In a Regression Discontinuity Design RDD what is the key idea behind identifying causal effects

The key idea behind identifying causal effects in a Regression Discontinuity Design (RDD) is based on the assumption that individuals or units on either side of a specific threshold value are similar on average, except for the treatment status. By comparing the outcomes of units just above and just below the threshold, any difference in outcomes can be attributed to the treatment, thus providing an estimate of the causal effect. The RDD leverages the sharp discontinuity in treatment assignment, which occurs when units have a score above or below the threshold, to achieve identification of the causal effect