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In an era where artificial intelligence is becoming increasingly prevalent in our daily lives, equipping students with AI literacy is more important than ever. Understanding how AI works, its ethical implications, and its real-world applications can prepare students to navigate and thrive in an AI-driven world. In a recent workshop during the 2024 Summer Faculty EdTech Bootcamp, “Teaching AI Literacy to Your Students,” Alan Cafferkey, Ph.D., Director of Education Technologies, guided faculty through the process of introducing AI concepts into their curriculum.
Key takeaways from the presentation
Understanding AI and Generative AI
The workshop started by differentiating between various forms of AI. A particular focus was on Generative AI, which refers to systems capable of creating new content on their own, like generating text, images, video, or audio. Generative AI is a tool that generates text, but not necessarily the truth, highlighting the importance of critical thinking when using AI.
Hallucinations and Misinterpretations
Practical Applications of Generative AI
The session explored the various uses of Generative AI, such as summarization, classification, translation, and text generation. Beyond text, tools like DALL-E and Stable Diffusion were highlighted for image generation, and GitHub Copilot for coding. These tools can be integrated into classroom activities to make AI concepts more tangible and engaging for students. See I put 7 leading AI image generators to the test with the same prompt — here’s the winner | Tom’s Guide
Intro to Prompt Engineering
One of the core skills discussed was “Prompt Engineering”—crafting inputs for AI models to yield t
he desired outcomes. Alan explained the elements of a prompt, including providing context, clear instructions, and examples. Understanding how to structure prompts is crucial for effectively interacting with AI tools.
Can AI Be Detected?
A common question is whether AI-generated content can be detected reliably. The workshop addressed this, noting that current tools cannot always reliably detect AI-generated text due to the inherent randomness in AI models. Instead, Alan suggested using traditional methods like the Trivium—Grammar, Logic, and Rhetoric—to critically evaluate content.
Suggested Resources
To continue building AI literacy, Alan recommended a variety of resources, including specific podcasts like “Super Data Science Podcast” and “This Day in AI,” which offer ongoing insights into AI developments.
The Fordham Faculty AI Interest Group also curates a magazine on Flipboard and organizes events during the semester.
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