Generative AI: FAQs & Ethics of use
A simple, accessible guide to understanding Generative Artificial Intelligence
Welcome to this repository! This project provides a clear and student-friendly overview of Generative AI (GenAI)—how it works, what it can do, its risks, and the ethical considerations we must keep in mind as AI becomes part of everyday life.
This repo powers a webpage that aims to educate readers on both the foundational concepts and the responsible use of AI tools.
📌 Overview
Generative AI is one of the most rapidly advancing technologies today. From writing and code generation to image and audio synthesis, GenAI models are transforming the way people work, communicate, learn, and create.
But along with these exciting possibilities come questions about fairness, safety, reliability, bias, and ethics.
This project collects essential FAQs, strengths, limitations, and ethical guidelines to help users understand how to use AI responsibly.
📚 Contents
- What is Generative AI?
An introduction to what GenAI is and what makes it different from traditional AI.
- How Does GenAI Work?
A simplified explanation of generative modeling, data patterns, training datasets, and how models produce new content.
- Examples of GenAI Tools
A categorized list of real tools including:
Language Models (ChatGPT, Claude, Llama, etc.)
Image Generators (Stable Diffusion, Midjourney, DALL·E)
Code Generators (Copilot, AlphaCode)
Audio/Music Models (AudioLM, MusicLM)
Video Models (Make-A-Video, DeepBrain)
- What Can GenAI Do? (Strengths)
Covers creative potential, productivity, multimodal capabilities, decision-support uses, and automation benefits.
- Limitations & Risks
A responsible and realistic look at the challenges:
Hallucinations
Bias and discrimination
Data privacy issues
Copyright & legal risks
Environmental cost
Security vulnerabilities
Lack of transparency
- Additional FAQs
More clarifications on AI behavior, usage boundaries, and common misconceptions.
⚖️ Ethics & Responsible Use
This project emphasizes responsible AI practices, including:
💬 Use AI as a support tool, not a substitute for deep understanding.
🔍 Verify outputs—AI can be confidently wrong.
🤝 Ensure fairness, avoid harmful or biased prompts.
🔒 Protect personal data; never submit sensitive information.
🎨 Respect copyright—AI outputs may resemble existing works.
🌍 Be mindful of the environmental footprint of large models.
Ethical AI is about ensuring technology helps people, not harms them.
🛠️ Purpose of This Repository
This repository was created to:
✔ Provide a digestible reference on GenAI for students and new users ✔ Support discussions on AI ethics and responsible use ✔ Serve as the content source for a public FAQ webpage ✔ Encourage critical thinking about technology’s impact
📖 References
The explanations are based on research and academic sources, including:
Feuerriegel et al. (2024). Generative AI – Business & Information Systems Engineering.
Fui-Hoon Nah et al. (2023). Applications, challenges, and AI-human collaboration.
Manduchi et al. (2024). Challenges and opportunities in Generative AI.
Kenthapadi, Lakkaraju & Rajani (2023). Generative AI meets responsible AI.