Prognozmis

Prognozmis is a term used to describe a critical approach to forecasting that concentrates on the epistemology and practical consequences of forecast errors. It encompasses the study of misforecasting, uncertainty, and the social effects of predictive models.

Etymology: the word combines "prognoz" (forecast, prediction) with the suffix "-ism", reflecting a focus on a methodological stance rather than a specific technique.

Origins and development: The term emerged in online risk-discussion communities in the early 2010s and appeared in a small number of scholarly works in the 2020s as part of debates about the reliability of predictive analytics.

Key ideas include emphasizing calibration and uncertainty, comparing forecast ensembles, and promoting robust decision making that remains viable across diverse futures. It also calls for transparent communication of limitations and potential biases.

Methods commonly used in prognozmis practice involve backtesting forecasts against observed outcomes, studying systematic errors, analyzing cognitive biases in interpretation, and using scenario planning to illustrate a range of possible futures.

Applications span climate policy, macroeconomics and market risk, public health forecasting, disaster preparedness, and technology roadmapping, wherever decision makers must plan under uncertainty and contend with imperfect predictive models.

Critics argue that prognozmis risks becoming a vague umbrella that undermines trust in reliable methods if used to dismiss proven forecasts. Proponents respond that it highlights necessary humility and governance around predictive work.

See also forecasting, predictive analytics, risk communication.