pop AI Consortium will offer excellent clustering ground and a well-established communication network, basing on various EU projects, that are coming with an extensive consortium portfolio and involvement in very relevant EU and national research projects and activities.
(robusT Risk basEd Screening and alert System for PASSengers and luggage) (completed, 1/6/2018 – 30/11/2021)
TRESSPASS is a H2020 project on border security, which aims at introducing a dynamic risk-based integrated border security management across all border modalities, thus overcoming the current rule-based approach. The TRESSPASS system is based on new technologies, validated and tested in three different pilots, representing the three border modalities (air, land and sea). The technological solutions envisage also Machine Learning and Computer Vision technologies in context of behaviour analytics, anomaly detection and criminal activity prediction. Considering the potential impacts that the introduction of new technologies for passengers’ border checks may have, the ethical and legal aspects have been closely monitored during the implementation of the project. The ethical considerations and the feedback from the end-users may offer valuable inputs to foster discussion within the pop AI community.
(A European AI On Demand Platform and Ecosystem) (completed, 1/1/2019 – 31/12/2021)
AI4EU is the European AI-on-demand platform of Europe that can be a source of components, research results, products and services, usable by LEAs but also by other parties (from SMEs and big companies to the public). AI4EU, thus, gives to pop AI access to the technical AI community in Europe. But it has another important aspect: it is an open ecosystem, including a variety of stakeholders.
(Optimising time-to-FLY and enhancing airport Security) (completed, 1/5/2015 – 31/7/2018)
FLYSEC developed and demonstrated an innovative, integrated and end-to-end airport security process for passengers, while enabling a guided and streamlined procedure from landside to airside and into the boarding gates, and offering for the first time an operationally validated innovative concept for end-to-end aviation security. FLYSEC achieved its ambitious goals by integrating new technologies on video surveillance, intelligent remote image processing and biometrics combined with big data analysis, open-source intelligence and crowdsourcing. The concept is based on social acceptance, legal compliance and ethics-by design; hence, the expertise and knowledge gained during the project implementation could be relevant to support discussions amongst the pop AI community.
(Αrtificial Intelligence and advanced Data Αnalytics for law enforcement agencies)(ongoing, 1/9/2019 – 31/8/2022)
AIDA ia a EU research project that aims at developing a Big Data Analysis and Analytics framework equipped with a complete set of effective, efficient and automated data mining and analytics solutions to deal with standardised investigative workflows, extensive content acquisition, information extraction and fusion, knowledge management and enrichment through novel applications of Big Data processing, Machine Learning, AI and predictive and visual analytics. The proposed solution aims at delivering a descriptive and predictive data analytics platform and related tools using state-of the art machine learning and Αrtificial Ιntelligence methods to prevent, detect, analyse, and combat criminal activities. The objective of AIDA is to significantly enhance LEAs’ capability to combat cybercrime and terrorist activities through innovations in knowledge mining, information fusion, Artificial Intelligence techniques and analytics services. Therefore, its results could be of utmost importance in the context of pop AI.
(Prediction and Visual Intelligence for Security Information) (completed, 1/9/2019 – 31/12/2021)
The mission of PREVISION is to empower the analysts and investigators of LEAs with tools and solutions not commercially available today, to handle and capitalise on the massive heterogeneous data streams that must be processed during complex crime investigations and threat risk assessments. PREVISION project is based on an iterative development methodology, which involves frequent software releases being made available to the LEA and practitioners end-users for testing and evaluation, resulting in keeping them continuously in the production loop. The findings from this project can offer valuable input in terms of specific AI-based technologies applied to the security domain, including their perception from LEAs and practitioners point of view.
(Analysis System for Gathered Raw Data) (completed, 1/9/2016 – 30/11/2020)
ASGARD aimed to contribute to LEA Technological Autonomy, by building a sustainable, long-lasting community for law enforcement agencies (LEAs) and the R&D industry. This community developed, maintained and evolved a best-of-class tool set for the extraction, fusion, exchange and analysis of Big Data, including cyber-offense data for forensic investigation. ASGARD has supported LEAs in significantly increasing their analytical capabilities. Besides the findings of the research, ASGARD can support popAI in extending its stakeholders community, thus reaching out to the ones that have been involved in the project’s activities and discussions.
(Real time Network, text and speaker Analytics for combating Organized crime) (ongoing, 1/9/2019 – 31/12/2022)
Criminals and terrorists use voice communication over different media. Determining and tracking target identities across such channels is extremely difficult, and speaker identification (SID) techniques (such as investigated in the European SiiP project) might not be effective in such challenging environments considering isolated data from one speaker only. This project proposes to combine the strengths of speaker data mining and link analysis to provide LEAs an efficient tool to track and uncover criminals and terrorists. The ROXANNE platform will be deployed and evaluated on real criminal cases, thus helping the LEAs adopt the technology in their daily work. This activity could bring significant input for pop AI, as it would allow understanding another type of applicability of AI-based technologies in security tasks, while creating synergies with the ROXANNE community.
(Values across Time and Space) (ongoing, 1/12/2020 – 30/12/2023)
VAST aims to bring (moral) values to the forefront in the field of advanced digitisation. The project focuses on citizen cultural experiences in order to study how the meaning of specific values has been expressed through different narratives. The project places emphasis in values considered fundamental for the formation of sustainable communities and enabling citizens to live well together, such as freedom, democracy, equality, tolerance, dialogue, human dignity, and the rule of law. In the discussion on an ethical use of AI in security, VAST can support popAI in gaining a more comprehensive view on the potential impact of digitalisation and similar technologies on social communities and citizens.
(Ethics for Technologies with High Socio-Economic Impact) (ongoing, 1/1/2021 – 31/12/2023)
New and emerging technologies are expected to generate new opportunities and offer a wealth of socio-economic benefits. However, in the early stages of their development, these technologies also pose a number of potential ethical challenges and societal consequences. In light of this problem, it is important to ask: how can we prioritise ethics and societal values in the design, development and deployment of new and emerging technologies, particularly those with high socio-economic impact? Ethics by design, or in other words, to bring ethical and societal values into the design and development of technology from the very beginning of the process.