Transparency in Machine Learning

Transparency in machine learning refers to how clearly and openly the workings of a model are communicated and understood. It involves making insights about how decisions are made accessible, so users can see what factors influenced outcomes. This helps build trust, allows for easier identification of errors or biases, and ensures accountability. Essentially, transparent models reveal their processes in a way that stakeholders can interpret, which is vital for ethical and responsible use of AI systems in sensitive areas like healthcare, finance, and justice.