This frequencies vs. probabilities issue is one of the controversies in heuristics & biases research, and Kahneman, Tversky, and others dispute Gigerenzer's take. For instance, here (pdf, see p. 8) is what Gilovich & Griffin have to say in their introduction to the book Heuristics and Biases (emphasis added):

In fact, presenting frequencies rather than probabilities sometimes makes judgment distinctly worse (e.g., Griffin & Buehler, 1999; Treadwell & Nelson, 1996), sometimes makes judgments distinctly better (e.g., Tversky & Kahneman, 1983; Koehler, Brenner, & Tversky, 1997) and quite often leaves the quality of judgment largely unchanged (Brenner, Koehler, Liberman, & Tversky, 1996; Griffin & Buehler, 1999). Even more troublesome for the evolution/frequency argument, Kahneman and Tversky’s original explanation of the probability—frequency discrepancy (Kahneman & Tversky, 1982a; Tversky & Kahneman, 1983) provides a unified account of when frequency formats improve judgments and when they do not (e.g., Sloman, Slovak, & Over, 2000).

Critics claim that assessments of single-event probabilities are unnatural, and that only a frequency format is consistent with how the mind works (Cosmides & Tooby, 1996; Gigerenzer, 1991b, 1994; Pinker, 1997). Kahneman and Tversky argued, in contrast, that representing problems in terms of frequencies tends to evoke mental models that facilitate the detection of set inclusion relations and thus improves judgment — and this view has received considerable support from the studies of Sloman and others (e.g., Evans, Handley, Perham, Over, & Thompson, 2000; Girotto & Gonzalez, 2001; Sloman & Over, in press; Sloman et al., 2000).