About
Adrian explores the evolving meaning of authorship in an academic environment increasingly influenced by artificial intelligence.
His areas of interest include AI-assisted writing, human intellectual contribution, academic originality, authorship verification, and the challenges of evaluating how written work is produced.
Through practical examples and academic scenarios, Adrian examines how educators, researchers, and institutions can distinguish between technological indicators and meaningful evidence when questions about authorship arise.
He emphasizes that similarity scores, AI-content indicators, and changes in writing patterns should not be treated as definitive proof of misconduct. Instead, responsible evaluation requires transparency, contextual understanding, appropriate documentation, and fair opportunities for individuals to explain their work.
His sessions encourage thoughtful conversations about maintaining academic integrity while recognizing the changing tools and processes involved in modern research and writing.
Sessions
When Writing Style Suddenly Changes: What Should We Do Next?
A sudden change in writing style may raise questions, but it does not automatically establish misconduct. This session explores how educators and academic reviewers can interpret writing-pattern changes responsibly, consider context, and determine appropriate next steps.
Authorship in the Age of Generative AI
As AI becomes part of research and academic writing, institutions need to reconsider how authorship and contribution are understood. This session explores responsible AI assistance, attribution, transparency, and the evolving expectations surrounding academic authorship.
Who Actually Wrote the Paper?
Generative AI is challenging traditional assumptions about academic authorship. This session explores what meaningful authorship means when AI can contribute to writing and why understanding human contribution, transparency, and verification matters.