Legal challenges in bringing AI evidence to the criminal courtroom

Published date01 December 2021
Date01 December 2021
New Journal of European Criminal Law
2021, Vol. 12(4) 531551
© The Author(s) 2021
Article reuse guidelines:
DOI: 10.1177/20322844211057019
Legal challenges in bringing AI
evidence to the criminal
Katherine Quezada-Tav´
Centre for IT and IP Law (CiTiP), KU Leuven, Belgium
Plixavra Vogiatzoglou
Centre for IT and IP Law (CiTiP), KU Leuven, Belgium
Soe Royer
Centre for IT and IP law (CiTiP), KU Leuven, Belgium
Articial Intelligence (AI) is rapidly transforming the criminal justice system. One of the promising
applications of AI in this eld is the gathering and processing of evidence to investigate and
prosecute crime. Despite its great potential, AI evidence also generates novel challenges to the
requirements in the European criminal law landscape. This study aims to contribute to the bur-
geoning body of work on AI in criminal justice, elaborating upon an issue tha t has not received
sufcient attention: the challenges triggered by AI evidence in criminal proceedings. The analysis is
based on the norms and standards for evidence and fair trial, which are eshed out in a large amo unt
of European case law. Through the lens of AI evidence, this contribution aims to reect on these
issues and offer new perspectives, providing recommendations that would help address the
identied concerns and ensure that the fair trial standards are effectively respected in the criminal
Evidence, articial intelligence, fair trial, criminal procedure, criminal investigation, European
criminal law
Corresponding author:
Katherine Quezada-Tav´
arez, Centre for IT and IP Law (CiTiP), KU Leuven, Sint-Michielsstraat, Leuven 3000, Vlaams-
Brabant, Belgium.
AI in law enforcement
In recent years, different elds have been experiencing the transformative power of Articial
Intelligence (AI)
exponentially, and the criminal justice system is not an exception. Notably, AI
can support criminal justice practitioners in examining vast amounts of data, thus creating new
opportunities to investigate and prosecute crimes. In fact, that is already the case for many Law
Enforcement Agencies (LEAs) that rely on AI-driven tools to gather data (which eventually turn
into evidence) or to scrutinise previously collected evidence illustrated by many examples
across Europe.
An evidence-recognising tool based on AI, for instance, is used by Spanish and German LEAs to
search for clues of child sexual abuse within images, assisting them in the detection of faces, objects,
sexual organs and other information which could be indicative of child sexual abuse material in
digital devices.
Such a tool could also help process information of a crime scene by helping detect
hints in pictures that may otherwise have been missed by investigating ofcers. Similarly, police
forces in the United Kingdom use an AI forensic tool to examine mobile phones seized during
criminal investigations to search for potential evidence.
That software can interpret images, analyse
communication patterns, match faces and cross-reference data from different devices func-
tionalities that can help connect the dots when investigating and prosecuting organised crime, for
example. A more concrete case in point is the use of an AI-driven system by Europol
to process
tons of data, facilitating a joint LEA operation. The evidence gathered and processed through AI
helped dismantle encrypted criminal networks, leading to hun dreds of arrests across Europe.
1. For the purposes of this paper, we adopt the general denition of AI in the draft proposal for a regulation on AI presented
by the EuropeanC ommission in 202 1, according to wh ich AI means software that is developed with one or more of
the techniques and approaches listed in Annex I [i.e., machine learning, logic- and knowledge-based, and sta tistical
approaches] and can, for a given set of human-dened objectives, generate outputs such as content, predictions,
recommendations, or decisions inuencing the environments they interact with(art 3(1)). European Commission,
COM(2021) 206 nal Proposal for a Regulation of the European Parliament and of the Council laying down
harmonised rules on Articial Intelligence (Articial Intelligence Act) and amending certain Union legislative acts
(European Commission 2021) <
articial-intelligence?s=09> accessed 21 April 2021).
2. See Spanish National Cybersecurity Institute (INCIBE), 4NSEEK Forensic Analysis Tool(2021)<https://www.incibe.
es/en/european-projects/4nseek/tool> accessed 20 February 2021 and German authorities turn to AI to combat child
pornogr9aphy online(2019) <>
accessed 20 September 2021.
3. See Owen Bowcott and Hannah Devlin, Police Trial AI Software to Help Process Mobile Phone EvidenceThe Guardian
(12 May 2018) <
evidence> accessed 22 February 2021; see more recent report: Siddharth Venkataramakrishnan, UK Police and Other
Investigators Spend £4m on Phone Hacking Software(9 November 2020) <
76a0-49c1-bbd2-f4ebe04ce58c> accessed 22 February 2021.
4. The European Unions law enforcement agency.
5. Ryan Gallagher, EuropeanPolice HackedSecret Phone Network, Used AIfor Major Bust[2020] Bloomberg <https://>
accessed 19 January 2021; Adam Nossiter, When P olice Are Hackers: Hundreds Charged as Enc rypted Network Is
BrokenThe New York Times (2 July 2020) < urope/encrypted-network-
arrests-europe.html> accessed 1 March 2021; The reliability of the collected evidence has been cont ested by Dutch
lawyers. See Jan Meeus, OM Ruziet Met Britt en over Bewijsmateriaal Uit Hack: Het Vertrouwen Is Geschaad”’ NRC
(8 April 2021) <
vertrouwen-is-geschaad-a4039092> accessed 15 April 2021.
532 New Journal of European Criminal Law 12(4)

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