Human intelligence, ambidexterity and ai: Reflections on a data cognification case study in an underwater scenario

We present an experimental study with three concurrent goals: a) to link AI-driven processes with some fundamental theoretical assumptions of management theory; b) to challenge the current assumption that modern synthetic intelligences might be easily "human-comparable"; c) to present the results a neural net has returned that was trained with real data from an underwater exploration scenario, with implications on the kind of the nature of this synthetic intelligence.