In the modern day and age, cybersecurity facesnumerous challenges. Computer systems and networks become more and more sophisticated and interconnected, and the attack surface constantly increases. In addition, cyber-attacks keep growing in complexity and scale. In order to address these challenges, security professionals started to employ generative AI (GenAI) to quickly respond to attacks. However, this introduces challenges in terms of how GenAI can be adapted to the security environment and where the legal and ethical responsibilities lie. The Universities of Twente and Groningen and the Hanze University of Applied Sciences have initiated an interdisciplinary research project to investigate the legal and technical aspects of these LLMs in the cybersecurity domain and develop an advanced AI-powered tool.
A musical improvisation inspired by a beautifulsummer day or by a song by Elvis; for patientsadmitted in hospital for an operation, music canhave healing powers. With the research projectMeaningful Music in Health Care (MiMiC), thattook place from autumn 2015 until 2018, the researchgroup Lifelong Learning in Music (LLM), togetherwith the department of surgery of the UniversityMedical Center Groningen (UMCG), researched thepractice of live music for hospital patients and theirhealth care professionals. For the research groupLifelong Learning in Music the focus of the researchwas on the meaning of this musical practice formusicians and health care professionals, and onthe development of this practice.The research of UMCG concentrated on the effectsof live music on the recovery and wellbeing of patients
We examine the ideological differences in the debate surrounding large language models (LLMs) and AI regulation, focusing on the contrasting positions of the Future of Life Institute (FLI) and the Distributed AI Research (DAIR) institute. The study employs a humanistic HCI methodology, applying narrative theory to HCI-related topics and analyzing the political differences between FLI and DAIR, as they are brought to bear on research on LLMs. Two conceptual lenses, “existential risk” and “ongoing harm,” are applied to reveal differing perspectives on AI's societal and cultural significance. Adopting a longtermist perspective, FLI prioritizes preventing existential risks, whereas DAIR emphasizes addressing ongoing harm and human rights violations. The analysis further discusses these organizations’ stances on risk priorities, AI regulation, and attribution of responsibility, ultimately revealing the diverse ideological underpinnings of the AI and LLMs debate. Our analysis highlights the need for more studies of longtermism's impact on vulnerable populations, and we urge HCI researchers to consider the subtle yet significant differences in the discourse on LLMs.
Developing a framework that integrates Advanced Language Models into the qualitative research process.Qualitative research, vital for understanding complex phenomena, is often limited by labour-intensive data collection, transcription, and analysis processes. This hinders scalability, accessibility, and efficiency in both academic and industry contexts. As a result, insights are often delayed or incomplete, impacting decision-making, policy development, and innovation. The lack of tools to enhance accuracy and reduce human error exacerbates these challenges, particularly for projects requiring large datasets or quick iterations. Addressing these inefficiencies through AI-driven solutions like AIDA can empower researchers, enhance outcomes, and make qualitative research more inclusive, impactful, and efficient.The AIDA project enhances qualitative research by integrating AI technologies to streamline transcription, coding, and analysis processes. This innovation enables researchers to analyse larger datasets with greater efficiency and accuracy, providing faster and more comprehensive insights. By reducing manual effort and human error, AIDA empowers organisations to make informed decisions and implement evidence-based policies more effectively. Its scalability supports diverse societal and industry applications, from healthcare to market research, fostering innovation and addressing complex challenges. Ultimately, AIDA contributes to improving research quality, accessibility, and societal relevance, driving advancements across multiple sectors.
