What is AI Explainability? Explained in Everyday Language for AI Beginners

As large language models and multimodal systems become increasingly prevalent, a major question arises: Are they safe?

In developing today’s AI systems, it’s essential to evaluate safety across querying, processing, and storage. This has led to frequent discussions about AI safety. While the concept of AI safety is quite self-explanatory, focusing on preventing harm from AI systems, the term “AI explainability” might not be familiar to everyone. So let’s talk about it :)

So what is AI explainability?

AI explainability refers to making AI decisions understandable to humans, highlighting the importance of transparency in AI operations.

(I know I’ve used cooking and recipes as analogies quite a lot in my previous articles — so here it is again!) AI explainability is like a cookbook that comes with your meal at a restaurant. Just as the cookbook explains how your meal was prepared, AI explainability reveals how AI systems arrive at their conclusions. It ensures the transparency of AI decisions, making them understandable to humans, similar to how a recipe clarifies the flavors in your dish. This clarity is crucial for trust, especially when AI decisions significantly impact our lives, akin to knowing the ingredients for dietary…