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Home / Beyond AI Basics: What Faculty Actually Need to Know

Beyond AI Basics: What Faculty Actually Need to Know

Lecture hall with screens displaying VR headsets

April 10, 2025

Presenters: Tina Austin, UCLA Lecturer for Computational Biology

11am – 12pm | Zoom

What to Expect in this Showcase

 If March’s session got you thinking, this one will go further. Faculty are struggling to keep up with AI’s rapid evolution—but there’s a reason why some are thriving while others are overwhelmed. This session will dig into real faculty experiences and the strategies that are actually making a difference.


Key Questions We’ll Explore:

  • What’s the #1 mistake faculty make when integrating AI?
  • How do different disciplines use AI in ways you wouldn’t expect?
  • What does it take to stay ahead without being buried in AI updates?
  • What’s the missing piece? Why one-off AI talks aren’t enough for faculty success.

Why You Should Come:
If you want to go beyond the surface-level AI talk and figure out what actually works, this session is for you. But be warned—this isn’t a step-by-step how-to. It’s a deep dive into what’s changing and why faculty need more structured support. 

Presenter’s Bio: 

For the past four years, UCLA lecturer Tina Austin has been teaching AI ethics across biomedical research, computational biology, and communication. Recognized consecutively for contributions to AI innovation and education, Tina has worked to integrate AI across many disciplines, focusing on AI and bias while developing teaching strategies, custom AI tools, and faculty training programs since 2022. In 2024, Tina was awarded a UCLA-OpenAI EDU License through a competitive call for proposals and has led faculty development workshops. In 2025, she was recognized by ASU-GSV as a leading AI innovator. Her goal is to empower her students by finding their unique strengths while seeing AI’s benefits and pitfalls. 

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