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.The Application Security Podcast is brought to you by Security Journey.About Security JourneySecurity Journey provides application security education for developers and everyone in the software development lifecycle.→ Learn more about Security JourneyConnect with Zoe Braiterman:→ Zoe Braiterman on LinkedInMentioned in this episode:→ OWASP Women in AppSec — project repositoryFollow the Application Security Podcast:➜ Home➜ X➜ LinkedIn➜ YouTube➜ Instagram➜ FacebookChapters:00:00 AI, machine learning, and AppSec with Zoe Braiterman02:03 Zoe’s path through data science into security03:31 Community work with OWASP Women in AppSec04:30 Distinguishing AI and machine learning06:25 What autonomy means for a process07:19 Examples of AI applications10:18 Fraud detection and learning from data14:25 Possible uses of AI in application security16:19 Smarter tools and penetration testing18:39 Pattern recognition in security data21:08 Protecting the data and processes behind AI23:45 Learning resources and closing advice