Osoba:
Urban, Adam

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Urban
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Adam
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Nyní se zobrazuje 1 - 3 z 3
  • PublikaceOtevřený přístup
    Introduction into AI tools for academia
    (National Library of Technology, 2024) Urban, Adam
    This presentation provides an introductory exploration into generative AI tools and their practical applications within academic research. Attendees will gain insight into the capabilities of prompt-based searches, enabling efficient and precise information retrieval. Additionally, the session will cover mapping tools that facilitate data visualization and analysis, and delve into text analysis techniques, demonstrating how AI can streamline and enhance content evaluation and interpretation.
  • PublikaceOtevřený přístup
    AI Essentials for Academia
    (National Library of Technology, 2025) Skládalová, Eliška; Urban, Adam
    This webinar is tailored for doctoral candidates, researchers, and students interested in integrating artificial intelligence into their academic workflows. The first part introduces large language models, explaining how they function, how they differ, what to watch out for when using them, and the basics of prompt engineering. The second part focuses on AI ethics, associated risks, emerging regulations, ethical frameworks in academia, and how to appropriately cite AI tools.
  • PublikaceOtevřený přístup
    Reskilling for the AI Era
    (National Library of Technology, 2025) Urban, Adam; Skládalová, Eliška
    This poster presents preliminary findings from an exploratory study on how academic library staff at the National Library of Technology (NTK) in the Czech Republic are reskilling and adapting to the challenges presented by AI. As AI technologies become more prevalent in information services provision, this poster sheds light on the ways NTK academic library staff are navigating the multifaceted challenges and opportunities associated with integrating AI into their professional practices while understanding how our patrons use emerging tools and how this changes research practices more generally. The objective of our research, in the form of qualitative semi-structured interviews, was to understand the reskilling needs and processes of our user support staff as they were adapting to the integration of AI technologies in our workflows. A diverse sample of interviewees was ensured by interviewing staff with different genders, levels of experience, and lengths of service. This methodological approach gave us an in-depth probe of evolving individual experiences, motivations, barriers, and mechanisms of knowledge transfer that are pivotal in the reskilling process.