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Generative Artificial Intelligence: Home

A guide for faculty and staff to understand the opportunities and challenges of ChatGPT, Microsoft CoPilot, and similar Generative AIs for higher education.

Looking Back and Looking Forward: History & Future Trajectories

The Beginning

Have you seen the 2014 film The Imitation Game, starring Benedict Cumberbatch as Alan Turing, the brilliant WWII code breaker who built a mathematical machine to crack the German code? 

In 1950, Turing posed what has become known as the Turing Test, which he called the Imitation Game. It posited that if a computer could sufficiently imitate human conversation and thought, it could think on its own. It took over 70 years, but AI finally passed the Turing Test in 2023. 

Check out the following articles to learn more about Turing's influence on the assessment of AI and future trajectories of the technology and the current problem of assessment. Julia Angwin also reminds us that the companies behind A.I. platforms are profit-driven, which can result in overpromising on what their products can deliver. This becomes clearer when their products are placed under expert review. Many current and former employees at companies like OpenAI, Google, and Microsoft have voiced concerns about safety and the lack of government regulation in the industry.

Imaginations of the Future as Budding Reality

The 2013 movie Her is an example of how a fictionalized imagining of A.I. companionship is influencing the development of modern A.I. The reality of chatbot companions such as Character.AI offer a grim reality check.

Blueprint for an AI Bill of Rights
The Old-Fashioned Library at the Heart of the A.I. Boom

Learn about the the library that is the "architectural centerpiece of the offices of OpenAI," and how OpenAI employees find it to be a place of inspiration for quiet work or breaks, full of their suggested books, while it also stands as a symbol of the controversy over whether the use of copyrighted books and other publications to train the company's AI platform ChatGPT was an appropriate application of fair use. 

Designed to be a symbol of human creativity and evoke the ethos of academia with Oriental rugs and modern furniture and fixtures, it looks like a sleek reimagining of the elegant reading rooms designed by the Victorians, like the Rose Reading Room at the New York Public Library and the Green Library at Stanford University.

It was important to Sam Altman, OpenAI's CEO, to create this space at OpenAI's headquarters because his "dining room and living room at home is inside a library--floor-to-ceiling books all the way around...There is something about sitting in the middle of knowledge on the shelves at vast scale that I find interesting." In the midst of ever-changing digital access to knowledge, the print word still holds unique sway. I even spied some of PTC's print titles on OpenAI's shelves, like Diana Gabaldon's Outlander books, and J.R.R. Tolkien's The Hobbit and The Two Towers.

Opportunities

  • students need to know how to use AI in a marketplace that is being transformed by it
  • transformative influence on academic research and teaching
  • cut down time spent on tedious and mundane tasks
  • explore new applications of critical thinking to prompt engineering
  • new applications of information literacy

Challenges

  • cheating
  • loss of writing and critical thinking skills
  • spread of misinformation, hate speech, and dangerous misuses
  • data privacy concerns
  • potential to be hacked
  • environmental impacts 
  • unclear how numerous copyright lawsuits will affect AI 

Databases, Definitions, and Search Terms

Where to Search

The best place to search for information of all types on ChatGPT/Generative AI is through the Online Catalog, especially since scholarly research on this subject is so new and evolving quickly.

Use the search box below to search the Online Catalog, or use one of the databases suggested below.

 
Definitions and Search Terms

Use this list of definitions that was put together by PASCAL (Partnership Among South Carolina Academic Libraries) to help you search the Online Catalog and Databases for information about AI:

  • Artificial Intelligence (AI) - 1) A branch of computer science dealing with the simulation of intelligent behavior in computers. 2) The capability of a machine to imitate intelligent human behavior. [Merriam-Webster]
  • Artificial Neural Networks - A network of artificial neurons or nodes. Used for solving AI problems, they model connections of biological neurons as weights between nodes. [Wikipedia]
  • ChatGPT - A large language model-based chatbot developed by the company OpenAI. Notable for enabling users to refine and steer a conversation towards a desired length, format, style, level of detail, and language used. [Wikipedia]
  • Deep Learning - Part of a broader family of machine learning methods, which is based on artificial neural networks with representation learning. The adjective ‘deep’ in deep learning refers to the use of multiple layers in the network.  [Wikipedia]
  • Generative AI - Artificial intelligence capable of generating text, images, or other media in response to prompts. Generative AI models learn the patterns and structure of their input training data by applying neural network machine learning techniques and then generating new data with similar characteristics.” Types of Generative AI systems include ChatGPT, built by OpenAI and Bard, a chatbot built by Google. [Wikipedia]
  • Hallucination (artificial intelligence) - In the field of artificial intelligence (AI), a hallucination or artificial hallucination (also called confabulation or delusion) is a confident response by an AI that does not seem to be justified by its training data. [Wikipedia]
  • Language Model - A probability distribution over words or sequences of words.” Using statistical and probabilistic techniques, language models determine the probability of a given word or sequence of words occurring in a sentence. [Wikipedia]
  • Large Language Model - A language model characterized by emergent properties enabled by its large size. Large Language Models are built with artificial neural networks, pretrained using self-supervised and semi-supervised learning and typically contain millions to billions of weights. [Wikipedia]
  • Machine Learning (ML) - The process by which a computer is able to improve its own performance (as in analyzing image files) by continuously incorporating new data into an existing statistical model. [Merriam-Webster]
  • Natural Language Processing - An interdisciplinary subfield of linguistics, computer science, and artificial intelligence concerned with the interactions between computers and human language, in particular how to program computers to process and analyze large amounts of natural language data. [Wikipedia]
  • Representation Learning - A set of techniques that allows a system to automatically discover the representations needed for feature detection or classification from raw data. This replaces manual feature engineering and allows a machine to both learn the features and use them to perform a specific task. [Wikipedia]

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