Zoe Braiterman — AI, ML, AppSec, and a dose of data protection

Artificial intelligence can help analyze security data, but the systems using it also need protection themselves. Zoe Braiterman brings a background in data science, organizational thinking, and OWASP community work to an early conversation about that two-way relationship. Chris and Robert ask how artificial intelligence and machine learning differ, where automation is already appearing, and what pattern recognition might contribute to application security. The discussion moves from familiar examples such as fraud detection toward the data, models, and processes behind automated decisions. Zoe emphasizes the human role in understanding those systems and protecting the information they use. This archive episode captures exploratory thinking about AI and AppSec while encouraging practitioners to keep asking questions and learning together.

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Connect with Zoe Braiterman:
→ Zoe Braiterman on LinkedIn

Mentioned in this episode:
→ OWASP Women in AppSec — project repository

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Chapters:
00:00 AI, machine learning, and AppSec with Zoe Braiterman
02:03 Zoe’s path through data science into security
03:31 Community work with OWASP Women in AppSec
04:30 Distinguishing AI and machine learning
06:25 What autonomy means for a process
07:19 Examples of AI applications
10:18 Fraud detection and learning from data
14:25 Possible uses of AI in application security
16:19 Smarter tools and penetration testing
18:39 Pattern recognition in security data
21:08 Protecting the data and processes behind AI
23:45 Learning resources and closing advice