Trueness and bias in measurement are often confused, but they have distinct meanings. Trueness refers to how close a measurement is to the true value, while bias indicates a systematic error that skews results away from the true value. The discussion highlights that bias has been historically used in statistical contexts, but the term trueness was introduced to emphasize a more positive aspect of accuracy. The distinction is significant in fields like statistics and measurement, where understanding the nuances can impact data interpretation. Overall, while trueness relates to accuracy, bias reflects systematic deviations from that accuracy.