To ensure the reliability and defensibility of predictive coding results, various sampling and validation techniques are employed. These include:

Control Sets: A randomly selected subset of documents that are independently reviewed by human experts to measure the accuracy of the AI model.
Statistical Sampling: Using statistical methods to determine the appropriate sample size for training and validation.
Recall and Precision Metrics: Quantifying the effectiveness of the AI model in identifying relevant documents (recall) and avoiding false positives (precision).