Planning the parliament of the future in greece – considerations for a data-driven Hellenic Parliament
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Presented on 1 July 2025 at the 12th International Summer School on Digital Government OpenGov2025
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Planning the parliament of the future in greece – considerations for a data-driven Hellenic Parliament
- 1. PLANNING THE PARLIAMENT OF THE FUTURE IN GREECE – CONSIDERATIONS FOR A DATA- DRIVEN HELLENIC PARLIAMENT 12th International Summer School on Digital Government OpenGov2025 Dr. Fotis Fitsilis Hellenic Parliament 1 July 2025
- 2. OUTLINE • Background, motivation and current topics. • Motivation for introducing AI in parliaments. • State of the art. • European examples. • Development of guidelines and frameworks. • Future steps. 2
- 3. TECHNOLOGICAL BACKGROUND • Artificial Intelligence is a bundle of technologies, methods and system architectures aimed at replicating aspects of human intelligence using computational power. • This includes learning methods like machine learning and deep learning; pattern recognition algorithms and natural language processing; and architectures such as neural networks, agent systems and hybrid models. • Goal: To create systems that autonomously or when instructed perform specific tasks, e.g., through analysis of large datasets, natural language interaction and support decision-making in complex environments. • Purpose: To support human activities and processes, particularly in administration, business, research or everyday life 3
- 4. MOTIVATION AND CURRENT TOPICS • The use of tools such as LLAMA, Claude, Mistral, ChatGPT and other large language models is gaining importance and entering the public sector, including parliamentary workflows. • There is a broad demand for clear rules governing AI use in parliaments to protect democratic values. • Ethical questions, data protection (especially personal data), algorithmic biases and upholding democratic principles are at the center of the debate. • The aim is to create a legal and operational framework that promotes innovation while minimizing risks and ensuring parliamentary sovereignty. 4
- 5. WHAT DEFINES AN AI EXPERT TODAY? • An AI expert is more than just a data scientist or programmer. • It is an interdisciplinary profile combining technical, analytical, social science and strategic competencies. A typical AI profile includes: • Technical know-how: Proficiency in Python or R, understanding algorithms, statistics and machine learning. • Linguistic competence: Knowledge of LLMs and natural language modeling by linguists or computational linguists. • Social sciences insight: Analysis of AI's impact on people, organizational culture and ethical implications. • Strategic thinking: Understanding digital transformation, HR, leadership culture, project and change management. • Engineering & infrastructure: Integration into systems, hardware selection and ensuring security and privacy. 5
- 6. AI IN ORGANIZATIONAL CHANGE • AI takes over specific tasks, not entire professions. This allows staff to focus more on creative, strategic or social aspects of their work. • Targeted use of AI can significantly accelerate workflows and improve precision, e.g., through automated analysis or intelligent decision-support systems. • Rather than replacing, AI extends existing roles. New skill profiles emerge and up- or reskilling become essential. • Technological and economic benefits of AI are unevenly distributed. • Without proper measures, social and economic divides may deepen. 6
- 7. THE GLOBAL AI INVESTMENT RACE • Examples of major current AI infrastructure investments: US “Stargate” project (Jan 2025): $500B investment. • EU’s response (planned budget: €200B). • Goal: Build sovereign EU infrastructure for generative AI (13 AI factories; 5 gigafactories) • Co-funded infrastructure projects. • Public and private access under clear legal frameworks. 7
- 8. GREECE • AI Factory “Pharos”. • Being constructed in Lavrion. • Linked to the development and training of Greek LLMs. • The Hellenic Parliament (HeP) was the first public organization that announced (Apr 2025) and pushes forward (MoU, May 2025) its collaboration with the Greek AI factory. 8
- 9. STATE OF THE ART – AI TECHNOLOGIES • Several documented AI solutions already exist in parliaments, including text analysis, speech-to-text and predictive analytics. • Besides LLMs like ChatGPT, other tools include OCR, NLP and ML techniques. • Cloud-based AI services (SaaS) and hybrid architectures (local + cloud) are increasingly used. • Challenges: Data security (especially when outsourcing); Bias in training data; Lack of transparency (black-box problem); Ethical trade-offs between efficiency and democratic oversight; European specificities: multilingualism and multiple legal traditions. 9
- 10. LLM DEPLOYMENT OPTIONS • Buy end-to-end app (no LLM control). • Buy app with limited LLM control. • Build own app, integrate controllable LLM via APIs. • Develop app + fine-tune LLM. • Build both app and LLM from scratch (pre-training). (Source: Chang/Pflugfelder 2023) 10
- 11. AI IN PARLIAMENTS – TIMELINE • Early Phase (2001–2023): Research & conceptual work in various national parliaments (e.g., Greece, Canada, Argentina). • 2022: Focus on supportive tools like machine translation, document digitization, speech-to-text. • 2024: Growing AI use in core processes: briefings, legislative drafting, summarization, classification and others. • Current: Heterogeneous progress globally; growing role for generative AI. 11
- 12. GLOBAL USE OF PARLIAMENTARY AI 2022 Study: 39 use cases (Fitsilis & de Almeda, 2024) 12 2024 Study: 65 use cases (Fitsilis, 2025)
- 13. EUROPEAN PARLIAMENTARY EXAMPLES • Greece: 'Demosthenes' transcription system. • Finland: AI hearings on UN 2030 Agenda. • Netherlands: Automated reporting. • Italy: Law classification. • European Parliament: “Archibot” public access tool. 13
- 14. MOTIVATION FOR GUIDELINES • Ensure AI supports, not replaces democratic processes. • Promote unified practices and interoperable systems for better cooperation. • Guarantee transparency (explainable AI), fairness (bias reduction) and rights protection. • AI should strengthen representative democracy, especially via public engagement. • EU AI Act will regulate AI in public sector & parliaments (starting August 2024 / 2026). • Translated in Greek for application within HeP. 14
- 15. GUIDELINE DEVELOPMENT AND STRUCTURE • Created by 22 parliamentary experts from 16 countries in a participatory process, using crowdsourcing methods. • Based on: Scientific frameworks (EU, UNESCO, OECD); Corporate principles (IBM, Google, Microsoft); Practical pilot project experiences. • 40 guidelines, grouped into 6 sections. • Key questions per guideline: • Why is this guideline important? • Are there examples? • How can it be implemented? • What additional considerations apply? 15
- 16. FUTURE STEPS AND DEVELOPMENTS • Next version of the guidelines will focus on implementation (2025/2026). • Apply AI technologies in parliamentary apps in line with the guidelines. • Expand language availability (French, Italian, Arabic, Swahili, …). • Create training programs for public administrators on AI skills and usage ethics. • Public awareness campaigns on AI in parliaments. • Develop metrics to measure effectiveness and compliance. • Knowledge transfer to the Hellenic Parliament. 16
- 17. SUMMARY AND CONCLUSION • With responsible use, AI can make parliaments more efficient, transparent and citizen-focused. • Harmonization among national parliaments (this also includes HeP!) and EU institutions is necessary (see also Interoperability Act). • A trade-off between ParlTech progress, operational efficiency and democratic control must be determined. • Guidelines and frameworks must evolve with technology (e.g., generative/agentic AI) and social expectations. • Parliaments have the opportunity to set standards for other state institutions through exemplary AI governance (a great opportunity for HeP). 17
- 18. CONTACT AND RESOURCES Thank you for your attention! Contact: [email protected] Guidelines: https://www.wfd.org/ai-guidelines-parliaments Hellenic OCR Team: https://hellenicocrteam.gr Disclaimer: This presentation reflects the author's personal views and not necessarily those of his institution. 18