The growing use of generative AI tools in research and professional contexts raises important questions about linguistic bias and consistency in model outputs. This short study explores whether the language of a prompt—specifically, English versus Hungarian—affects the content, tone, and legal precision of responses produced by a state-of-the-art
Generative AI is not only useful for content creation – it is increasingly being explored for structured data collection tasks as well. With a simple prompt, the Gemini Deep Research function can collect the requested data from publicly available sources. However, not all models can reliably complete such tasks; in fact,
When using generative AI models for academic research, one must be aware of a key limitation: their knowledge cut-off. This refers to the latest point in time up to which the model has been trained on data. Beyond this date, the model may lack awareness of significant events, publications, or
Interview metadata often arrives in semi-structured formats, making it difficult to analyse or integrate into standard research workflows. This short prompt-based approach shows how GenAI can transform a JSON file containing interview-related metadata into a clean, structured Excel (.xlsx) file—in seconds, without requiring any programming knowledge. The method enables
University lecturers can improve curriculum planning by using GenAI to create detailed assignment briefs quickly and effectively. This blog introduces a custom prompt that guides GenAI in producing a ready-to-use "AI and Ethics" group presentation brief. It shows how it saves time, incorporates real ethical dilemmas, and suggests
GenAI can be efficiently used as a learning assistant, as demonstrated by this case study. This GenAI prompt assists university students in preparing for exams by targeting a specific topic from their lecture notes. It extracts the relevant section and creates focused revision questions to support active recall and understanding.
Data pre-processing is a crucial but often tedious stage in research, particularly when standardising complex CSV datasets. This blog demonstrates how GenAI can systematically structure geographic location data directly from an input CSV file without coding. Our primary objective was to ensure consistent and accurate categorisation, preparing the data for
Natural Language Processing (NLP) allows us to automatically analyse and categorise textual data. With the help of GenAI, even complex classification tasks can now be executed using just a well-designed prompt. In this post, we present a practical example where GenAI classifies financial-related sentences into domain-specific categories, showcasing how effective
Making research accessible to a wider audience is no longer optional – it’s essential to academic life. Whether for public engagement, broader impact, or to ensure that essential findings reach beyond the academic bubble, science communication plays a vital role in connecting scholarship with society. One simple but effective way
Clustering refers to the unsupervised process of grouping similar entities, such as sentences, into categories based on shared characteristics without relying on predefined classes, thus revealing latent patterns in the data. For researchers, GenAI models enable this analysis without the need for programming expertise, offering a powerful means to explore
Recent advances in Generative AI offer researchers new opportunities to assign topic labels to political and legislative texts without manual coding or programming. The Comparative Agendas Project (CAP) provides a structured topic classification system that captures the major areas of public policy. Traditionally, applying these labels required manual annotation or
Time series analysis is a powerful tool for researchers across disciplines, yet its reliance on programming can pose a challenge for those without coding expertise. This blog demonstrates how AI-driven prompts can enable researchers to perform simple time series analyses without writing a single line of code, making data insights
