# Generative AI Literacy: Twelve Defining Competencies

arXiv: https://arxiv.org/abs/2412.12107 · HTML: https://mlsanity.com/paper/2412.12107/

## Key facts

- Cited by 13 papers in the map (data through 14 Oct 2026).
- Builds on 21 of its 107 references that are in the map.
- First posted on arXiv 29 Nov 2024.

## Builds on (most cited first, 21 of 21)

- [Large Language Models are Zero-Shot Reasoners](https://mlsanity.com/paper/2205.11916/) (2022)
- [Learning to Prompt for Vision-Language Models](https://mlsanity.com/paper/2109.01134/) (2021)
- [Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing](https://mlsanity.com/paper/2107.13586/) (2021)
- [An Introduction to Variational Autoencoders](https://mlsanity.com/paper/1906.02691/) (2019)
- [Multimodal Chain-of-Thought Reasoning in Language Models](https://mlsanity.com/paper/2302.00923/) (2023)
- [A Prompt Pattern Catalog to Enhance Prompt Engineering with ChatGPT](https://mlsanity.com/paper/2302.11382/) (2023)
- [Prompt Programming for Large Language Models: Beyond the Few-Shot Paradigm](https://mlsanity.com/paper/2102.07350/) (2021)
- [Generative Adversarial Networks: An Overview](https://mlsanity.com/paper/1710.07035/) (2017)
- [Prompting GPT-3 To Be Reliable](https://mlsanity.com/paper/2210.09150/) (2022)
- [Large Language Model Guided Tree-of-Thought](https://mlsanity.com/paper/2305.08291/) (2023)
- [Design Guidelines for Prompt Engineering Text-to-Image Generative Models](https://mlsanity.com/paper/2109.06977/) (2021)
- [Ask Me Anything: A simple strategy for prompting language models](https://mlsanity.com/paper/2210.02441/) (2022)
- [Regulating ChatGPT and other Large Generative AI Models](https://mlsanity.com/paper/2302.02337/) (2023)
- [Testing of Detection Tools for AI-Generated Text](https://mlsanity.com/paper/2306.15666/) (2023)
- [Review of Large Vision Models and Visual Prompt Engineering](https://mlsanity.com/paper/2307.00855/) (2023)
- [Adversarial Deepfakes: Evaluating Vulnerability of Deepfake Detectors to Adversarial Examples](https://mlsanity.com/paper/2002.12749/) (2020)
- [DeepRhythm: Exposing DeepFakes with Attentional Visual Heartbeat Rhythms](https://mlsanity.com/paper/2006.07634/) (2020)
- [Students' Voices on Generative AI: Perceptions, Benefits, and Challenges in Higher Education](https://mlsanity.com/paper/2305.00290/) (2023)
- [The Social Impact of Generative AI: An Analysis on ChatGPT](https://mlsanity.com/paper/2403.04667/) (2024)
- [ChatGPT in education: A discourse analysis of worries and concerns on social media](https://mlsanity.com/paper/2305.02201/) (2023)
- [Generative AI is already widespread in the public sector](https://mlsanity.com/paper/2401.01291/) (2024)

## Built on by (most cited first, 13 of 13)

- [Fostering Appropriate Reliance on Large Language Models: The Role of Explanations, Sources, and Inconsistencies](https://mlsanity.com/paper/2502.08554/) (2025)
- [The AI Literacy Heptagon: A Structured Approach to AI Literacy in Higher Education](https://mlsanity.com/paper/2509.18900/) (2025)
- [Use Me Wisely: AI-Driven Assessment for LLM Prompting Skills Development](https://mlsanity.com/paper/2503.02532/) (2025)
- [Exploration vs. Fixation: Scaffolding Divergent and Convergent Thinking for Human-AI Co-Creation with Generative Models](https://mlsanity.com/paper/2512.18388/) (2025)
- ["If You're Very Clever, No One Knows You've Used It": The Social Dynamics of Developing Generative AI Literacy in the Workplace](https://mlsanity.com/paper/2602.01386/) (2026)
- [Toward Human-Centered AI-Assisted Terminology Work](https://mlsanity.com/paper/2512.18859/) (2025)
- [What is Safety? Corporate Discourse, Power, and the Politics of Generative AI Safety](https://mlsanity.com/paper/2602.06981/) (2026)
- [Framing, Judging, Steering: An Assessable Competency Model for Teach-ing Students to Reason With Generative AI](https://mlsanity.com/paper/2606.05983/) (2026)
- [AI Literacy for Legal AI Systems: A practical approach](https://mlsanity.com/paper/2505.18006/) (2025)
- [Generativism: Toward a Learning Theory for the Age of Generative Artificial Intelligence](https://mlsanity.com/paper/2606.12441/) (2026)
- [The GenAI Skill Bypass: Mapping Divergent Pathways of University Students and Staff AI Literacy](https://mlsanity.com/paper/2607.05411/) (2026)
- [Introducing Human-Centeredness in AI-Assisted Lexicography](https://mlsanity.com/paper/2607.11808/) (2026)
- [Rethinking Generative AI Literacy: An Integrative, Developmental, and Dialectical Framework for K-12 Teacher Education](https://mlsanity.com/paper/2608.01705/) (2026)

## Abstract (arXiv)

This paper introduces a competency-based model for generative artificial intelligence (AI) literacy covering essential skills and knowledge areas necessary to interact with generative AI. The competencies range from foundational AI literacy to prompt engineering and programming skills, including ethical and legal considerations. These twelve competencies offer a framework for individuals, policymakers, government officials, and educators looking to navigate and take advantage of the potential of generative AI responsibly. Embedding these competencies into educational programs and professional training initiatives can equip individuals to become responsible and informed users and creators of generative AI. The competencies follow a logical progression and serve as a roadmap for individuals seeking to get familiar with generative AI and for researchers and policymakers to develop assessments, educational programs, guidelines, and regulations.