AI4Gov-X Extracurricular Activities

1) Identify and explain possible ethical issues in AI design and development.
2) Analyze what ethical issues could arise in AI applications.
3) Determine steps to take for more responsible use of AI applications
4) Apply the steps involved in responsible AI design

1) Apply human-centered design and agile methods to public sector challenges.
2) Identify user needs and stakeholder perspectives in service design.
3) Generate and develop innovative ideas through structured ideation techniques.
4) Design, prototype, and (simulate) test solutions to real institutional challenges.
5) Collaborate effectively within teams and with external innovation stakeholders.
6) Develop actionable solutions and contribute to an institutional innovation playbook.

1) Explain and critically assess the principles, benefits, and challenges of publishing and managing legal sources on the web using structured technologies
2) Apply XML-based standards, particularly Akoma Ntoso, to structure and annotate legislative documents in a consistent and interoperable way
3) Design and implement identification and metadata schemes for legal resources using URIs and Semantic Web standards such as Resource Description Framework (RDF)
4) Model the structure, lifecycle, and interconnections of legal sources, including naming conventions, normative references, and legislative changes
5) Develop and evaluate basic ontologies for the legal domain using Web Ontology Language (OWL), applying established design patterns and best practices. Integrate legal markup, metadata, and semantic models into a coherent project, and communicate and justify design choices using appropriate legal and technical reasoning. Considering these ILOs, the emerging learning profile is that of a legislative office manager who intends to fully understand the potential of Semantic Web technologies, or an ICT manager who intends to master the operational methods and then create projects aimed at the dematerialization of legal documents. The primary objective is training in technological innovation in legal document management in parliaments, public administrations, legal publishing houses, and official bodies publishing legislative acts. Teaching modules include the following: Introductive overview of XML; Introductive overview of URI, RDF and OWL; Structure, naming, processes in the legal domain; Semantic Web for the law; Legal Knowledge Management

1) Understand the key concepts and processes of digital entrepreneurship and AI-enabled innovation;
2) Identify and analyse real-world problems and opportunities suitable for AI-driven business solutions;
3) Design and develop innovative start-up ideas using data-driven and AI-based approaches;
4) Apply basic principles of business modelling, value proposition design, and market validation;
5) Develop and present a structured pitch deck for an AI-enabled venture;
6) Evaluate digital marketing and growth strategies, including AI-driven and data-informed approaches;
7) Collaborate effectively in multidisciplinary teams for the development of entrepreneurial ideas;
8) Critically assess the feasibility, impact, and scalability of AI-enabled business concepts.

1) Understand the key concepts, architectures, and applications of artificial intelligence and data-driven technologies in digital government;
2) Analyse how AI and emerging ICTs transform public administration, policymaking, and service delivery;
3) Apply basic techniques of data-driven decision-making, policy modelling, and simulation in governance contexts;
4) Critically assess the ethical, legal, and societal implications of AI in the public sector, including issues of transparency, accountability, bias, and privacy;
5) Explore the role of large language models, big data, and intelligent systems in supporting citizen engagement and e-democracy;
6) Identify opportunities and challenges for implementing AI-enabled solutions in real-world governmental settings;
7) Collaborate across disciplines and contribute to discussions on open, participatory, and collaborative governance.

TBD

1) Explain AI and its role in public services (Bloom: Understand | A1) Explain the fundamental principles of Artificial Intelligence and describe its role within public service delivery and administrative processes.
2) Contextualise AI in governance and society (Bloom: Analyse | A1 → E1) Analyse the relationship between AI technologies, public values, and political-administrative contexts, including implications for democratic governance.
3) Assess opportunities and limitations of AI (Bloom: Analyse | A1) Assess where AI applications can enhance public services and identify contexts in which their use may be ineffective or detrimental.
4) Apply risk–opportunity frameworks (Bloom: Apply | A1 → C4) Apply risk–opportunity frameworks to evaluate AI and algorithmic applications in public-sector use cases.
5) Evaluate ethical and societal risks (Bloom: Evaluate | E1) Evaluate ethical, legal, and societal risks of AI in public services, including bias, inequality, transparency, and accountability.
6) Propose improvements to AI-enabled processes (Bloom: Evaluate / Create | C4) Propose improvements to AI-enabled public service processes based on principles of quality management and continuous improvement.
7) Explain and critically assess regulatory and governance approaches (Bloom: Understand / Evaluate | E1 → C4) Explain and critically assess regulatory and governance approaches for AI in public administration, including existing tools such as audits, standards, and compliance mechanisms.

1) Analyse the role of science and technology diplomacy in addressing global challenges, and explain its main dimensions—science in diplomacy, diplomacy for science, and science for diplomacy—in a context increasingly shaped by AI and digital technologies.
2) Evaluate how full-stack AI influences international relations, geopolitical competition, regulatory debates, and technological sovereignty across the different layers of the AI value chain.
3) Critically assess the ethical, regulatory, and strategic implications of AI both as a subject of diplomatic negotiation and as a tool that transforms diplomatic practice.
4) Apply interdisciplinary methods and evidence-based reasoning to examine case studies, scenarios, stakeholders, and policy challenges at the intersection of AI, science, and international affairs, and communicate complex issues effectively to policy and diplomatic audiences.

1) Explain the core concepts of digital transformation, digital identity, and trust services (eID, eSignature, eSeal) and their role in secure public service delivery. Analyse public sector use cases to determine where AI, trust services, and digital identity can be effectively and responsibly applied.
2) Apply relevant legal and regulatory frameworks (e.g. eIDAS, EU AI Act principles) to assess compliance, accountability, and risk in digital public services. Evaluate different approaches to AI-enabled service design, ensuring human oversight, transparency, and citizen-centred outcomes.
3) Design a concept for an AI-enabled public service that integrates trust services and digital identity while ensuring security, usability, and public trust.