Bridging disciplines for positive societal impact with crypto-economic intelligence research
Dr. Frédérik Sinan Bernard
Postdoctoral Fellow, IEBIS Section, University of Twente.
Blockchain technology, now commonly accepted as a major disruption in several fields of science, notably due to its characteristic as a technological layer for data storage and leverage, is a particularly interesting candidate for transdisciplinary research. Economic intelligence (EI) as a field of study also is, by nature, transdisciplinary. This field, which focuses on the set of activities involving the collection, analysis, dissemination of strategic information to enhance, in offensive and defensive practices, the competitiveness of businesses and nations, widely involves the private sector, the public sector and academia - although most often in very disconnected ways; and even more so at the European level. Considering the impact blockchain already has and will likely have even further in the various (public & private) sectors of activities, this disruption provides the opportunity (if not the necessity) to (re)discover the field of EI and bring together stakeholders, experts and academics to join forces in ensuring that technology disruptions have a positive impact on how we perceive, model, plan and act in the world we live in - while attempting to remain conscious of the tactical and strategic risks and opportunities such technological advances bring forth, as we go through them. This talk is a presentation of crypto-economic intelligence (CEI) as an avenue for research, as defended by Dr. Bernard during his PhD, aimed to a wide audience interested in these topics, to reflect on how research should be coordinated and structured, with an open ended invitation to participate and engage around this field. The objective is to participate in the debate to ensure that future European EI systems adapt and incorporate CEI considerations in their frameworks, to at least try to strike a balance between fair and robust competitive environments, safeguard national interests, consider the increasing privacy concerns and move forward coherently with relevant research objectives in the field of blockchain.
Dr. Frédérik Sinan Bernard started his post-doctoral researcher position at the University of Twente (NL) in May 2024. He finished his PhD in 2022 at the Centre d'Études Diplomatiques et Stratégiques (CEDS) in Paris, working on the conceptualization of the impact of crypto-economics as a new subfield of economics and the introduction of blockchain technology within different systems of national economic intelligence. He recently developed the MPA program entitled "Geopolitics of Crypto-Economics" at CEDS, scheduled to be launched for the first time 2024-2025, is involved in several non-profits (core member of Paris Blockchain Society, fellow for Turkey of Blockchain for Good, founding member of Lisbon Art Weekend).
Semantic Interoperability and eXplainable Artificial Intelligence in food systems or food recommenders
Donika Xhani
Ph.D. Candidate, IEBIS Section, University of Twente.
The food system is a complex network involving diverse stakeholders and processes, generating extensive data at every stage of the supply chain. This data presents an opportunity for the application of recommender systems, which are widely used to deliver relevant content to users. In the context of food systems, these recommender systems are employed to suggest food items, recipes, or diet plans tailored to user needs. However, current systems often lack transparency in their decision-making processes and fail to adequately personalize recommendations by considering users' dietary needs, preferences, or cultural backgrounds. To address these issues, it is essential to incorporate semantic reasoning and eXplainable Artificial Intelligence (XAI) into food recommender systems. XAI aims to make machine learning algorithms more explainable and understandable to humans, while semantic reasoning can be enhanced through the use of ontologies, which define the underlying semantics in a system clearly and precisely. This Systematic Literature Review (SLR) aims to identify the components of the food supply chain, existing ontologies and knowledge graphs used in food supply chains or food recommenders, and XAI methods employed to make the outputs of recommender systems comprehensible to users. By exploring these aspects, the SLR seeks to improve the effectiveness and trustworthiness of food recommender systems.
Donika Xhani obtained her bachelor’s degree in Business Information in 2019. Later on, in 2021, she obtained her master’s degree in Business Information Technology (BIT) with the specialization in IT management and Enterprise Architecture. After her MSc, she pursued an EngD in BIT, within the Semantics, Cybersecurity and Services (SCS) group in the EEMCS faculty, UT. The topic of her EngD thesis is “Ontology Engineering for eXplainable Artificial Intelligence in Tyre Engineering”. Since the 1st of December 2023, she is a PhD student in the IEBIS group, and the topic of her PhD is “Next Generation Cross-Sectoral Data Platform for the Agriculture Sector”, which is part of the 4TU.Redesign project.