There is an escalating debate over the value and validity of memory-based dietary assessment methods (M-BMs). Proponents argue that despite limitations, M-BMs such as food frequency questionnaires (FFQs), provide valid and valuable information about consumed foods and beverages, and therefore can be used to assess diet-disease relations and inform public policy. In fact, over the past 60 years thousands of research reports using these methods were published and used to populate the United States Department of Agriculture's National Evidence Library, inform public policy, and establish the Dietary Guidelines for Americans. Despite this impressive history, our position is that FFQs and other M-BMs are invalid and inadmissible for scientific research and cannot be employed in evidence-based policy making. Herein, we present the empirical evidence, and theoretic and philosophic perspectives that render M-BMs data both fatally flawed and pseudo-scientific. First, the use of M-BMs is founded upon two inter-related logical fallacies: a category error and reification. Second, human memory and recall are not valid instruments for scientific data collection. Third, in standard epidemiologic contexts, the measurement errors associated with self-reported data are non-falsifiable (i.e., pseudo-scientific) because there is no way to ascertain if the reported foods and beverages match the respondent's actual intake. Fourth, the assignment of nutrient and energy values to self-reported intake (i.e., the pseudo-quantification of qualitative/anecdotal data) is impermissible and violates the foundational tenets of measurement theory. Fifth, the proxy-estimates created via pseudo-quantification are physiologically implausible (i.e. meaningless numbers) and have little relation to actual nutrient and energy consumption. Finally, investigators engendered a fictional discourse on the health effects of dietary sugar, salt, fat and cholesterol when they failed to cite contrary evidence or address decades of research demonstrating the fatal measurement, analytic, and inferential flaws presented herein.