Artificial intelligence supporting cross-border cooperation in criminal justice : joint report prepared by eu-LISA and EUROJUST.
Date: 2022-08-31
Institutions: European Union Agency for Criminal Justice Cooperation, European Union Agency for the Operational Management of Large-Scale IT Systems in the Area of Freedom, Security and Justice
Subjects: Eurojust, area of freedom, security and justice, artificial intelligence, biometrics, cross-border cooperation, digital transformation, fight against crime, information security, judicial cooperation in criminal matters in the EU, new technology, terrorism

ARTIFICIAL INTELLIGENCE SUPPORTING CROSS-
BORDER COOPERATION IN CRIMINAL JUSTICE 
JOINT REPORT PREPARED BY EU-LISA AND EUROJUST 

Artificial 
the  key 
(AI) 
technologies  enabling  the  digital  transformation  in 

is  one  of 

Intelligence 

the  justice  area.  The  report  provides  a  high-level 
overview of the policy and legal context for the use 
of  AI  in  cross-border  judicial  cooperation  and 
explores  the  relevant  technologies  and  possible 

use-cases for the application of AI within the judicial 
field.  

Policy and legal context 

At European level, a forward-looking stance on the 
topic  of AI has been adopted since 2017, when 
the EU Council called for a way to address AI as an emerging 
trend, while ensuring ‘high level of data protection, digital rights 
and ethical standards’1. The European approach to regulating 
AI was gradually developed, culminating in the proposal for a 
Regulation laying down harmonised rules on AI, published in 
April 2021 (AI Act)2.  

in 

the  Justice  area, 

Specifically 
the  challenges  and 
opportunities for the use of AI technologies were identified in 
the Digital Criminal Justice study3 and also analysed in the 
Commission  Communication  on  the  further  enhancement  of 
digilisation  of  justice4.  The  European  Parliament  adopted  a 
resolution on AI use by police and judicial authorities in criminal 
matters which highlighted the possible uses and risks of the 
AI use in law enforcement and judiciary.5 

The  proposed  AI  Act  indicates  that  the  use  of  AI  justice 
should  be  considered  as  high-risk,  especially  what 
concerns  AI  systems  intended  to  assist  judicial  authorities  in 
researching and interpreting facts and the law and in applying 
the law to a concrete set of facts. However, such categorisation 
should  not  affect  AI  systems  or  tools  applied  for  ancillary 
administrative  activities, 
such  as  anonymization  or 
pseudonymization  of  judicial  decisions,  documents  or  data, 
communication  between  personnel,  administrative  tasks  or 
allocation of resources.  

AI use-cases for cross-border 
justice cooperation 

Natural language processing technologies 

Figure 1 — overview of NLP applications 

in  different 

langugages.  To  address 

One  of  the  key  challenges  for  judicial  authohrities  is  the 
amount  of  unstructured  information  they  have  to  process 
as part of their investigations. This is further complicated by the 
fact that this information is often presented in multiple media 
and 
this,  natural 
language  processing  (NLP)  technologies  in  combination 
with  other  technologies,  such  as  speech-to-text,  optical 
character recognition and automated translation may be used 
to assist the practitioners in the context of cross-border judicial 
cooperation.  However,  the  compliance  with  the  EU  data 
protection legislation is a precondition before deciding on any 
use of such technologies, notably the principles of necessity, 
proportionality,  data  minimisation  and  data  protection  by 
design should always be considered upfront. 

1 European Council, European Council meeting (19 October 2017), 
https://www.consilium.europa.eu/media/21620/19-euco-final-conclusions-en.pdf   
2 European Commission, 2021/0106(COD), https://eur-lex.europa.eu/legal-con-
tent/EN/TXT/?uri=CELEX:52021PC0206  
3 https://www.eurojust.europa.eu/judicial-cooperation/judicial-cooperation-in-
struments/digital-criminal-justice   

4 European Commission 2020, https://ec.europa.eu/commission/presscor-
ner/detail/en/ip_20_2246  
5 European Parliament 2021, https://www.europarl.europa.eu/doceo/docu-
ment/TA-9-2021-0405_EN.html 

1 

 
 
                                                   
  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
More  specifically, 
following 
applications of natural language processing technologies:  

report  discusses 

the 

the 

Automated document processing;  

Automated translation; 

Automated summarization systems; 

NLP for evidence analysis and anonymization;  

NLP for legal research and analysis. 

AI for forensic analysis and anonymization of audio-
visual media 

Figure 2 — AI for forensic analysis and anonymisa-
tion 

FORENSIC 
ANALYSIS 

BIOMETRIC 
RECOGNITION 

DATA  
ANONYMISATION 

Evidence in criminal investigations is often not limited to text 
and contains a wide range of other media, including images, 
video and audio or voice media. Manual processing of multi-
media evidence has a number of limitations. 

In that sense, machines are a nearly perfect replacement, as 
they can tirelessly perform such tasks, consuming significantly 
fewer resources and in a significantly smaller amount of time.  

Focusing on forensic analysis and anonymisation of audio-
visual  media,  the  report  discusses  applications  of  computer 
vision  for  facial  recognition  and  object  detection  in  image  or 
video data, voice or sound pattern detection in audio data, as 
well as the use of AI for the purposes of anonymisation of 
multi-media evidence. 

It is worth noting that AI supporting these applications is not 
perfect and a number of challenges need to be addressed 
in order for these systems  to be compliant with the ethical 
and legal requirements. Those challenges include reducing 
bias, as well as ensuring transparency and explainability of 
AI systems, among others. 

Ethical and fundamental rights considerations 

The  Ethics  Guidelines  for  Trustworthy  AI 6,  based  in  a 
legislative  acts7, 
following  key 
number  of 
requirements for AI systems:  

identify 

the 

Human agency and oversight;  

Technical robustness and safety;  

Privacy and data governance;  

Transparency; 

Diversity, non-discrimination and fairness;  

Societal and environmental wellbeing; 

Accountability. 

Some  of  these  principles were  also  integrated  in  the  Ethical 
Charter  on  the  use  of  AI  in  judicial  systems,  focusing  more 
specifically on the application of AI in the justice area. 

The  transformative  potential  of  AI  for  the  justice  field  is 
clear; however, AI brings with it a range of risks, which need 
to be taken into consideration when developing and deciding 
to  apply  such  tools.  The  abovementioned  principles  and 
requirements will help in addressing these risks. 

Conclusions 

justice 

field  of 

is  undergoing  digital 
The 
transformation, and artificial intelligence, as a  set 
of  different  technologies,  has  great  potential  to  contribute  to 
and  further  enhance  this  process,  allowing  for  a  significant 
improvement  in  both  the  efficiency  and  effectiveness  of 
operation of the judicial authorities. Similar to digitalisation, the 
use of AI may, in the long term, help significantly reduce 
the  costs  for  the  judicial  authorities.  Efficiency  gains, 
improvements in effectiveness, cost reduction: all of these 
performance improvements can eventually result in improved 
access to justice and reduced time to render judicial decisions. 
However,  a  balanced  approach  is  necessary  in  order  to 
ensure  the  protection  of  fundamental  rights  while 
enhancing  the  digital  transformation,  as  it  is  not  a  purely 
technical challenge, but may have significant legal, ethical and 
fundamental  rights 
implications.  A  risk-based  approach 
(integrating cost benefit analysis, fundamental rights and data 
protection assessments) is proposed to be be developed and 
applied  to  determine  the  safeguards  and  the  deployment 
model for AI systems in practice. 

6 European Commission 2019, https://digital-strategy.ec.europa.eu/en/li-
brary/ethics-guidelines-trustworthy-ai 

7 E.g. Regulation (EU) 2016/679; OJ L 119, 4.5.2016, p. 1–88; Regulation (EU) 
2018/1725; OJ L 295, 21.11.2018, p. 39–98; Directive (EU) 2016/680; OJ L 
119, 4.5.2016, p. 89–131; Directive 2002/58/EC; OJ L 201, 31.7.2002, p. 37–47 

ISBN 978-92-95227-18-7 

doi:10.2857/44362 

Catalogue number: EL-07-22-406-EN-N 

© European Union Agency for the Operational Management of Large-Scale IT Systems in the Area of Freedom, Security and Justice (eu-LISA), 2022 
© The European Union Agency for Criminal Justice Cooperation (Eurojust), 2022 
This document is public. Reproduction is authorised, except for commercial purposes, provided that the source is acknowledged  

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