assummere

Assummere is a neologism used in speculative and technical discourse to describe the practice of explicitly adopting a simplifying assumption as a starting point for analysis, and then tracing the consequences of that assumption through the argument or model. The term is not widely standardized in major dictionaries and appears mainly in discussions of epistemology, decision theory, systematic modeling, and AI risk assessment. It serves to foreground the link between the choice of an assumption and the resulting inferences, highlighting how reasoning can depend on foundational premises.

The etymology of assummere is informal and interpretive, combining elements of “assume” with notions of summarizing or taking up a premise. In practice, an assummere is used as a deliberate methodological step: state a core assumption, justify it with context, and then summarize the potential outcomes or predictions that follow. The approach promotes transparency about limitations but can invite criticism when assumptions are overly strong or left untested.

Applications include scenario analysis, policy modeling, and simplifying simulations where tractability requires bounded assumptions. Proponents argue that assummere clarifies the reasoning process and makes subsequent conclusions more traceable, while critics caution that reliance on unexamined assumptions can distort results. Effective use typically involves sensitivity analysis, explicit qualification of uncertainty, and clear delineation between assumption-driven results and evidence-based conclusions.

See also: assumption, hypothesis, modeling, cognitive bias, scenario analysis.