A Guide to AI Ethics Literacy

A growing need, a growing list of issues, and a growing collection of resources from the Markkula Center for Applied Ethics

Curated by Irina Raicu and Subramaniam Vincent

Across industries and disciplines, across corporations, government agencies, and nonprofits, and across various roles within various organizations, many of us are being encouraged to use generative AI tools—or find ourselves using them, since they are increasingly baked into various products and services.

The effective use of generative AI requires a certain level of AI literacy. AI ethics literacy is a part of AI literacy. It helps developers build better products, helps users of such products make better use of them, and helps all of us understand how various tools impact us, and how societies are being reshaped by such uses.

Below is a list of AI ethics issues (not exhaustive, and likely to be updated as generative AI tools are deployed in novel ways in new contexts). For each of them, we have pulled together relevant materials (articles and video recordings) from the center’s website. We will add materials as Markkula Center staff and Santa Clara University faculty scholars continue to write and present events related to AI literacy.

We hope that engagement with these resources will generate a deeper and broader conversation.

Preface
1. Environmental Impact
2. Transparency
3. Labor
4. Socio-Economic Inequality
5. Ethics of Deployment
6. Social Life (with Chatbots)
7. Moral Deskilling
8. Anthropomorphism
9. Hallucinations / Accuracy / Truth
10. Bias (In and Out)
11. Prediction
12. Authenticity
13. AI Slop
14. Privacy
15. Cybersecurity
16. Consciousness / Sentience
17. AGI and Superintelligence
18. Effects on the Human Spirit

Preface

Using generative AI well requires a level of AI literacy. Without understanding both the technology’s affordances and its limitations, we cannot make good use of it. Without understanding (at least at a general level) how large language models generate what they do, we can’t decide when they are fit for the purpose. And without understanding the benefits and harms they might bring, and to whom, we can’t conduct the ethical analysis that should precede any technology’s adoption.

AI ethics literacy is the part of AI literacy that highlights the ethical issues related to the development and deployment of generative AI tools. AI ethics comprises more than privacy, intellectual property rights, bias, and job displacement (important issues with which many people are now more or less familiar). The many beneficial uses of AI are also, of course, a key part of AI ethics literacy, but those are often touted loudly by all the entities developing and deploying AI tools; to the extent that this compendium rings more of a cautionary note, it’s in response to the volume of the AI-related hype.

Amid the growing calls for AI literacy, we hope that this compendium will serve as a resource for developers, users, students, teachers, parents… in truth, for all of us who live in societies that are rapidly adopting generative AI.

Guide to AI Ethics Literacy

A Guide to AI Ethics Literacy

A growing need, a growing list of issues, and a growing collection of resources from the Markkula Center for Applied Ethics

Preface

Environmental Impact

Overview

Water

Green AI

Energy

Business Implications

Regulation

AI for Sustainability

Public Health

Transparency

Labor

Labeling, Augmenting, Evaluating Data

Replacement/Augmentation of Human Work

Cheating

Socio-Economic Inequality

Ethics of Deployment

Social Life (with Chatbots)

Moral Deskilling

Anthropomorphism

Hallucinations / Accuracy / Truth

Bias (In And Out)

Prediction

Authenticity

AI Slop

Privacy

Data Harvesting

Data Leakage

Copyright

Cybersecurity

Agentic AI’s Cybersecurity Challenges

Prompt Injection

Data Leakage

Consciousness / Sentience

AGI and Superintelligence

Effects on the Human Spirit