Description:
In a higher ed galaxy not so far away, departments across campus are exploring AI speech engines—each hoping to find the one tool powerful enough to transcribe lectures, fuel research, and support accessibility without accidentally summoning the Dark Side of inaccurate output.
Come listen to a panel who have explored and navigated asteroid fields of demos, pilots, and vendor promises. They’ll discuss what “accuracy” truly means (because not all engines hear like a protocol droid), which factors determine a good transcription match for diverse academic needs, and what hidden considerations—privacy, cost, language support, security, discipline specific vocabulary—must be evaluated before choosing a speech engine worthy of the Jedi Archives.
IT professionals will leave with insights, cautionary tales, and perhaps renewed hope that with the right tools—and a bit of humor—the Force of good technology decision making can prevail.
About this event:
Presenters:
- Ann Fredricksen, Coordinator of Accessible Media, DRES
- Bob Dignan, ASSOC DIR INSTRN MEDIA RSRSC, CITL
- Lawrence Angrave, TCH PROF, Computer Science
Track:
Make It So with Data and AI — Leverage AI and predictive analytics to chart courses no one has calculated before.
Experience Needed:
Beginner
Learning Outcome:
Understand accuracy you will—beyond simple numbers, its true meaning learn.
Evaluate speech engines with clarity you must, considering context, domain, and the chaos of human voices.
Aware you will become of hidden factors—privacy, accessibility, integration—much to consider, yes.
Judge when human review needed is; rely on machines alone, wise it is not.
Balance speed, cost, and quality you shall, for harmony in your institution this brings.
Choose a speech engine with confidence you will, guided by knowledge, not vendor Sith tricks.
Maximum Capacity:
No maximum capacity
Additional Keywords:
automatic speech recognition, AI
Where and When:
June 4, 2026 from 3:15 pm to 4:00 pm- Alma Mater