Human–AI Relations Research Group

Official, full name of the research group: Human– Artificial Intelligence Relations Research Group

The primary objective of the research group is to examine the individual and social consequences of the rapid spread of artificial intelligence (AI) – with particular emphasis on generative AI and large language models (LLMs) – from a psychological perspective. Our focus is on everyday interactions with various content-generating systems and how this technology influences thinking, decision-making processes, learning and teaching, work, social relationships, psychological diagnostic methods, and psychotherapy. Our goal is to explore and understand the psychological implications of generative AI, the changes in human cognition, emotions, and behavior that occur when interacting with AI systems, as well as their applications in research and practice.

Main research areas and activities:

  • Social relationships and the anthropomorphization of AI (chatbots as social and supportive partners, perception and interpretation of AI systems, attitudes toward them, mechanisms of anthropomorphization, perceived social support, therapeutic chatbots, issues related to guidelines in helping professions)

  • Trust, persuasion, and the information environment (technology adoption and related attitudes, empirical examination of cognitive and emotional effects, information processing, identification of psychological protective factors against disinformation, credibility perception, source-critical analysis of AI-generated content, management of hallucinations)

  • Generative AI in education, research, and skill development (personalized learning support, academic integrity, AI literacy, development of critical thinking and learning strategies, possibilities for educational implementation and their impact assessment, use as a research assistant)

  • Organizational and workplace applications (generative AI as a coworker, sense of responsibility, perceived control, decision support, technostress)

  • Ethics, bias, vulnerable user groups (ethical dilemmas, biases in generative systems, transparency, addictive usage patterns, studies on specific target groups – such as differences related to age, digital competence, and psychological characteristics [e.g., individuals with narcissistic personality disorder], AI-related phobias and irrational fears)

  • Diagnostic and psychological measures and assessments supported by generative AI (mental health support, analysis of measuring instruments, qualitative data analysis, pattern recognition)

Methodological approach:

The research group operates within a multidisciplinary framework: drawing on theoretical perspectives from cognitive and social psychology, clinical psychology, education, and the broader social sciences. Our mixed-methods approach encompasses a wide range of methodologies, from psychological experiments to questionnaire-based, longitudinal, and qualitative methods, as well as computational content and text analysis. A key priority of the group is the development, adaptation, and validation of new measurement instruments, alongside the evaluation of interventions (e.g., brief training programs and educational modules), with a focus on the rapid practical applicability of research findings.

Research group leaders:

  • Dr. Kálmán Abari – assistant professor
  • Szilvia Hujber-Mitru – assistant lecturer

Research group members:

  • Dr. Tünde Éva Polonyi – associate professor
  • Dr. Anita Szemán-Nagy – associate professor
  • Lilla Kegyes – assistant lecturer
  • Viktor Havan – MA student in Psychology
  • Kevin Dominik Kiss – MA student in Psychology
  • Panna Lengyel – MA student in Psychology
  • Letícia Lengyel – BA student in Psychology
  • Rishona Koshy – BA student in psychology

Research group contact information:

  • hujber-mitru.szilvia@arts.unideb.hu
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