About
An ERA-curated thematic profile exploring the challenges of maintaining research integrity in an increasingly AI-enabled academic environment. Sessions examine responsible AI use, research credibility, verification, ethical boundaries, and the practices researchers and institutions need to protect trust in scholarly work.
Focus: Research integrity, responsible AI use, academic misconduct, research verification, scholarly ethics, and trustworthy academic practices.
Sessions
Academic Misconduct or Responsible AI Use? Where Is the Boundary?
As AI becomes part of academic work, distinguishing acceptable assistance from misconduct is increasingly complex. This session explores how researchers and institutions can evaluate AI use through transparency, contribution, institutional expectations, and human judgment.
The New Integrity Risks Researchers Need to Recognize
AI-assisted research introduces new questions about transparency, attribution, evidence, and responsibility. This session explores emerging research integrity risks and the practical warning signs researchers should recognize.
When Research Looks Credible but Isn't
A polished research paper can contain convincing arguments, references, and evidence that do not withstand scrutiny. This session explores why apparent credibility is not enough and how researchers can evaluate claims, sources, and supporting evidence more carefully.
Research Integrity After Generative AI
Generative AI is changing how research is written, reviewed, and communicated. This session explores emerging integrity challenges and how researchers and institutions can respond through stronger verification, responsible practices, and informed judgment.