Q.No.3. Explainable AI (XAI) techniques aim to make machine learning models more ____

Explainable AI (XAI) techniques aim to make machine learning models more transparent. Transparency in machine learning models is crucial for users to understand how models make decisions, which enhances trust and accountability in AI systems. By employing XAI techniques, developers can provide insights into the inner workings of their models, elucidate the features that influenced decisions, and demonstrate compliance with regulations. This ongoing need for explainability is especially pertinent in fields such as healthcare, finance, and autonomous systems where the stakes are high and decisions can significantly impact lives and society at large. XAI encourages the integration of interpretability into the design of machine learning algorithms, thereby improving not only user acceptance but also facilitating better model debugging and improvement.