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Artificial Intelligence

This guide is a basic overview of Artificial Intellegence through the lens of student research in an academic library.

Disclaimer

  • Generative artificial intelligence has already started to have an impact on the way we discover, manage, create, and disseminate information. 
  • Generative AI tools are in a state of rapid development, and new information about applications, policies, and social impact is released each day. While every attempt will be made to keep this guide up to date, please be aware that the information included here is likely to age quickly. 
  • The Library does not endorse any specific AI technologies, and encourages users to be cautious about sharing personal information when using AI tools. 

(Used with permission from Brown University Library)

Xavier University Student Handbook

The Student Handbook mentions AI or Generative AI twice:

  • 2.3.8.1.2 DEFINITIONS & GLOSSARY OF TERMS

    • 7. Misuse of Generative Artificial Intelligence (GAI or AI)
      Students are expected to originate their own work. Misuse of generative artificial intelligence (known as GAI or AI) includes, but is not limited to, using GAI/AI to write a paper or using GAI/AI to generate assignment responses.

  • 2.3.8.1.3 STUDENT RESPONSIBILITIES OF UPHOLDING ACADEMIC INTEGRITY
    • 8. No student shall submit materials or assignments generated or written by Generative Artificial Intelligence (GAI or AI) unless authorized by the instructor. 

What is Artificial Intellegence?

Artificial intelligence refers to both the areas of computer science and engineering that aim to build intelligent computers as well as the human-like intelligence, judgment, learning, and awareness displayed by machines.

Artificial intelligence encompasses a number of important subareas, including voice recognition, image identification, natural language processing, expert systems, neural networks, planning, robotics, and intelligent agents.

Artificial intelligence is also referred to as machine learning (ML) although they are different.

  • Large Language Models (LLMs) are often referred to as AI and fit under the umbrella of AI with ML but neither demonstrates actual intelligence.

“Large language models use deep neural networks, such as transformers, to learn from billions or trillions of words, and to produce texts on any topic or domain. Large language models can also perform various natural language tasks, such as classification, summarization, translation, generation, and dialogue." (Maeda & Chaki, 2023)

  • Intelligence of created systems and algorithms is typically compared to human intelligence. Sometimes LLMs and ML products can appear to have human intelligence, but it is simply the product of coding, not actual intelligence.
  • Generative AI
    “a type of artificial intelligence that can learn from and mimic large amounts of data to create content such as text, images, music, videos, code, and more, based on inputs or prompts.” (Harvard, 2024)
    • Examples: Adobe Firefly, Microsoft Copilot, OpenAIChatGPT

  • GPT (Generative Pre-trained Transformer)
    a type of large language model and a prominent framework for generative artificial intelligence.

    • "models that give applications the ability to create human-like text es, music, and more), and
      answer questions in a conversational manner." (What Is GPT AI?, n.d.)