have been adopted; and (2) technology monitoring and steering mechanisms, i.e. the continuous assessment of the readiness of key technologies for anticipated updates to the system as well as interventions in publicly funded research programmes.
  • Politicising Security at the Boundaries: Privacy in Surveillance and Cybersecurity
    Item type: Journal Article
    Dunn Cavelty, Myriam; Leese, Matthias (2018)
    ERIS - European Review of International Studies
  • Digital Data and Algorithms in Law Enforcement: Some Pointers for Responsible Implementation
    Item type: Journal Article
    Leese, Matthias (2022)
    European Law Enforcement Research Bulletin
    Digital data and algorithmic tools have over the past years found their way into law enforcement contexts, including modes of biometric identification and matching, automated surveillance capacities, short-term situational predictions, AI-supported analysis for large amounts of data, and the interoperability of large-scale databases and platforms for data exchange and investigation. These tools can help to increase the effectiveness and efficiency of law enforcement operations on the strategic, tactical, and operational level. They do, however, also come with a number of concerns that must be acknowledged and addressed in order to realize their potential and avoid unintended side-effects and societal frictions. Based on a multi-year research project on predictive policing in Germany and Switzerland, this paper provides a systematic perspective on the challenges involved in implementing new and emerging technologies in law enforcement contexts. Specifically, it will address (1) the nature of data, i.e. how data are socially constructed and present a particular account of the world, inevitably leading to “biased” results; (2) transparency in algorithms and AI, i.e. how “black boxes” undercut human capacities to understand and retrace processes and create problems for public accountability; (3) automation and human control, i.e. the question how human operators can retain meaningful influence over analytical processes; (4) decision-making processes and automation bias, i.e. how humans can be empowered to critically question and override system recommendations; and (5) strategic and societal implications, i.e. the fact that digital tools should not be misused to displace larger programs that address the root causes of crime.
  • Data quality in police work
    Item type: Book Chapter
    Leese, Matthias (2024)
    Palgrave’s Critical Policing Studies ~ Policing and Intelligence in the Global Big Data Era, Volume II: New Global Perspectives on the Politics and Ethics of Knowledge
    This chapter engages the question of data quality, that is the accuracy and reliability of data, in police work. As the police have established novel ways of using data for analytical and managerial purposes, the question of how they make sure that data-driven decisions can be trusted has been given increased practical and political attention. Based on empirical research, this chapter argues for understanding data quality in a relational fashion, as it means different things for different police tasks. Subsequently, it can be studied through the various data practices geared towards the establishment and maintenance of data quality.
  • Between a Carrot and a Stick: Science Diplomacy and Access to EU Research Funding
    Item type: Journal Article
    Leese, Matthias (2018)
    Global Policy
Publications1 - 10 of 66