AI Ethics & Research Integrity Workshops (ENG Version Only)

Date & Time

2026/11/18 to 2026/11/19

AI Ethics & Research Integrity Workshops

About the Speaker

Professor Mohammad Hosseini is an Assistant Professor at Northwestern University Feinberg School of Medicine, Department of Preventive Medicine, specializing in research integrity, AI ethics, and open science. He is the Co-Editor-in-Chief of Accountability in Research and a member of the Global Young Academy. As a researcher and educator, he promotes the responsible integration of AI into research, aiming to help researchers anticipate risks, uphold scientific integrity, and engage thoughtfully with the social and environmental impacts of their work.

The CUHK Library is pleased to welcome Professor Mohammad Hosseini for two sessions on AI ethics and research integrity, featuring an interactive workshop and a talk on the responsible use of artificial intelligence in research :

Title	Date & Time	Venue	Registration
Responsible Use of AI in Medical Research Artificial intelligence (AI) is transforming medical research in numerous ways. This transformation is visible across five trends with ethical implications: AI is moving upward in the research workflow, from editing assistance toward hypothesis generation and analysis; the consistency and quality of publications are under pressure; increasingly autonomous AI agents are appearing as core contributors, supporting contributors, and even as research participants; disclosure remains a sticky and unevenly practiced issue; and AI is entering research oversight, where errors, bias, confidentiality breaches, deskilling, and unclear attribution carry particular weight. This interactive session will offer practical responses to these trends and provide an opportunity to exchange ideas and learn more about the ethical implications of using AI.	18 Nov 2026 (Wed) 2:30 p.m.–4:30 p.m.	User Education Room G/F, University Library	Register
Doing Science With Generative AI: From AI Slop to Responsible AI The increasing use of generative artificial intelligence (GenAI) in scholarship has generated concerns about the quality, integrity, and reliability of outputs. Public discussions often contrast AI slop, characterized by heavily automated, poorly validated, and low-quality content, with responsible AI use, in which researchers employ AI tools transparently, critically, and with appropriate human oversight. These should be understood as the two ends of a spectrum. Between these poles lies a range of intermediate grey practices, including what has recently been described as vibe scholarship: the production of apparently credible academic work through substantial AI assistance while the author’s engagement with, understanding of, or validation of the underlying arguments, evidence, methods, or literature may be limited. Conceptualizing AI-assisted research as a continuum provides a framework for evaluating scholarly practices based on numerous factors and can inform discussions about authorship, research integrity, peer review, and the responsible governance of AI in science.	19 Nov 2026 (Thu) 2:30 p.m.–3:30 p.m.	Zoom + User Education Room G/F, University Library	Zoom: Register In-person : Register

Title

Date & Time

Venue

Registration

Responsible Use of AI in Medical Research

Artificial intelligence (AI) is transforming medical research in numerous ways. This transformation is visible across five trends with ethical implications: AI is moving upward in the research workflow, from editing assistance toward hypothesis generation and analysis; the consistency and quality of publications are under pressure; increasingly autonomous AI agents are appearing as core contributors, supporting contributors, and even as research participants; disclosure remains a sticky and unevenly practiced issue; and AI is entering research oversight, where errors, bias, confidentiality breaches, deskilling, and unclear attribution carry particular weight.

This interactive session will offer practical responses to these trends and provide an opportunity to exchange ideas and learn more about the ethical implications of using AI.

18 Nov 2026 (Wed)
2:30 p.m.–4:30 p.m.

User Education Room
G/F, University Library

Doing Science With Generative AI: From AI Slop to Responsible AI

The increasing use of generative artificial intelligence (GenAI) in scholarship has generated concerns about the quality, integrity, and reliability of outputs. Public discussions often contrast AI slop, characterized by heavily automated, poorly validated, and low-quality content, with responsible AI use, in which researchers employ AI tools transparently, critically, and with appropriate human oversight.

These should be understood as the two ends of a spectrum. Between these poles lies a range of intermediate grey practices, including what has recently been described as vibe scholarship: the production of apparently credible academic work through substantial AI assistance while the author’s engagement with, understanding of, or validation of the underlying arguments, evidence, methods, or literature may be limited.

Conceptualizing AI-assisted research as a continuum provides a framework for evaluating scholarly practices based on numerous factors and can inform discussions about authorship, research integrity, peer review, and the responsible governance of AI in science.