Artificial intelligence (AI):

"Machines that imitate some features of human intelligence, such as perception, learning, reasoning, problem-solving, language interaction and creative work" (UNESCO, 2022).

Generative AI (GenAI):

“A type of artificial intelligence that involves creating machines or computer programs that can generate new[?] content, such as images, text, or music. Unlike traditional AI systems that rely on predefined rules or pre-existing data to make decisions, generative AI models use algorithms and neural networks to learn patterns and relationships in data and generate new[?] outputs based on that learning” (Kwantlen Polytechnic University, n.d., p. 1).

Large Language Models (LLMs):

"A language model is a type of artificial intelligence model that is trained to understand and generate human language. It learns the patterns, structures, and relationships within a given language and has traditionally been used for narrow AI tasks such as text translation. The quality of a language model depends on its size, the amount and diversity of data it was trained on, and the complexity of the learning algorithms used during training.

A large language model (LLM) refers to a specific class of language model that has significantly more parameters than traditional language models. Parameters are the internal variables of the model that are learned during the training process and represent the knowledge the model has acquired" (Rouse, 2024)

More information about GenAI and teaching and learning can be found on the MRU GenAI webpage: https://library.mtroyal.ca/ai

ENGL 2207 - GenAI Brainstorm In-Class Activity

1. Click the link to this Padlet: https://padlet.com/bleching/engl_2207_genai

2. Take 3-5 minutes to brainstorm what you think some of the opportunities and challenges presented by GenAI technologies are, or will be.

There are many issues with GenAI tools. Here is a non-exhaustive list. Some to keep in mind are:

• Academic integrity—probably the issue that has been most talked about in higher education. What does it mean if GenAI can "pass" an assignment/test? Should the assignment/test be altered? How much—if at all—should students be taught about how to use GenAI? (Answers to that question vary significantly by discipline from total embrace to banning.)

  • For example: ChatGPT "passing" the MCAT: "Depending on its visual item response strategy, ChatGPT performed at or above the median performance of 276,779 student test takers on the MCAT." (Bommineni et al., 2023). Other examples of tests.

• Research integrity—can GenAI be considered an author? Should researchers have to disclose if they've used GenAI in their research or their writing? How should that disclosure be made? There have been notable instances of GenAI output making it past peer review, particularly early after ChatGPT's popularization. 

  • Textual examples and image examples of GenAI output making it past peer review.

  • Here are some statements about AI and authorship from the Committee on Publication Ethics (COPE), Nature, the JAMA Network journals, and the World Association of Medical Editors.

• User privacy and protection of user information—if people disclose private information to GenAI tools, will it be used to train/refine the tools?

  • For example: AI therapy chatbots.

• Bias—both in GenAI training data and in generated output.

  • Textual examples and image examples. (Over-correction for bias has also been its own problem, too, though!)

• Information quality—sometimes called the "hallucination" problem or fabrication problem.

  • A notable example of this problem from early after ChatGPT became popular was lawyers that got in trouble for referencing fake legal cases generated by ChatGPT.

• Deskilling—if we come to rely too much on GenAI, will we lose valuable skills? Are there some skills that we're okay with losing because we'll save time and energy for other, more important tasks?

  • For example: critical thinking skills.

• Copyright infringement—in training data and in generated output.

  • For example: GenAI image generation tools and lawsuits—here's a list of some American cases—filter for "Copyright Infringement" under "Cause of Action."

• Distinguishing machines from humans—do people have a right to know if/when they're interacting with a bot that is convincingly "human"? If so, how will people respond to the disclosure that they're being served by AI? Are there communicative contexts where this disclosure may not be met positively?

  • For example: Vanderbilt University.

• Environmental impacts/sustainability—concerns about energy consumption and carbon emissions used both in training GenAI models and then in integrating them into preexisting software, workflows, etc.

  • One estimation of the water used to generate a 100 word email using ChatGPT: 519 ml (a little over 1 bottle of water).

AI as a Research Tool

Generative artificial intelligence (AI) is a hot topic these days that is having an impact on many areas of cultural life, education, and the economy.

Many people in education (including myself) are still getting their heads around generative AI as a topic, and this is made difficult by how quickly the technology changes and how little non-experts understand about it. It is incredibly complex, blackboxed technology.

If you do choose to use generative AI, you may want to use it as a brainstorming partner early on in your exploration of a topic similar to how you might browse a Wikipedia article on a subject to get a quick grasp of it in the early stages of your research. Do not use generative AI as a research tool in complete replacement of LibrarySearch or Google Scholar. If you do so, your research (and thinking) will suffer.

Specifically, be sure to scrutinize any source(s) that generative AI provides you with on a topic. This is because, at this point, it is prone to error: what some have called "hallucination," but that I prefer to call "fabrication."

If generative AI provides you with a source:

(1) make sure that the source actually exists, and, if it does exist;

(2) make sure that the source actually contains the information that generative AI has attributed to it.

What is fabrication?

An Investigation of ChatGPT's Sources

1. Book: Influencer Marketing for Dummies by Kristy Sammis, Cat Lincoln, and Stefania Pomponi

   • This source does exist and it was written by these authors, but it is a For Dummies book that wouldn't be considered scholarly.

2. Book: Influencer Marketing: Building Brand in a Digital Age by Duncan Brown and Nick Haye

   • This source does exist and it was written by those authors, but ChatGPT has fabricated a subtitle for it that it doesn't have.

3. Academic Article: "The Rise of Influencer Marketing and Its Impact on Consumer Behavior" by Liu, Hu, and Zhang (2019)

   • To the best of my searching abilities, this source does not exist.

4. Academic Article: "Ethical and Legal Issues in Influencer Marketing" by Brenner, A. and Capron, L. (2019)

   • To the best of my searching abilities, this source does not exist.

5. Academic Article: "The Dark Side of Social Media: A Consumer Psychology Perspective" by Phua, J., Jin, S.V., and Kim, J.J. (2017)

   • This source is a Frankenstein composite of 2 sources. The authors have been taken from this article and the title has been taken from this edited book with which those authors had no involvement.

Different AI Tools

Generative AI Product Tracker (Ithaka S+R).

The categories are:

• General Purpose Tools (pp. 1-9)

• Discovery Tools (pp. 10-19)

• Teaching & Learning Tools (pp. 19-31)

• Workflow Tools (pp. 31-42)

• Writing Tools (pp. 42-46)

• Coding Tools (pp. 46-48)

• Image Generation Tools (pp. 49-50)

• Other (pp. 50-53)

For this assignment, you will likely want to be using General Purpose Tools (pp. 1-9).

For the purposes of text generation, here are a few GenAI LLM chatbot tools you could use. (This list is not exhaustive.):

• OpenAI's ChatGPT (requires a free account to use ChatGPT 4o a limited number of times and ChatGPT 4o mini, their free chatbot)

  • Perhaps experiment with changing the model, the web search mode, and reasoning modes.

• Google AI's Gemini (formerly known as Bard, but was renamed Gemini) (requires a Google account to use Gemini chatbot)

  • Perhaps experiment with Flash Thinking Experimental mode.

• Perplexity AI's Perplexity AI (doesn't require an account, but a free account is required to try Perplexity AI Pro and to save chats/threads)

  • Perhaps experiment with Pro Search, Deep Research, and Reasoning modes.

• Anthropic's Claude (requires a free account to use the chatbot)

  • Perhaps experiment with Claude's writing style customization.

• Microsoft's Copilot/Bing search (doesn't require an account, but supposedly works best with Microsoft account and in the Microsoft Edge browser)

• HuggingFace's HuggingChat (requires a free account to use the chatbot)

Keep in mind:

• These models work by performing a calculation to predict what the next most likely word in a sequence is.

• These models are not search engines, or, at least, they weren't designed as search engines originally. Some of them have search engine functionality now (like ChatGPT) and some will even provide footnotes (like Copilot/Bing), but it is still worth examining the linked source to see how the chatbot has represented the source.

In-Class Activity #2: Comparing Textual Outputs Across Tools (~12-15 minutes)

1. First, we will divide the class into groups. Each group will experiment with 1 GenAI chatbot and report back on what they find by answering some questions.

2. Each group will pick a GenAI chatbot tool that they will use for the activity from this list:

   • OpenAI's ChatGPT (requires a free account to use ChatGPT 4o a limited number of times and ChatGPT 4o mini, their free chatbot)

     • Perhaps experiment with changing the model, the web search mode, and reasoning modes?

   • Google AI's Gemini (formerly known as Bard, but was renamed Gemini) (requires a Google account to use Gemini chatbot)

     • Perhaps experiment with Flash Thinking Experimental mode?

   • Perplexity AI's Perplexity AI (doesn't require an account, but a free account is required to try Perplexity AI Pro and to save chats/threads)

     • Perhaps experiment with Pro Search, Deep Research, and Reasoning modes.

   • Anthropic's Claude (requires a free account to use the chatbot)

     • Perhaps experiment with Claude's writing style customization?

   • Microsoft's Copilot/Bing search (doesn't require an account, but supposedly works best with Microsoft account and in the Microsoft Edge browser)

   • HuggingFace's HuggingChat (requires a free account to use the chatbot)

3. Spend a few minutes familiarizing yourselves with the tool as a group.

   • If the tool requires account creation to access it and you're not comfortable with that, please choose another tool that provides free functionality without an account.

4. Provide the following prompt to your tool:

   • Write about a genre of music that you love. Provide some factual information about the genre using a minimum of two scholarly sources that you should cite, and provide at least one personal anecdote about your experience attending a concert by a specific performer that works and performs in that music genre. This writing output should be 300-500 words total.

5. After prompting your tool, perform the following analysis, answering the following questions:

   • 1. Which tool did you choose to investigate?

   • 2. Did you get the tool to successfully generate output?

     1. If yes, were you satisfied with the tool's overall generated output? Why or why not?

     2. If no, what was it that prohibited you from generating output?

   • 3. Did you experiment with any of the tool's settings to try to generate different text?

     1. If so, which settings did you try, and did they meaningfully change the textual output in your opinion?

   • 4. What kind of sources did the tool provide as part of its textual output?

     1. Did the sources exist or were they hallucinated/fabricated?

     2. Would you consider them to be scholarly sources?

     3. Why do you think the tool selected those specific sources? (If you have no answer for this one, that's okay!)

   • 5. Did the tool write compellingly about attending a live concert experience by an artist in the chosen genre?

     1. If yes, why?

     2. If no, why not?

   • 6. Did anything surprise you about the tool's overall output?

Citation Help

• How do I cite generative AI in MLA style?

• MRU Guide to MLA style for Academic Work (2024-2025) (see example E15 on p. 18)