Developing a research roadmap regarding Artificial Intelligence in support of Law Enforcement -

As indicated in the Coordinated Plan on Artificial Intelligence and in the Cybersecurity Joint Communication [1], there is a need to better understand: how AI-based systems, services and products could enhance the objectives of the security sector; how AI technologies can be protected from attacks; how to address any potential abuse of AI for malicious purposes; how to establish cybersecurity requirements for AI. From the Law Enforcement point of view, these dimensions have to be analysed in a longer term, taking into account that the potential AI benefits for Law Enforcement Agencies (LEAs) are threefold, i.e., through: 1) proactive policing (from reactive to anticipative policing); 2) data analysis (e.g., connecting the dots, discovering criminal patterns and defragmenting LEA actions), and 3) identity checks (improving detection, targeting and interdiction).

Scope

Proposals under this topic should provide an EU AI roadmap for LEAs, meeting their specific operational and cooperation needs, by identifying, in a longer-term perspective: the key areas in which AI would be beneficial for LEAs, the key areas in which it could pose a threat to security, cybersecurity requirements for AI based technologies in use or to be used by LEAs as well as means of prevention and mitigation of malicious use of AI for criminal activities. As such this project would not only need to continuously interact (in a cluster mode) with projects funded under SU-AI02-2020 and SU-AI03-2020 but also provide recommendations for further work to be done under Horizon Europe, Digital Europe, or the Internal Security Fund as well as for policy and market uptake. The objective is to develop a research roadmap that provides answers to, e.g., following questions: What are and will be the AI needs of LEAs in their daily work? What are the major research gaps in the area of AI in support of LEAs? What are the challenges that need to be addressed, both from the fighting crime, including cybercrime and terrorism, and from improving cybersecurity (re)actions? Which approaches might be desirable? What needs to be set up for test and evaluation? How to prevent and mitigate malicious use of AI for criminal activities and terrorism?

Starting from these considerations, proposals must demonstrate commitment to produce recommendations that are updated continuously, and at least every 6 months, about the following lines of actions: which AI based technologies, systems and solutions could support/enhance the work of LEAs and how, what the corresponding restraints (including ethical and legal) are, as well as related risks, security challenges and protection measures. The proposal shall provide specific real-life LEAs scenarios, examples and evidence supporting their recommendations. The proposing consortium is expected to incorporate relevant security practitioners, researchers, civil society organisations and LEAs.

As indicated in the Introduction of this call, proposals should foresee resources for clustering activities with other projects funded under this call to identify synergies and best practices.

The Commission considers that proposals requesting a contribution from the EU of around EUR 1.5 million would allow this specific challenge to be addressed appropriately. Nonetheless, this does not preclude submission and selection of proposals requesting other amounts.

Short term:

• Effective contribution to the overall actions of this call;

Medium and longer term:

• In the longer term perspective, identification of key areas in which AI would be beneficial for LEAs, meeting their operational and collaborative needs, and of key areas in which it could pose a threat to security;
• A carefully planned roadmap in order for Law Enforcement to benefit as much as possible from the AI based technologies, systems, solutions, including their protection;
• Increased awareness regarding the state of the art and trends in AI-based criminal activities (short-, mid- and long-term).

GenderSocio-economic science and humanities

[1]JOIN(2017) 450

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