Artificial Intelligence (AI) is changing the way we live and work, from speech recognition systems to self-driving cars.
But as AI becomes more ubiquitous, concerns about accountability and transparency are growing.
That's where Explainable AI comes in.
Explainable AI, or XAI for short, is an approach to developing AI that enables human beings to understand how it works and why it makes certain decisions.
To understand XAI, it's important to know that AI systems are often modeled on the human brain.
Just like the human brain, an AI system can have many layers of neurons that process and interpret information.
However, unlike the human brain, AI systems can't explain why they make certain decisions.
XAI seeks to change that by providing human-readable explanations for how the system arrived at a particular decision.
This is important not only for accountability and transparency but also for improving the performance of AI systems by allowing developers to identify and correct errors.
XAI is still a relatively new field, but it's one that's likely to become increasingly important as AI becomes more integrated into our lives.
With XAI, we can ensure that AI remains a tool for positive change and that its decisions are always made with human understanding and oversight.
