1. Artificial Intelligence in the domain of security
Building a strategy for DG HOME

3. Definition of Artificial Intelligence https://ec. europa
Artificial intelligence (AI) refers to systems (i) designed by humans (ii) given a complex goal, (iii) act in the physical or digital world by perceiving their environment, (iv) interpreting the collected structured or unstructured data, (v) reasoning on the knowledge derived from this data and deciding the best action(s) to take (according to pre-defined parameters) to achieve the given goal.

4. EU Principles ON AI also for law enforcement
Human-Centric AI: The human-centric approach to AI strives to ensure that human values are always the primary consideration, and forces us to keep in mind that the development and use of AI should not be seen as a means in itself, but with the goal of increasing citizen's well-being.
Trustworthy AI: Trustworthy AI has two components: (1) its development, deployment and use should comply with fundamental rights and applicable regulation as well as respecting d values, ensuring “ethical purpose”, and (2) it should be technically robust and reliable.
Safeguard the EU global competiveness
Safeguard the EU strategical autonomy in research, development and deployment as well as in training

5. Relevance of AI in the security domain
Cybersecurity of Artificial Intelligence based technologies, preventing and protecting them from external attacks.
The exploitation of benefits of Artificial Intelligence for security purposes, including the prevention, detection and investigation of criminal offences and terrorism. Opportunities and benefits of AI tools and solutions in support of the work of law enforcement.
The prevention of malicious and criminal use of Artificial Intelligence.

6. Role of the social media and the dark web and crypto-currencies
Traffickers and smugglers use social media, websites and anonymizing applications and networks to contact and recruit their victims and customers and communicate easily and anonymously with buyers and conspirators within their trafficking rings.
Illicit trade of firearms, drugs child pornography takes place on the dark web (encrypted network)
Payment is in crypto currencies which make the traceability very difficult.
In order to ensure effectiveness of investigations and prosecutions, it is important to better understand the extent and ways that traffickers, victims and consumers are using technology in the different stages of the trafficking process (recruitment, travel or transfer, housing, financial transactions, advertisement and control methods).
Technological advancements also provide unprecedented opportunities for law enforcement agencies to monitor illicit activities, locate and rescue victims, collect and analyse data leading to the prosecution of traffickers and smugglers.

7. Challenges of the data volume
The increased volume of digital data to be collected, preserved and analysed in computer-based investigations has highlighted the need for highly specialized capacity-building and the absolute necessity of strengthening international judicial and law enforcement cooperation to handle the substantively increased volume of requests for digital data.
Member States face the lack of or deficiencies in systematic and longitudinal data collection, analysis and dissemination, including on trends, patterns and modi operandi related to new and emerging forms of crime, many of which are not consistently monitored at the domestic or international levels.
Unprecedented technological developments in the last decades have opened up many opportunities for the law enforcement authorities but at the same time they have also posed a major challenge. Law enforcement authorities must have the capacity to acquire and develop the same skills than the criminals.

8. Challenges of quickly evolving technologies
Tracking the flows of illicit funds, particularly those derived from corruption and transnational organized crime, as well as those intended for the financing of terrorism, and analysing the magnitude of these illicit funds and the extent to which they are laundered through the world’s financial systems, remain daunting tasks.
Illegal activity based upon advanced technologies is as varied as the technologies themselves.
The lack of recognition and underutilization of forensic science and specialized investigative techniques.
At the borders officers must take informed decisions affecting individuals within a very short period of time based upon high amount of data.

9. Opportunities and challenges in the security domain
AI represents considerable challenges concerning:
Technology
Expertise,
Manpower
Misuse
Opportunities and challenges in the security domain
AI offers new, so far unknown, unexplored opportunities, it will open up new knowledge, hidden information and links

10. The most pressing challenge is to undertake the necessary adaptations of criminal justice and law enforcement measures in order to adequately respond to crimes committed by using such technologies. The Commission can offer expertise and funding.
A change is needed

11. Examples where AI can be used
Interpreting/analysing huge amount of data (images, videos, audio records, geospatial intelligence, communication data, surveillance/datafication);
Movement profiles of stolen vehicles;
Detection of illicit content online and misinformation,
Detection, clustering and analysis of child sex abuse material,
Web analytics and open source intelligence from social media, dark web;
Enriching biometrics and identity techniques by machine learning;
Early identification of criminal behaviour and events,
Protection of public spaces and mass events;
Object recognition and identification
Localisation of bomb factories, networks, facilities;

12. Examples where AI can be used
Autonomous border surveillance;
Detection of network attacks;
Monitoring and protection of networks in critical infrastructure;
Preventing political profiling, targeting, manipulation, bots spreading fake news;
Preventing influencing public opinion, voter behaviour

13. EXISTING AI-BACKED PROJECTS IN EU
AI-backed technologies are already in use either as a test or pilot or they are on the market. Examples of EU funded research projects are the following:
ANITA (Advanced tools for fighting oNline Illegal TrAfficking) is designing and developing a novel knowledge-based user-centred AI investigation system for analysing heterogeneous (text, audio, video, image) online (Surface Web, Deep Web, DarkNet) and offline content for fighting illegal trafficking of drugs, counterfeit medicines, NPS and firearms.
TENSOR (Retrieval and Analysis of Heterogeneous Online Content for Terrorist Activity Recognition) and DANTE (Detecting and ANalysing TErrorist-related online contents and financing activities) are developing AI-based tools for automatic identification and collection of electronic evidence in the area of the terrorist content online.
VALCRI (Visual Analytics for Sense-Making in Criminal Intelligence Analysis) can scan millions of police records, interviews, pictures, videos and other types of evidence to identify patterns and make connections that might be relevant to an investigation.

14. Approach of dg home Pilot research project under Horizon 2020
Study on AI in the field of the large-scale IT system
Establishing the priorities for law enforcement and border security
Particular challenge related to the complex EU landscape:
Altogether 32 European countries with very different level of IT development, priorities, administrative organisation and also legislation
Resource intensive development – pulling together the expertiese
Role of the EU agencies

15. RESEARCH UNDER H2020 and PRIORITIES FOR LAW ENFORCEMENT
In the scope of Horizon 2020, on-going discussions are taking place in order to set up a pilot call on AI that would:
Lead to a research roadmap for future calls in the scope of Horizon Europe
Build a basis for an AI-hub in support of Law Enforcement and citizen protection, cybersecurity operations and prevention and protection against adversarial AI
Analyze human, societal, ethical and legal aspects of using AI in support of Law Enforcement
In order to discuss needs of Law Enforcement from digital tools in general, with a special focus on AI, a technical meeting is organized in the scope of the Community of Users on Secure, Safe and Resilient Societies on 29 March, bringing together representatives of security research, Law Enforcement and policy making.

16. Study on Ai in the field of large-scale It systems
Purpose: assess the conditions for implementing IA in the areas supported by large-scale IT systems
Expected result: a description of the portfolio of initiatives to be undertaken – both under constant or changed legislation
Approach:
Identify the “landscape” of opportunities
Go back to the processes to identify the opportunities to do “the same thing better”, the “same thing differently (and better)”, “ a different thing for reaching the (policy) objective”
Formalise the initiatives in a portfolio: what, when, where, what goes first,..
Study results by the end of 2019

17. Dg home high level meeting of 13 march
Objective: to identify priority actions for the Member States, the Commission and the JHA agencies which would be eligible for funding under the Digital Europe program and would be incorporated into the 2020 Work Program of CNECT. Participants: all Member States and Schengen Associated countries EBCGA, EUROPOL, eu-LISA and CEPOL were represented as well as colleagues from HOME, JRC, CNECT, the General Secretariat of the Council and the Counter-Terrorism Coordinator

18. Questions to member states and agencies
What is according to your knowledge the current use of AI in your area both at the EU and Member State level (if any)?
What are your 2-3 main ideas about the use of AI in your field that you would want to foster in the future?
What are the main (current and possible future) challenges of the use of AI in your field?
Do you have already or do you plan to establish a dedicated structure or framework to deal with AI for law enforcement purposes?

19. Outcome of the meeting
State of play: in many MS a national AI strategy has been adopted but there is no dedicated AI strategy for security and migration.
Deployment: In some MS there are already ongoing AI deployment in certain areas, such as big data analysis, facial recognition, biometrics, forensic and predictive policing. In other MS projects and studies have been launched.
Governance: Only in very few MS there is a dedicated structure in place (a governance) for AI deployment in the field of security, in most MS this activity forms part of existing structures or ongoing projects.
Regulation: Certain MS prefers to with creating an appropriate legal framework before launching any project or deployments.
Education: Some MS has already invested into dedicated training and educational programs in AI technologies.  
Challenges: most MS mentioned the lack of training data to train the algorithms, the maintenance of data quality and the risk of data pollution. They have also see the limits imposed by the constitutional and legal order of MS, in particular the GDPR and the Police Data Protection Directive. One MS also underlined the necessity to build public- private partnership to obtain the necessary financing. Several participants mentioned deepfakes and tampering of digital evidence which will soon pose unsurmountable difficulties to investigators and courts to distinguish them from real evidence.

20. Possible way forward
COM to revise the concept note by adding the current and upcoming sources of funding provided by the EU for AI related projects with the timeline as well as the prioritisation of security related AI activities as agreed in the meeting.
COM to organise a follow up meeting to better define the concept of a data lake (description, elements and objectives) and common available training data with the view to better define its purpose and possible legal issues.
MS to circulate its inventory of procedures, possibly in a simplified format.
MS to organise a workshop with other interested MS to develop the concept of a “recommendation system” proposing possible relevant data for investigators about a concrete subject matter.
COM to clarify the availability of test tools which are available on the market.
COM to clarify the legal and data protection issues in the development and use of AI.
COM to examine and asses the use of the European Data Space for the use of law enforcement and migration authorities.
HOME to reach out to JUST to align the JUST AI backed-technologies with the HOME initiatives.

21. ThANK YOU zsuzsanna felkai janssen zsuzsanna.felkai-janssen@ec.europa.eu