AI for Education:

Using AI to Save Your Sanity

Jake Sherlock

Instructor, Journalism and Media Communications

College of Liberal Arts

Our agenda for today

1. Overview of AI basics – common terminology, what it can and can’t do, and some of the ethical concerns
2. Explore tools that can help
1. Interview your own notes and research
2. Create visuals that will add more information and understanding to your teaching materials
3. Build your own simple AI bots
4. Improve your writing
3. Prompts that can help you make the most of AI
4. Q&A

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You can find these slides and additional resources that I reference today at JakeSherlock.com

Overview of AI Basics

You can find these slides and additional resources that I reference today at JakeSherlock.com

Common terminology

Artificial intelligence: A term coined in the 1950s by John McCarthy to describe efforts to develop machines that could reason and solve problems in human-like ways. Now widely applied to any software that can identify patterns in data.

Artificial general intelligence: A label computer scientists apply to the still-unachieved goal of creating AI that can reason and learn in broad ways; apply those skills to new realms it hasn't encountered before; and grow in unpredictable ways.

Autonomy: The capacity of AI to act on its own to achieve a goal without specific human direction at every step — in the physical world (self-driving cars), in virtual environments (non-player characters in games) or on computer networks (personal assistants).

— Scott Rosenberg, Axios

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You can find these slides and additional resources that I reference today at JakeSherlock.com

Common terminology 2

Generative AI (or genAI): Machine-learning based AI that trains on sets of real-world data — most commonly images and text — to learn to predict or "generate" the next word or pixel in a sequence, creating the capacity to "write" new texts and "make" new images.

Training data: The data initially provided to an AI model for it to create its map of relationships.

Supervised and unsupervised training: If the training data has been labeled by humans in advance, giving the AI signposts and hints for how to organize it, the training is considered supervised. In unsupervised training, the model is simply turned loose on raw data, and the model gradually draws connections … .

— Scott Rosenberg, Axios

You can find these slides and additional resources that I reference today at JakeSherlock.com

Common terminology 3

Language Model: A type of machine learning module that is designed to understand, predict and then generate human language.

Large Language Model: A language model that uses a larger dataset than a typical LM. There is no industry standard between what constitutes large datasets and standard data sets, so you may see LM and LLM used in the same way depending on the writer’s interpretation.

Generative pre-trained transformer (GPT): Open AI invented this particular type of LLM – first, the GPT is trained in an unsupervised fashion, followed by a supervised training that is designed to “fine tune” the results.

You can find these slides and additional resources that I reference today at JakeSherlock.com

Common terminology 4

Hallucination: When the AI system can’t find the right answer, it reaches for the “next best” answer. This is where you really need to be careful – hallucinations can sound correct.

Deepfake: An image, graphic or video that was created with AI for the sole purpose of duping folks. What used to take folks days to do with Photoshop can now be done in moments.

Prompts: What we tell an AI system to get it to produce the content we want.

Prompt engineering: The practice of trying to perfect prompts. A cottage industry has sprung up around this – rather than build your own AI, just use an existing AI and learn how to tell it to do what you want it to do.

Prompt injection: Like prompt engineering, but with the intent of getting around the safeguards creators have put into their systems. Examples: Generating Deepfakes, generating instructions on how to build a bomb, etc.

You can find these slides and additional resources that I reference today at JakeSherlock.com

Ethical concerns

• Cheating
• Dependence on AI systems
• Bias, discrimination, fairness and representation
• Privacy and data protection
• Environmental impacts
• Societal and economic impacts
• What else?

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Caption: Concerned teacher, generated with Google Fx.

Tool time: Let’s play!

But first, any questions so far?

Tools to interview your data

• Google Notebook LM – we’ll take a look at my Media Ethics notebook and all the things it can do, including:
• Podcasts
• Summaries
• Study Guides
• Timelines
• Claude – Have AI scan and summarize complex documents
• CoPilot – Can also scan and summarize complex documents
• Otter – Interview and transcription software

Build tools for you and/or your students

• Poe — A sandbox for playing with AI.
• Sherlock5000 automated reply generator
• JMC Interview Bot
• Browse AI – Keep an eye on things online, get updates in your email

Image generation

• Google FX
• Dall-E
• Gemini
• Poe

Writing prompts

AI does what it thinks we’re telling it to do, for better or for worse

Common prompts to try

• Informational Queries:
• "What is the best time to visit Paris?"
• "Explain the concept of quantum computing.”
• “Can an American purchase land in Tuscany and live there?”
• Creative Writing:
• "Write a short story about a character who discovers a hidden world."
• "Compose a poem inspired by the beauty of nature."
• Editing”
• Check the following text for grammar, spelling and AP Stylebook errors.
• Highlight all adjectives and adverbs

Common prompts to try 2

• Content Creation
• “generate a cartoon image of a college student taking an exam on a computer and looking confident. The student should be a person of color”
• “An image of a person locked happily in a steel pod”
• “Kant vs. Mill in a boxing match”
• Cut the complexity
• "Summarize these articles: [insert URLs]. Contextualize why these announcements are important to [industry]."
• "Explain the concept of blockchain technology in simple terms.”
• “What are some synonyms for [insert term or phrase]
• Role-Based Prompts
• "Act as a personal trainer and suggest a workout routine for beginners.”
• "Act as a travel guide and recommend places to visit in Tokyo.”
• "Act as a marketing expert and explain three essential digital marketing strategies."

Q&A time!

What can I help you with?

Let’s connect!

• Connect with me on LinkedIn
• Email me at Jake.Sherlock@colostate.edu
• Look for more resources from me at JakeSherlock.com

Thank you