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Teaching and Generative AI

Resources to help SJSU Faculty and Teaching Assistants how to address ChatGPT and other generative AI tools in their classrooms and assignments.

Welcome to the Teaching and Generative AI LibGuide!

ChatGPT Mobile Screen

This guide is designed to help you:

  • Evaluate whether and how to incorporate tools like ChatGPT into your courses.
  • Make informed decisions based on your specific pedagogical goals.
  • Design assignments that thoughtfully integrate generative AI tools.
  • Address concerns around inappropriate or unauthorized use of AI in academic settings.

 

As of May 2025, SJSU does not have a specific policy regarding student use of AI. California's public higher education systems have not yet created a formal policy regarding using ChatGPT and other generative AI tools. Many universities leave the decision to apply generative AI tools in assignments and courses up to individual faculty and teaching staff. However, it is highly encouraged for faculty to clarify their stance on generative AI and other technologies in their syllabi.

What is AI? What is Generative AI (GenAI)?

AI is the ability of computer systems or algorithms to perform tasks that typically require human intelligence, such as learning, reasoning, problem-solving, and decision-making. For example, reading handwriting, recognizing speech, and providing Netflix recommendations. Artificial Intelligence (AI) is everywhere and it's actually has been around for a long time.

Between the 1950s and 1990s, the field of artificial intelligence was dominated by what is now referred to as classical or symbolic AI. These systems operated using explicit, human-programmed rules and logic to perform tasks. This rule-based approach enabled early AI to automate specific functions, play games, simulate conversation, and respond to queries. In the decades since, AI has advanced significantly, giving rise to modern techniques such as machine learning, natural language processing, computer vision, and generative AI(GenAI).

Generative AI is a form of artificial intelligence that creates new content such as text, images, music, video, code, and voice. It responds to user input, often called a prompt, and can produce content in different tones, styles, and formats. These tools are capable of synthesizing information, answering questions, and adapting to the way a prompt is phrased. Examples include ChatGPT for text, DALL·E for images, and Suno for music.

Unlike earlier AI systems that mainly analyze data or make predictions, generative AI produces original outputs by recognizing and reusing patterns it has learned from large collections of data. Although its responses can appear creative, novel, and "intelligent," it is often argued that the content is not entirely new but rather a recombination of existing material based on training data.

Newer models go beyond text-only capabilities. Multimodal AI systems can process and generate content across different formats(text, images, charts, audio, and apps.)

For example:

  • GPT-4o (OpenAI): Powers ChatGPT with advanced text, vision, and voice capabilities.
  • Gemini (Google): Available in both text-only and multimodal versions.
  • Claude (Anthropic): Known for strong reasoning and summarization.

Disclaimer: This list is for informational and educational purposes. SJSU and the King Library do not endorse any specific generative AI tool or provider.

Types of Generative AI Tools

Text Generation (Large Language Models): Generate human-like text for writing, coding, summarizing, and research (e.g., GPT-4o, Gemini, Claude).

Image Generation: Generate images from text prompts (e.g., DALL·E 3, Stable Diffusion, Midjourney, Adobe Firefly).

Music Generation: Generate full songs from text prompts, including vocals and instrumentation (e.g., Suno AI, Udio).

Video Generation: Generate or edit videos using text, image, or mixed media prompts (e.g., Runway Gen-2, Pika Labs).

What are the limitations and ethical concerns? 

  • Lack of context: AI does not understand meaning or emotion the way humans do.
  • Bias: Generated content may reflect biases in the training data.
  • Hallucinations: AI may generate content that sounds accurate but is completely false or misleading.
  • Makes up citations: AI may fabricate citations or research works that do not exist.
  • Limited access to verified research: Although many newer models come with grounding (the ability for a model to search the web for sources), many AI tools do not have access to scholarly databases or subscription-based academic resources.
  • Misinformation & Deepfakes: AI can generate realistic but false content, including realistic video clips and impersonations that are hard to detect.
  • Copyright & Intellectual Property:Many models are trained on copyrighted content without permission, raising legal and ethical questions about ownership and fair use.
  • Environmental impact: High energy and water consumption in training and running large models.