Decoding AI in Cybersecurity: Navigating Supervised, Unsupervised Learning, and the Critical Need for Explainability.

In this week's publication, we delve deeper into the intricate world of AI algorithms, distinguishing the nuanced roles of supervised and unsupervised learning. But we won't stop there. We'll unravel the often-overlooked yet vital aspect of AI - explainability. Why is it crucial? This post serves as the second part: Part 1: We examined the Detection Engineer’s Perspective, emphasizing why 'Explainability Matters and Context is King.' (link) Part 2: We're here to dissect 'Supervised vs Unsupervised Learning and the Importance of Explainability.' Part 3: Stay tuned for practical 'Recommendations for Cyber Builders when integrating AI in the UX of their cybersecurity solutions and programs.' I don’t want to spend too much time on machine learning definition, but here is a very short reminder and then we’ll go into the specifics for cybersecurity. Supervised learning in AI is akin to a student learning under the guidance of a teacher. The 'teacher' (in this case, the training data) provide

In this week's publication, we delve deeper into the intricate world of AI algorithms, distinguishing the nuanced roles of supervised and unsupervised learning. But we won't stop there. We'll unravel the often-overlooked yet vital aspect of AI - explainability. Why is it crucial? This post serves as the second part: Part 1: We examined the Detection Engineer’s Perspective, emphasizing why 'Explainability Matters and Context is King.' (link) Part 2: We're here to dissect 'Supervised vs Unsupervised Learning and the Importance of Explainability.' Part 3: Stay tuned for practical 'Recommendations