📖 Module 2: Essential Resources
Ethics and GenAI
How to Use This Resource Library
This resource library is organized into three tiers — Essential, Recommended, and Optional — to help you plan your available class time and meet your students’ needs. Essential materials form the core of the module and directly address the learning outcomes. Recommended materials add depth. Optional materials extend the module or offer additional support to students.
The materials below are the Essential resources for Module 2. There are 3 sections: Academic Integrity and GenAI, Ethics and GenAI, and Citing GenAI. Each entry includes a brief description to help you decide how and when to use it.
Section 1: Academic Integrity and GenAI
💻 Instructor Preparation
📚 Readings
Guidance for Faculty on Addressing GenAI-Related Academic Integrity Issues (Harvard Bok Center) 🔗[ https://bokcenter.harvard.edu/guidance-faculty-addressing-ai-related-academic-integrity-issues]
Harvard’s faculty guidance on preventing and addressing GenAI-related academic integrity violations. A practical resource for thinking through policy, communication, and response strategies in your own courses.
GenAI Bias and Discrimination Across Industries (ScienceDirect) 🔗 [https://www.sciencedirect.com/science/article/pii/S2667096823000125]
A qualitative study examining how GenAI biases and vulnerabilities manifest across industries, contributing to gender bias and racial discrimination. Describes the different types of biases and emphasizes the importance of responsible GenAI use in organizations. Useful background for teaching the ethics and equity dimensions of GenAI literacy.
Federal Guidance on GenAI Discrimination in Education (U.S. Department of Education) 🔗[https://files.eric.ed.gov/fulltext/ED661946.pdf]
Federal guidance on GenAI discrimination in education under Title VI (race/color/national origin), Title IX (sex), and Section 504 (disability). Provides 21 detailed examples of potentially discriminatory GenAI use in educational settings. An essential resource for understanding legal obligations and equity risks when implementing GenAI in the classroom.
📝 Student Materials
📽️ Videos
Integrity First: Using GenAI Ethically in College (Cannon Library SLU, ~15 min.) 🔗 [https://www.youtube.com/watch?v=fz0ZOdY7q-c]
A video built around a single core question: Who is doing the thinking right now? An excellent pre-class viewing prompt to spark reflection on academic integrity and GenAI use. Works well as a homework assignment or an opening hook.
Why We Must Stop Letting GenAI Do the Thinking for Us! (Ahan Singh at TEDx, ~8 min.) 🔗[https://www.youtube.com/watch?v=BTcsTXrfYgY]
A student-led TEDx talk that resonates with peers because it centers the lived experience of learning — focusing on the creative struggle that GenAI shortcuts. Useful for discussions about what students lose when they let GenAI do their thinking for them.
Searching for “GenAI Ethics” (Emmet Stitely at TEDxYouth, ~8 min.) 🔗 [https://www.youtube.com/watch?v=sMJ7Sf2cDiM]
Challenges students to think critically about the rules governing GenAI and who gets to write them. A strong discussion starter for conversations about student agency, responsibility, and the future of GenAI policy.
Section 2: Ethics and GenAI
💻 Instructor Preparation
📚 Readings & Resources
GenAI Ethics: A Free Educational Resource Series (Leon Furze) 🔗 [https://leonfurze.com/ai-ethics]
A comprehensive free resource series covering nine GenAI ethical concerns, organized by difficulty level and designed for K–12 and undergraduate students. Topics include:
- Beginner: Bias and discrimination, environmental impact, truth and academic integrity
- Intermediate: Copyright, privacy, datafication
- Advanced: Emotion and affect recognition, human labor exploitation, power structures
Each topic includes case studies, cross-disciplinary discussion questions, lesson ideas, and external resources. A valuable planning resource for structuring ethics discussions across multiple class sessions.
GenAI for Education: Navigating Ethics and Deepfakes (AI for Education Webinar, ~45 minutes) 🔗[https://www.aiforeducation.io/navigating-ai-ethics-in-education-from-deepfakes-to-academic-integrity]
A 45-minute webinar covering the gray zones of GenAI use, including deepfakes and academic integrity. Includes a flowchart for helping students decide when GenAI use is ethical, a useful tool to adapt for your own course materials.
GenAI Ethics Research Guide (SUNY Fredonia Library) 🔗 [https://fredonia.libguides.com/AI/ethics]
A library research guide covering ethical concerns in GenAI in a comprehensive and visually engaging format. Useful as instructor background reading and as a resource to share with students doing independent research on GenAI ethics.
🖥️ Slide Deck
GenAI and Ethics: Investigating ChatGPT, Gemini, and Copilot 🔗[https://docs.google.com/presentation/d/1-8gKehnXe2hw466IvymHncM9eIv3ysgBCk3aTig7-0s/edit#slide=id.g2bc6dfcabf1_0_131]
“AI & Ethics” slide deck by Torrey Trust, Ph.D. is licensed under CC BY NC 4.0.
A ready-to-use slide deck exploring ethical considerations across three major GenAI platforms. Can be used as-is or adapted for your course. Useful for structured platform comparison discussions.
📝 Student Materials
📽️ Videos
Ethics and GenAI: Understanding AI (Khan Academy) 🔗 [https://www.khanacademy.org/khan-for-educators/khanmigo-for-educators/xb4ad566b4fd3f04a:welcome-to-khanmigo-your-new-ai-teaching-assistant/xb4ad566b4fd3f04a:understanding-ai/v/ethics-and-ai]
A clear, visual breakdown of red-teaming, data privacy, and why GenAI may produce harmful or biased content based on its training data. Works well as an in-class viewing activity or homework assignment to introduce the ethics section of the module.
The Deep Logic of GenAI Cheating (Jared Henderson, ~15 minutes) 🔗[https://www.youtube.com/watch?v=xTiBF2Hq40I]
A critical examination of why students cheat — drawing on signaling theory to argue that technology is not the primary driver of academic dishonesty, but rather the system itself. A thought-provoking assignment for students who are ready to engage with structural critiques of academic integrity.
Section 3: Citing GenAI
The following resources support both instructors designing citation expectations and students learning how to cite GenAI use properly. See also the citation practice activity in the Module 2 lesson plans.
💻 Instructor Preparation & 📝 Student Materials
📚 Citation Guides by Style
Citing Generative AI (APA Style) 🔗[https://apastyle.apa.org/blog/cite-generative-ai-references]
The official APA guidance on how to cite generative GenAI tools including ChatGPT. Includes reference entry and in-text citation formats with examples.
How Do I Cite Generative AI in MLA Style? (MLA Style Center) 🔗 [https://style.mla.org/citing-generative-ai-updated-revised/] 🔗 [https://style.mla.org/citing-generative-ai/]. Modern Language Association, 12 April 2023 (updated).
The MLA’s official guidance on citing generative GenAI, including updated formats and worked examples. Two versions are linked above — the updated/revised guidance and the original post — for reference.
Citing GenAI Tools (Chicago Manual of Style) 🔗[https://www.chicagomanualofstyle.org/qanda/data/faq/topics/Documentation/faq0422.html]
The Chicago Manual of Style’s FAQ guidance on citing GenAI-generated content. Useful for students in disciplines that use Chicago citation style.
📚 Disclosure Frameworks & Tools
👉 Using GenAI at LaGuardia: A Student Guide (LaGuardia Specific Resource)🔗
[https://laguardiaaihub.commons.gc.cuny.edu/using-genai-at-laguardia-a-student-guide/]
The GenAI Disclosure Framework (College & Research Libraries News) 🔗 [https://crln.acrl.org/index.php/crlnews/article/view/26548/34482]
A framework for disclosing GenAI use in academic and research contexts. Provides a structured approach to transparency that goes beyond citation to address the nature and extent of GenAI contributions to a piece of work.
GenAI Disclosure Statement Builder for Research 🔗 [https://aidframework.org/]
An interactive tool that helps students and researchers build accurate, transparent GenAI disclosure statements. A practical classroom resource for teaching students how to document their GenAI use.
Demystifying Generative GenAI Disclosures (EPIC) 🔗 [https://epic.org/demystifying-generative-ai-disclosures]
A clear guide to understanding what GenAI disclosure means, why it matters, and how to do it well. Useful for both instructors setting disclosure expectations and students learning how to communicate their GenAI use honestly and accurately.
AI at CUNY 🔗 [https://www.cuny.edu/academics/ai-academic-hub/#responsible-ai]
A guide to understanding responsible GenAI use within CUNY.
