info/developer-roadmap
1
0
Fork 0
mirror of https://github.com/kamranahmedse/developer-roadmap.git synced 2025-08-26 02:25:35 +02:00
Code Issues Releases Wiki Activity

Fix broken URLs

Browse Source
This commit is contained in:
Kamran Ahmed
2025-04-26 12:56:24 +01:00
parent ebd34612a2
commit 3e059cc3e9
1 changed files with 1 additions and 8 deletions
Download Patch File Download Diff File Expand all files Collapse all files

7
src/data/roadmaps/ai-red-teaming/content/why-red-team-ai-systems@fNTb9y3zs1HPYclAmu_Wv.md
View File

@@ -1,10 +1,3 @@
# Why Red Team AI Systems?
AI systems introduce novel risks beyond traditional software, such as emergent unintended capabilities, complex failure modes, susceptibility to subtle data manipulations, and potential for large-scale misuse (e.g., generating disinformation). AI Red Teaming is necessary because standard testing methods often fail to uncover these unique AI vulnerabilities. It provides critical, adversary-focused insights needed to build genuinely safe, reliable, and secure AI before deployment.
Learn more from the following resources:
@article@What's the Difference Between Traditional Red-Teaming and AI Red-Teaming? - Cranium AI - Compares objectives, techniques, expertise, and attack vectors to highlight why AI needs specialized red teaming.
@article@What is AI Red Teaming? The Complete Guide - Mindgard - Details specific use cases like identifying bias, ensuring resilience against AI-specific attacks, testing data privacy, and aligning with regulations.
@article@The Expanding Role of Red Teaming in Defending AI Systems - Protect AI - Explains why the dynamic, adaptive, and often opaque nature of AI necessitates red teaming beyond traditional approaches.
@article@How red teaming helps safeguard the infrastructure behind AI models - IBM - Focuses on unique AI risks like model IP theft, open-source vulnerabilities, and excessive agency that red teaming addresses.