Dubito is a Latin word meaning ‘I doubt’. Famously, it is part of René Descartes’ deduction “Dubito ergo cogito; cogito ergo sum” which means “I doubt, therefore I think; I think therefore I am.”
Uncertainty occurs whenever a data observer or sensor is unsure of the exact value of the quantity being recorded. Examples might be a time of day, geographic location, or elevation. If many of these data points are collected and used to generate predictions using a machine-learning or regression algorithm, this uncertainty propagates throughout the model producing imprecise results.
Where we come in
Dubito tracks uncertainty through the model, showing the user the range of possible values the true predicted value could take. This enables decision makers to take into account all of possible outcomes and adjust their strategy accordingly. For example, if we're trying to predict the presence of something in a particular location, a precise prediction could potentially mislead decision makers, causing them to overlook certain areas they might have otherwise searched. There are clear applications of this in GeoIntelligence, Mining, and Reconnaissance.