📖 Module 2: Optional 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 Optional resources for Module 2. There are three sections: Bias, Labor, and Climate. Each entry includes a brief description to help you decide how and when to use it.
Section 1: Bias
💻 Instructor Preparation
📚 Readings
Bias and Ethical Concerns in Machine Learning (ISACA Journal, 2022) 🔗 [https://www.isaca.org/resources/isaca-journal/issues/2022/volume-4/bias-and-ethical-concerns-in-machine-learning]
Explains how bias enters GenAI systems through two main entry points: data input and algorithm design. A solid conceptual foundation for instructors before leading discussions on bias and discrimination in GenAI.
How Can We Manage Biases in Artificial Intelligence Systems? A Systematic Literature Review (ScienceDirect)🔗 [https://www.sciencedirect.com/science/article/pii/S2667096823000125]
A systematic literature review examining how bias manifests across GenAI systems and what organizational strategies can reduce it. Note: This article also appears in the Module 2 Essential materials.
📝 Student Materials
📚 Readings
‘They’re All So Dirty and Smelly:’ Study Unlocks ChatGPT’s Inner Racist (Germain Thomas, Gizmodo, April 2023) 🔗 [https://gizmodo.com/chatgpt-ai-openai-study-frees-chat-gpt-inner-racist-1850333646]
An accessible and provocative look at racial bias in ChatGPT, based on a research study examining what happens when the model’s guardrails are bypassed. A strong discussion starter for conversations about who is harmed by biased GenAI systems and why it matters.
📽️ Videos
Algorithmic Bias and Fairness (Crash Course AI, Episode 18, ~ 12 min.) 🔗 [https://www.youtube.com/watch?v=gV0_raKR2UQ&list=PL8dPuuaLjXtO65LeD2p4_Sb5XQ51par_b&index=19]
Part of the PBS/Crash Course AI series, this episode examines how algorithmic bias develops, how it gets embedded in GenAI systems, and what fairness in GenAI design actually looks like. Uses accessible language and clear examples to make technical concepts approachable. Can be shown in class or assigned as homework, and pairs well with the readings in this section.
Section 2: Labor
💻 Instructor Preparation
📚 Readings
Evaluating the Impact of GenAI on the Labor Market: Current State of Affairs (Yale Budget Lab) 🔗 [https://budgetlab.yale.edu/research/evaluating-impact-ai-labor-market-current-state-affairs]
A research-based assessment of GenAI’s current and projected impact on employment. Useful instructor background for grounding class discussions about GenAI and the future of work in real data.
📝 Student Materials
📚 Readings
Here’s What Happens When Your Lawyer Uses ChatGPT (New York Times, May 2023) 🔗 [https://www.nytimes.com/2023/05/27/nyregion/avianca-airline-lawsuit-chatgpt.html]
The now-famous story of an attorney who submitted a legal brief filled with GenAI-hallucinated case citations and the professional and legal consequences that followed. A vivid, real-world example of what happens when professionals over-rely on GenAI without verification. Note: NYT subscription or free article access may be required.
Yes, GenAI Is Affecting Employment. Here’s the Data. (ADP Research) 🔗 [https://www.adpresearch.com/yes-ai-is-affecting-employment-heres-the-data/]
A data-driven look at how GenAI is already reshaping the labor market. Accessible enough for students while substantive enough to anchor a serious class discussion about GenAI and career planning.
Section 3: Climate
💻 Instructor Preparation
📚 Readings
Environmental Impact of GenAI (National Education Association) 🔗 [https://www.nea.org/professional-excellence/student-engagement/tools-tips/environmental-impact-ai]
An educator-facing overview of the environmental costs of GenAI including energy consumption, water use, and carbon emissions. Useful instructor background for connecting GenAI literacy to environmental and sustainability discussions.
What Direct Risks Does GenAI Pose to the Climate and Environment? (LSE Grantham Research Institute) 🔗 [https://www.lse.ac.uk/granthaminstitute/explainers/what-direct-risks-does-ai-pose-to-the-climate-and-environment/]
A concise, research-grounded explainer from the London School of Economics on the direct environmental risks posed by GenAI systems. Covers energy use, hardware production, and ecosystem impact.
📝 Student Materials
📚 Readings
GenAI Has an Environmental Problem. Here’s What the World Can Do About That (UNEP) 🔗[https://www.unep.org/news-and-stories/story/ai-has-environmental-problem-heres-what-world-can-do-about]
A clear, accessible overview of GenAI’s environmental footprint and potential solutions from the United Nations Environment Programme. A good entry point for students new to the climate dimensions of GenAI.
📽️ Videos
GenAI Is Dangerous, but Not for the Reasons You Think (Sasha Luccioni, November 2023, ~11 min.) 🔗 [https://www.youtube.com/watch?v=eXdVDhOGqoE]
A compelling talk by a leading GenAI researcher arguing that the most pressing dangers of GenAI are not the ones dominating headlines. Focuses on environmental costs, labor exploitation, and systemic harms. A strong discussion starter for students ready to think critically about the broader consequences of GenAI development.
