Center for Innovation in Teaching and Learning

Generative AI 

Beyond generating topic-based paper assignments, generative AI can be used to improve writing skills, create royalty free art and music, and serve as an advanced form of search in all aspects of life. One example of how unique this resource is: you can copy and paste your grocery list and ChatGPT or Bing will provide you with recipe recommendations ensuring that you maximize meals throughout the week.

The list of generative AI is ever expanding. Here are a few examples of generative AI platforms:

ChatGPT: ChatGPT is an artificial intelligence language model developed by OpenAI. It uses machine learning techniques, particularly a method known as transformer-based deep learning, to generate human-like text based on the input it's given. The "GPT" in its name stands for "Generative Pretrained Transformer," reflecting the technical methodology used to create and train the model.

The main function of ChatGPT is to interact with users in a conversational manner, generating responses to a variety of prompts. It can perform tasks like answering questions, writing essays, creating poetry, and even coding, to some extent.

It's worth noting that while ChatGPT is able to generate impressively coherent and contextually appropriate text, it doesn't actually "understand" the content in the way humans do. It bases its responses on patterns and structures in the data it was trained on, rather than any true understanding or consciousness.

The version of ChatGPT that you're interacting with right now, based on the GPT-4 architecture, represents a continued evolution of the model, with each version generally offering improved performance over its predecessors (response from ChatGPT on 7/11/2023).

Learn more:  

• What is ChatGPT? Open AI’s Chat GPT Explained 
• OpenAI blog on ChatGPT 

Bing: Bing AI, paired with the Bing web browser and search engine, Microsoft’s AI chatbot runs on OpenAI’s GPT-4 model. Currently, it can be found in the right page of the Microsoft Edge browser. 

Dall-E 2: Dall-E 2 uses a version of the GPT-3 model that's specifically trained to generate images from textual descriptions. It's named as a portmanteau of "Dali" (for Salvador Dali, the surrealist painter) and "WALL-E" (the Pixar movie).

Microsoft Designer: Designer is Microsoft’s graphic design app that utilizes AI to create stunning designs based on written text prompts. This is an early example of how AI will be used in the design process. You can learn more here.  

Bard: Google’s Bard is a large language model, also known as a conversational AI or chatbot trained to be informative and comprehensive. It is trained on a massive amount of text data, and able to communicate and generate human-like text in response to a wide range of prompts and questions.

The name "Bard" is a reference to the traditional Celtic poets and seers who were skilled in storytelling, music, and verse. I hope to live up to the name by using my knowledge and abilities to help people learn, create, and be entertained (response from Google’s Bard 7/11/2023). 

Midjourney: Midjourney is a generative AI program and service created and hosted by San Francisco-based independent research lab Midjourney, Inc. Midjourney generates images from natural language descriptions, called "prompts", like OpenAI's DALL-E and Stable Diffusion. It is a powerful tool that can be used for a variety of purposes. If you're interested in creative art projects, concept development, or product design, then Midjourney is worth checking out (response from Google’s Bard 7/11/2023).

Teaching with Generative AI 

Welcome to an era where AI assistance has become an invaluable tool in education and the workforce. Through properly educating ourselves and our students about AI and its uses, generative AI can become more than a way to cheat, but a resource for taking concepts and ideas beyond what we can imagine. 

As we navigate the AI revolution in education, we will continue to uphold the values of integrity, fostering a culture of honesty, and nurturing an environment where genuine learning thrives providing a foundation of success for our students in their future careers.

Our pedagogical approaches will need to change to mediate the temptation of students who want to overly rely on this resource in their course work.

Here are some suggestions that you can implement in your classroom. 

• Make reflection and planning part of your course work. Encourage your students to spend time reviewing their learnings and planning their next steps as part of the learning process. Currently, artificial intelligence cannot compete with human ability in these tasks. After each lesson, set aside some time for students to discuss and digest what they've learned. Include a section for self-review and future planning in their written assignments, which will also be a part of their grades. This is something that students won't be able to accomplish effectively using AI tools, so feel free to explain this to them.

  • Example: Instead of a traditional paper assignment, which is even easier to cheat through now, assign a multimedia project and a self-reflection essay.

• Encourage students to utilize a variety of media. Instead of a traditional essay or brief written task, ask them to present their understanding via an audio recording, podcast, video presentation, speech, sketch, infographic, or a multifaceted multimedia project.

• Design tasks that relate to recent happenings or emerging discussions in the relevant domain; to challenges inherent to the local community, or to debates that have transpired within your own class. Alternatively, prompt your students to discern a correlation between the subject matter of the course and their individual experiences or understanding.

• Flipped Learning approach: Instruct students to study and understand the subject matter at home, and then put this knowledge into practice, show their understanding, and actively participate in class activities, either individually or in collaborative small groups.

  • View previous workshops on how to incoporate flipped learning in your classroom. 

• Integrate ChatGPT into your assignments. The more accustomed your students get with its advantages and disadvantages, the less likely they are to rely on it when trying to cut corners on assignments.

  • Example: to enhance your students' analytical skills, have them formulate a question for ChatGPT and analyze the generated response, highlighting its strengths and weaknesses.

• Educate your students on the safe usage of generative AI. Be aware that ChatGPT may share the personal information of account holders with third parties, such as vendors and service providers, as per their Privacy Policy. Ensure your students understand the importance of never divulging personal or sensitive data to AI chatbots. See Privacy Policy. 

• Ensure your students know how to correctly cite generative AI. 

  • ChatGPT outlines how it uses the information provided in its privacy policy.  

  • Cite generative AI correctly 

AI in the Classroom 

As generative AI continues to expand and make its way into industry, it is important we ensure our students are familiar with the tools and technology being created for their future fields. Listed below are a few examples of how generative AI is being used in various industries. 

Gaming and Entertainment:

• Procedural content generation for video games, including landscapes, characters, and levels.

• Generating realistic human-like faces for video game characters.

• Creating virtual worlds and environments.

Fashion and Design:

• Generating unique and innovative designs for clothing, accessories, and home decor.

• Virtual try-on for clothing and accessories, allowing customers to see how they would look.

• Creating personalized fashion recommendations based on individual preferences.

Art and Creativity:

• Generating artwork, including paintings, sculptures, and digital art.

• Assisting artists in creating new and unique pieces.

• Enhancing and transforming images and photographs.

Film and Animation:

• Creating realistic visual effects and computer-generated imagery (CGI) in movies.

• Generating virtual characters and creatures.

• Automating the animation process.

Healthcare and Medicine:

• Generating synthetic medical images for training and testing algorithms.

• Creating personalized treatment plans based on patient data.

• Assisting in drug discovery and molecule design.

Robotics and Automation:

• Generating robot motion and behavior.

• Simulating and optimizing robot tasks and movements.

• Creating virtual training environments for robots.

Advertising and Marketing:

• Generating personalized content and advertisements based on customer preferences.

• Creating virtual spokespersons and influencers.

• Designing customized user experiences and interfaces.

Music and Audio:

• Composing original music and melodies.

• Enhancing audio quality and removing noise.

• Creating virtual instruments and synthesizers.

Architecture and Interior Design:

• Generating building designs and floor plans.

• Simulating and visualizing interior design concepts.

• Assisting in urban planning and landscape design.

Data Augmentation:

• Generating synthetic data for training machine learning models.

• Increasing the size and diversity of datasets.

• Addressing privacy concerns by generating privacy-preserving synthetic data.

Please note that this list is not exhaustive, and generative AI is continually finding new applications in various industries as research and development progress.

AI in Assessments 

For assignments where generative AI is not allowed, here are a few tips for detecting the use of generative AI and helping ensure students don't use it. 

Clear Communication

• It is important to clearly communicate your expectations to your students. This should be done on the syllabus and specified for each assignment. 

• Remind your students of the university's academic integrity policy. 

Rethink Assessment Questions

• Run your assessment questions through ChatGPT.  It is important to run them a few times so you can see the various outputs students could turn in and learn the likely answers ChatGPT or other generative AI might generate. 

• Create questions that require reflecting on personal experiences or in class discussions. 

• Use multiple assignments and methods to create a history of student's writing styles to use as comparison for their personal writing abilities and voice. 

• Keep in mind, AI generated responses typically have a tone of voice that seems overly professional, grammatically exact, and detached. 

Strategies to Deter Academic Misconduct

Submitting assignments created or enhanced by Generative AI when not approved by the course instructor is academic misconduct. It is similar to paying an individual to complete your assignments, write your papers, or take your tests. Here are some tips to mitigate cheating and ensure that your students are getting the most out of their educational experience.

Or as a hallucinating AI would say, “Using AI to whip up or boost your work when it's not really asked for or okayed is pretty much cheating. It's like paying someone else to pen your essay, sit your exam, or get your work done. Here are a few pointers on keeping cheating in check in this age of AI magic.”

• Implement Consistent and Clear Communication in your course. The best way to deter academic misconduct is to address the elephant in the room. 

• Discuss the policy on academic misconduct, discuss when and when not to use AI for each of your assignments throughout the semester.

• Give specific examples of how generative AI can help and hinder their academic progress.

• Be specific and real with the students about your concern for their academic progress if they use AI to cheat.

• Build relationships with your students by ensuring them that you want what they want, to be successful in their future careers. 

• Ask pointed questions through out the semester: Why is integrity important? Are you getting the most out of this class? Are you ensuring that you are prepared for your future career?

• Run your assignments through generative AI and discuss the results with your students. Generative AI does not produce the same results each time, but the results will be similar. 

• Learn to recognize some key components to AI produced text.

  • Often very formal (unless asked to use a different tone) and systematic utilizing perfect grammar and sentence compensation.

  • Consider students previous writing and compare for a dramatic difference.

  • Ask students to handwrite every other assignment. Research shows some improvement in mixing both methods of writing.

  • Often very verbose using multiple paragraphs to illustrate a point. Additionally, AI produced text will repeat, though phrased differently throughout the text.

  • Cite made up sources, though this is quickly changing with access to tools like Orchid, Research Gate, and Google Scholar. (Paid AI services are nearly perfect in citing sources)

  • Does not follow specific assignment guidelines by using sources not discussed in class.

  • Perfect use of grammar, editing, and the tone of the work is voiceless and impersonal.

  • General and predictable responses. For example, Some people believe that X is better than Y. However, there are well established foundations for X and Y with strong supporters of Y over X. 

• AI hallucination is when factual errors are written to look plausible but are factually incorrect. These happens often when referencing data from a specific “Lens”, but does not take into account the entire picture of events. 

Resources

Learn more about ChatGPT from reading the resources below. 

Online Courses and Tutorials:

• Fast.ai's "Practical Deep Learning for Coders": A practical course that covers various deep learning techniques, including GANs. Website: https://course.fast.ai/
• Stanford University's CS231n: "Convolutional Neural Networks for Visual Recognition": A renowned course that covers deep learning topics, including GANs. Website: http://cs231n.stanford.edu/

Books:

• Generative Deep Learning by David Foster: This book provides a comprehensive introduction to generative models, including GANs, and their applications. Website: https://www.oreilly.com/library/view/generative-deep-learning/9781492041931/
• Deep Learning by Ian Goodfellow, Yoshua Bengio, and Aaron Courville: Although not focused solely on generative AI, this book provides a detailed understanding of deep learning, including GANs. Website: http://www.deeplearningbook.org/

Research Papers and Publications:

• "Generative Adversarial Networks" by Ian Goodfellow et al.: The original research paper that introduced GANs. Paper: https://arxiv.org/abs/1406.2661
• "Progressive Growing of GANs for Improved Quality, Stability, and Variation" by Tero Karras et al.: A significant advancement in GANs that enables the generation of high-quality images. Paper: https://arxiv.org/abs/1710.10196
• "CycleGAN: Unpaired Image-to-Image Translation Using Cycle-Consistent Adversarial Networks" by Jun-Yan Zhu et al.: Introduces the CycleGAN model for image-to-image translation without paired training data. Paper: https://arxiv.org/abs/1703.10593

Online Platforms and Communities:

• GitHub: Explore GitHub repositories for open-source implementations of generative AI models and projects. Website: https://github.com/
  Papers with Code: Provides a collection of research papers, code implementations, and evaluation results for various topics, including generative models. Website: https://paperswithcode.com/
• Reddit: Join the subreddit r/MachineLearning or r/generativeai to engage in discussions, ask questions, and learn from the community. Website:
  • • https://www.reddit.com/r/MachineLearning/
    • https://www.reddit.com/r/generativeai/