Cases for Research Integrity: Generative AI - Vol. 2

Moral Reasoning in Research Integrity Classes


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Date

2025

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Educational Material

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yes

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Abstract

Generative AI now contributes to every phase of the research lifecycle—from digital image enhancement and synthetic media production to automated data gathering, analysis, and manuscript drafting. Such capabilities promise greater efficiency and novel insights but also give rise to complex ethical and regulatory challenges. Volume 2 addresses these challenges through eight carefully constructed case studies: • Image Editing and Gen AI: Navigating Ethical Challenges in Scientific Image Preparation • Is this science? AI-Generated Images in Scientific Communication • Data Feasts and Fair Use Series o Case 1: The New York Times vs. OpenAI o Case 2: Reddit Experiment o Case 3: ETHZ Library Licensing & Text-and-Data Mining • The Human Paradox: Objective Instruments, Subjective Minds • Automation of the Research Cycle: Opportunity or Risk? • Deepfakes: Concerns of Regulation, Consent, and Transparency Each case study comprises a concise narrative framing real or factual scenario; an analytical exposition of the principal ethical issues, accompanied by graduated discussion questions and references for further reading recommendations.

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published

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Zurich-Basel Plant Science Center, ETH Zurich

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02222 - Zurich-Basel Plant Science Center / Zurich-Basel Plant Science Center

Notes

With contribution of Réka Mihálka and Paulina Zybinska.

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