ICCS 2022 Keynotes

Title: Tractable Probabilistic Models for Ethical and Causal AI

Abstract: Among the many ethical dimensions that arise in the use of ML technology, three stand out as immediate and profound: enabling the interpretability of the underlying decision boundary, addressing the potential for learned algorithms to become biased against certain groups, and capturing blame and responsibility for a system’s outcomes. In this talk, we advocate for a research program that seeks to bridge tractable (probabilistic) models for knowledge acquisition with rich models of autonomous agency that draw on philosophical notions of beliefs, intentions, causes and effects.

Title: Qualitative Spatial Evaluation of Sketch Maps

Abstract: Sketch Mapping, i.e. drawing a map on a piece of paper, is a common method to investigate human spatial knowledge. To evaluate, how complete, correct and generalized a person’s spatial knowledge is, we analyze qualitative spatial relations among the sketched features and compare them to relations between corresponding features in city maps. Since the sketched information is often generalized, our research investigates how generalization and incompleteness affect qualitative spatial relations at different levels of abstraction.

Title (Preliminary): Cognitive Memory – For Language, Learning, and Reasoning 

Abstract: TBA