Kahan is a numerical analyst, and probably had extensive experience with worrying about known numerical analysis pitfalls, such as the tablemaker's dilemma, which means you don't necessarily know a priori how much precision you need on the input or intermediate computations to get the desired output precision.
As it turns out, though, most people don't need more than 3 or 4 decimal digits of precision, so while a float may easily accumulate enough error to corrupt that last needed digit, a double tends to be more than roomy enough for almost everybody.
As it turns out, though, most people don't need more than 3 or 4 decimal digits of precision, so while a float may easily accumulate enough error to corrupt that last needed digit, a double tends to be more than roomy enough for almost everybody.