most citedEffects of data ambiguity and cognitive biases on the interpretability of machine learning models in humanitarian decision making

3 citations · 3 across the 1 of their papers we have counts for

collaborators

2 papers

cs.LG2019★ 3 cited

Effects of data ambiguity and cognitive biases on the interpretability of machine learning models in humanitarian decision making

David Paulus, Gerdien de Vries, Bartel Van de Walle

The effectiveness of machine learning algorithms depends on the quality and amount of data and the operationalization and interpretation by the human analyst. In humanitarian respo…

cs.MA2018

Towards Agent-based Models of Rumours in Organizations: A Social Practice Theory Approach

Amir Ebrahimi Fard, Rijk Mercuur, Virginia Dignum +2

Rumour is a collective emergent phenomenon with a potential for provoking a crisis. Modelling approaches have been deployed since five decades ago; however, the focus was mostly on…