Definitions of AI (What is it?)

LLMs, Chatbots, Data Analytics……Machine Learning, Neural Networks

We use more precise language…..

Suggestion by Rich Radke: (AI snake Oil required reading)

ECSE Faculty our stance - Knowledge and Thoroughness, - last step…

Knowledge: use all tools to gather knowledge, to ask questions freely, and start projects.

Assessment is AI-free? (Discussion about how to do this…from faculty)

General RISKS - Benefit analysis of AI use

Ethics: NDA issue - For profit (RPAi club - Aashrut)

https://www.linkedin.com/posts/katyayini_aisnakeoil-ethicalai-aiandsociety-activity-7356354985506267139-vh3S

Where it falls short?

Non-replicability of output issues (different answers for same questions)

Why isn’t a reference enough?

Pitfalls

Knowledge vs. understanding vs. critical thinking

“What if I don’t want to use it? I learn better without it.”

*Use cases (Department John Wen Quantum computing saved) curate for faculty learning

Challenge: Do an example traditionally and compare to AI?