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Political Science 398: Cyberpolitics

This guide provides information, resources, and tools for generative AI

What is generative AI?

Generative artificial intelligence (GenAI) is a type of artificial intelligence that creates new content. GenAI is possible with large language models (LLM) that are trained on massive amounts of text content or data. Each LLM is trained on a particular set of data, which might come from website, social media, and internet forum crawls, news sites, copyrighted or public domain materials, scientific articles, etc, for its intended purpose. GenAI generates outputs based on prompts. Responses are a prediction of subsequent units of meaning (tokens) to generate text that resembles natural language based on that particular LLM's training materials. However, GenAI creates content independent of context. This means that it can sometimes "hallucinate", or generate content that is inaccurate or that doesn't make sense, including book and article citations, data, recent events.

Notable generative AI LLMs and their applications

  • GPT-4o (OpenAI ChatGPT, Bing Co-Pilot)
  • LLAMA-3.1 (Meta)
  • Gemini 2.0 (Google, formerly Bard)
  • Claude-3.5 (Anthropic)
  • DeepSeek-V3

Notable text-to image generative AI applications

  • Midjourney
  • DALL-E (OpenAI)
  • Stable Diffusion (Stability AI)
  • Gemini (Google)
  • Firefly (Adobe)

Writing prompts

Prompts are the instructions you input into the AI system to generate content. The AI system is responsive and you can use additional prompts to refine the AI system's outputs. There are a few frameworks for crafting effective prompts. Effective prompt writing takes practice.

Frameworks for writing prompts for generative AI

  • CLEAR Framework (Lo, 2023)

    • Concise: brevity and clarity in prompts

    • Logical: structured and coherent prompts

    • Explicit: clear output specifications

    • Adaptive: flexibility and customization in prompts

    • Reflective: continuous evaluation and improvement of prompts

  • CRISPE Framework (Nigh, 2023)

    • Capacity and Role: What role (or roles) should the app act as?

    • Insight: Provides the behind the scenes insight, background, and context to your request

    • Statement: What you are asking the app to do

    • Personality: The style, personality, or manner you want it to respond in

    • Experiment: Asking the app to provide multiple examples for you