Month: September 2025

27 September 2025 – Generative AI Workshop at the LĂĄtkĂ©p (Panorama) Art History Festival

From 25 to 27 September 2025, the LĂĄtkĂ©p (Panorama) – Art History Festival was held for the second time in Budapest, this year focusing on digitalisation and technological innovation. As part of the festival, on 27 September, poltextLAB organised a Generative AI workshop titled “The Future of Visual Arts: AI-based Digital Solutions”. The workshop demonstrated how generative artificial intelligence (GenAI) – such as Stable Diffusion, Midjourney, and similar models – is transforming both research and creative processes in the visual arts. Participants were introduced to concrete examples of the scientific use of these tools, including image classification and linking to metadata, object recognition in paintings with the help of GenAI, and producing iconographic descriptions based on images. The session also emphasised discussion of scientific integrity, transparency of data sources, and the ethical issues that arise from the application of generative AI.

25-26 September 2025 – MiklĂłs SebƑk on using AI for metadata management at CafĂ© de la donnĂ©e at Sciences Po, Paris

On 25 September 2025, the Centre for Socio-Political Data (CSDP) hosted a discussion titled CafĂ© de la donnĂ©e on the topic of AI and social science metadata. Short presentations were delivered by researchers from several institutions – including Inserm, INSEE, and poltextLAB. Representing poltextLAB, MiklĂłs SebƑk demonstrated how artificial intelligence can support the better organisation and easier accessibility of research data. The event was interactive: participants not only listened to presentations but also engaged in a joint discussion. The following day, 26 September 2025, the first meeting of the FAIRwDDI scientific and technical board took place at Sciences Po in Paris. Participants discussed how to align the description of research data (also known as metadata) with the international FAIR principles. These principles ensure that data can be easily found, accessed, linked, and reused. The meeting aimed to define common directions for the future management of social science data.Both events highlighted that artificial intelligence and well-structured metadata play a key role in making social science research more efficient, transparent, and accessible in the future.

24 September 2025 – WORKSHOP on NLP and AI at the University of Namur, HELD BY mIKLÓS SEBƐK

On 24 September 2025, Miklós SebƑk, Research Professor at the ELTE Centre for Social Sciences, delivered a workshop titled Using advanced AI solutions for text-based social and economic research at the University of Namur. The event introduced participants to conceptual foundations of generative AI, the current state of large language models (LLMs), and their application in content classification, literature search, and applied regressions. SebƑk compared API-based and local uses of LLMs and discussed the role of AI agents in data collection. The workshop was designed as a hands-on session accessible to all levels, from beginners to advanced researchers.

23 September 2025 – MiklĂłs SebƑk’s presentation on AI-supported classification in social research at the University of Namur

On 23 September 2025, Miklós SebƑk delivered a lecture at the University of Namur as part of the “Methods Seminar” series. His talk, titled Solving classification problems for social and economic research with the Babel Machine, introduced how natural language processing and large language models can be applied to the analysis of social science and economic data. He also outlined the potential of AI-driven multilingual tools for addressing classification challenges in empirical research, with examples from ongoing projects. The presentation illustrated how machine learning methods expand opportunities for computational social science by enabling richer and more scalable text analysis.

17 September 2025 – Registration open: Generative AI COURSE at Corvinus University

On October 7, 2025, poltextLAB will hold a full-day training on Generative Artificial Intelligence (GenAI) at Corvinus University of Budapest. The program is designed for researchers and professionals who work with documents, writing, or data and want to understand how generative AI can be applied in their everyday work. The training will provide an introduction to the fundamentals of generative models, hands-on practice in prompt engineering and model selection, and practical examples of research applications. It will also address key ethical and legal issues, including data protection, intellectual property, and proper citation practices. More details and registration: https://bit.ly/4n3Du7E

3 SEPTEMBER 2025 – ANNA TAKÁCS’S PRESENTATION AT THE METRISTP WORKSHOP IN NAPLES

On September 3, 2025, Anna TakĂĄcs gave a presentation titled “From Crisis-Exploitation to Sticky Narratives: A Research Agenda for the Comparative Study of Policy Crises and Illiberal Policy Frames” at the MetRiSTP workshop titled Methods for Political Science Research in the Age of Artificial Intelligence. The presented paper examines the illiberal framing in parliamentary speeches on immigration and the COVID-19 pandemic in Austria, Germany, Hungary, and the United States.

25-26 August 2025 – Nathalie Neptune’S participation in the Causal Inference Workshop

On August 25 and 26, 2025, Nathalie Neptune attended the Causal Modelling and Inference Workshop, which brought together researchers working in statistics, machine learning, and social science, in Paris, France. The workshop featured presentations on causal discovery for time series, counterfactual modeling, and causal representation learning. While much of the work is still ongoing, the event highlighted promising directions for integrating causal inference into multimodal research. For the Integrating Geospatial Data and Legislative Text project on Hungarian forestry and fire management, the most relevant takeaways were the applications of causal time-series methods. These approaches could strengthen the project’s analysis of how forest and fire policies interact with environmental outcomes, and set the stage for future use of causal ML with satellite image time-series. This research is supported by the Hungarian Academy of Sciences Distinguished Guest Scientists Fellowship Programme.