The politics of deceptive borders: ‘biomarkers of deceit’ and the case of iBorderCtrl

ABSTRACT

This paper critically examines a recently developed proposal for a border control system called iBorderCtrl, designed to detect deception based on facial recognition technology and the measurement of micro-expressions, termed ‘biomarkers of deceit’. Funded under the European Commission’s Horizon 2020 programme, the system is analysed in relation to the wider political economy of ‘emotional AI’ and the history of deception detection technologies. We then move on to interrogate the design of iBorderCtrl using publicly available documents and assess the assumptions and scientific validation underpinning the project design. Finally, drawing on a Bayesian analysis we outline statistical fallacies in the foundational premise of mass screening and argue that it is very unlikely that the model that iBorderCtrl provides for deception detection would work in practice. By interrogating actual systems in this way, we argue that we can begin to question the very premise of the development of data-driven systems, and emotional AI and deception detection in particular, pushing back on the assumption that these systems are fulfilling the tasks they claim to be attending to and instead ask what function such projects carry out in the creation of subjects and management of populations. This function is not merely technical but, rather, we argue, distinctly political and forms part of a mode of governance increasingly shaping life opportunities and fundamental rights.

KEYWORDS:

• Smart borders
• migration
• machine learning
• deception detection
• lie detection
• affective computing

Acknowledgement

We are grateful to two anonymous reviewers as well as Vera Wilde, Andrew McStay and Nello Cristianini for their comments on earlier drafts of this article.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1. For a discussion of these issues in the context of iBortderCtrl, we refer to the resources published on www.iborderctrl.no

Additional information

Funding

This work was supported by a Starting Grant from the European Research Council (ERC) under grant number 759903.

Notes on contributors

Javier Sánchez-Monedero

Javier Sánchez Monedero is Research Associate at Cardiff University's School of Journalism, Media and Culture and the Data Justice Lab working on the ERC-funded DATAJUSTICE project. With a background in Computer Science, his current research focuses on bridging the knowledge gap between social and media researchers and technology as well as to perform technological auditing and design proposals at the intersection of intelligent information systems and social justice. Javier has worked on several projects involving distributed systems and machine learning targeting problems of biomedicine, renewable energy and climatology among others. He can be reached at [email protected].

Lina Dencik

Lina Dencik is Reader at Cardiff University's School of Journalism, Media and Culture and Co-Director of the Data Justice Lab. Her research concerns the interplay between media developments and social and political change, with a particular focus on governance and resistance. She has published widely in the areas of digital media and the politics of data and is the author of several books, most recently Digital Citizenship in a Datafied Society (with Arne Hintz and Karin Wahl-Jorgensen, Polity Press 2018) and The Media Manifesto (with Natalie Fenton, Des Freedman and Justin Schlosberg, Polity Press 2020). Lina is Principal Investigator on the ERC-funded DATAJUSTICE project. She can be reached at [email protected].