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How social science academics use AI – Activities and tools

Erika Janiūnienė et al.

Journal of Information Science2026https://doi.org/10.1177/01655515251396892article
AJG 2
Weight
0.50

What the paper says

This study examines generative AI integration in Lithuania’s social sciences research and education following ChatGPT’s 2022 release, exploring usage patterns and challenges faced by researchers. Semi-structured interviews were conducted with 13 Vilnius University social sciences faculty members, selected for diverse AI-related expertise. Content analysis examined perceptions, roles and ethical considerations of AI use in academic activities. AI was perceived as valuable for information-seeking and research productivity, but tensions exist between adoption benefits and challenges related to academic integrity, methodological standards and variable output quality. Participants emphasised the need for clearer AI usage norms. Generative AI integration in social science research at Vilnius University presents significant opportunities and challenges. Addressing tensions between effort-saving and competence acquisition, unclear guidelines and AI output reliability is crucial for positive academic AI utilisation. The research highlights the importance of comprehensive guidelines and enhanced digital literacy to take advantage of AI benefits while maintaining academic integrity.

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https://doi.org/https://doi.org/10.1177/01655515251396892

Or copy a formatted citation

@article{erika2026,
  title        = {{How social science academics use AI – Activities and tools}},
  author       = {Erika Janiūnienė et al.},
  journal      = {Journal of Information Science},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1177/01655515251396892},
}

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How social science academics use AI – Activities and tools

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.