ABOUT THIS EPISODE
In this episode of Lunchtime BABLing, BABL AI CEO Dr. Shea Brown introduces the new AI Test, Evaluation, & Red Teaming Specialist Bootcamp—a hands-on, technical program designed to train the next generation of AI assurance professionals.
Drawing directly from BABL AI’s internal methodologies used to audit and evaluate high-risk AI systems across industries, this bootcamp addresses one of the most critical gaps in the AI ecosystem: the lack of practical training in how to design, execute, and interpret rigorous AI testing and red teaming in real-world contexts.
Dr. Brown explains:
-Why AI testing, evaluation, and red teaming are essential for high-risk AI systems
-How BABL AI developed its internal, risk-driven testing and assurance frameworks
-The difference between auditing AI systems and directly evaluating and validating them
-What participants will learn during the five-week, hands-on bootcamp
-The prerequisites, structure, and technical depth of the program
-How this bootcamp will evolve into BABL’s new AI Test, Evaluation, & Red Teaming Specialist Certification
-This exclusive early adopter cohort is limited to approximately 30 participants and is designed for professionals with foundational knowledge in AI auditing, governance, or assurance who want to develop practical technical capabilities in AI evaluation and red teaming.
-Participants will learn how to move systematically from an AI use case to defensible test results—building real test plans, executing evaluations, and developing assurance-relevant conclusions using BABL’s proven frameworks.
Take the test to see if you are a good candidate for the AI Test, Evaluation, & Red Teaming Specialist Bootcamp: https://zfrmz.eu/RBroC4VLZ9I41ihKl1XV
Learn more about BABL AI Certifications: www.babl.ai
About Lunchtime BABLing:
Lunchtime BABLing is hosted by Dr. Shea Brown, CEO of BABL AI, an independent AI assurance firm that audits algorithms for bias, risk, and governance. The podcast explores AI auditing, governance, regulation, and technical assurance practices shaping the future of trustworthy AI. Check out the babl.ai website for more stuff on AI Governance and
Responsible AI!
Drawing directly from BABL AI’s internal methodologies used to audit and evaluate high-risk AI systems across industries, this bootcamp addresses one of the most critical gaps in the AI ecosystem: the lack of practical training in how to design, execute, and interpret rigorous AI testing and red teaming in real-world contexts.
Dr. Brown explains:
-Why AI testing, evaluation, and red teaming are essential for high-risk AI systems
-How BABL AI developed its internal, risk-driven testing and assurance frameworks
-The difference between auditing AI systems and directly evaluating and validating them
-What participants will learn during the five-week, hands-on bootcamp
-The prerequisites, structure, and technical depth of the program
-How this bootcamp will evolve into BABL’s new AI Test, Evaluation, & Red Teaming Specialist Certification
-This exclusive early adopter cohort is limited to approximately 30 participants and is designed for professionals with foundational knowledge in AI auditing, governance, or assurance who want to develop practical technical capabilities in AI evaluation and red teaming.
-Participants will learn how to move systematically from an AI use case to defensible test results—building real test plans, executing evaluations, and developing assurance-relevant conclusions using BABL’s proven frameworks.
Take the test to see if you are a good candidate for the AI Test, Evaluation, & Red Teaming Specialist Bootcamp: https://zfrmz.eu/RBroC4VLZ9I41ihKl1XV
Learn more about BABL AI Certifications: www.babl.ai
About Lunchtime BABLing:
Lunchtime BABLing is hosted by Dr. Shea Brown, CEO of BABL AI, an independent AI assurance firm that audits algorithms for bias, risk, and governance. The podcast explores AI auditing, governance, regulation, and technical assurance practices shaping the future of trustworthy AI. Check out the babl.ai website for more stuff on AI Governance and
Responsible AI!
English
United States
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