CQAA May 2025
Testing the Untestable: Cracking the Code of AI Systems
About the Topic
How do you test a system that learns, evolves, and sometimes hallucinates? Testing AI systems is unlike anything we’ve encountered before—traditional methods fall short, and new challenges emerge at every turn. From validating opaque machine learning models to ensuring fairness, accuracy, and robustness, testers are navigating uncharted territory. The trends are real and AI is coming to a project near you.
In this session, Kevin Pyles takes you deep into the world of AI testing. Discover why AI systems demand a new mindset and innovative strategies, including adversarial testing, data validation, and ethical assessments. Learn practical techniques to identify hidden biases, test unpredictable outputs, and ensure your AI behaves as intended in real-world scenarios. Through practical examples and hands-on insights, Kevin will show you how to tackle the complexities of testing AI with confidence. Get real with the secrets of testing AI systems.
Key Learning Objective
About the Speaker
Kevin Pyles works for FamilySearch as an AI/ML SDET where he is testing test AI with AI. Yeah, it has come to that. He has been in the QA industry now for over 15 years with project, product, and management roles throughout. Kevin worked previously for test.ai where he was the Head of Product Kevin also served on the board for QA at the Point (a local testing meetup), and is an award-winning international speaker. Kevin believes AI and Python are the future of testing. Kevin is still spending too much time golfing and watching college football. He loves spending time with his 6 kids. He loves Brazilian food and pepperoni pizza, and can’t help himself when there is ice cream.
Registration
REGISTRATION IS REQUIRED TO ATTEND THIS PROGRAM.
Please register by May 19th, 2025 at www.cqaa.org.
If you have any questions, please contact info@cqaa.org.
Date: Wednesday, May 21st 2025, from 12:00pm-1:00pm
Location Webinar - https://zoom.us/j/95211786414?pwd=YBGnu97x36quiSsG6iuliGLGPiFF5C.1
