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Human decision-making and governance challenges in AI-assisted invention: Insights from Romanian intellectual property experts

Angela Repanovici & Laura Leluțiu

Human Systems Management2026https://doi.org/10.1177/01672533261437677article
ABDC C
Weight
0.50

What the paper says

Objective This study examines how Romanian intellectual property experts perceive and manage the complexities of AI-assisted invention, with a focus on the challenges posed by human decision-making and governance. Methods This study employed a qualitative design, conducting semi-structured interviews with five Romanian experts from the academic, legal, and industrial sectors. Thematic analysis was performed using NVivo 12. Results Experts consistently viewed AI as a supportive tool that enhances data processing but lacks the intentionality and creativity required for inventorship. Key concerns included authorship ambiguity, risks of infringement, and the need for transparent human oversight. Participants emphasized the importance of adaptive regulatory frameworks and interdisciplinary education. Conclusion AI-assisted invention requires human-centered governance that ensures ethical accountability and legal clarity. The findings underscore the central role of human judgment and call for enhanced information literacy and institutional preparedness in managing AI-driven innovation.

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https://doi.org/https://doi.org/10.1177/01672533261437677

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@article{angela2026,
  title        = {{Human decision-making and governance challenges in AI-assisted invention: Insights from Romanian intellectual property experts}},
  author       = {Angela Repanovici & Laura Leluțiu},
  journal      = {Human Systems Management},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1177/01672533261437677},
}

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Human decision-making and governance challenges in AI-assisted invention: Insights from Romanian intellectual property experts

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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.