Human- versus Artificial Intelligence

AI is one of the most debated subjects of today and there seems little common understanding concerning the differences and similarities of human intelligence and artificial intelligence. Discussions on many relevant topics, such as trustworthiness, explainability, and ethics are characterized by implicit anthropocentric and anthropomorphistic conceptions. In addition, this lack of understanding may lead to the pursuit of human-like intelligence as the golden standard for Artificial Intelligence. By presenting and discussing three notions on the similarities and differences of human- and artificial intelligence, this paper aims to substantiate possible future research objectives. These notions concern: 1) the fundamental constraints of human (and artificial) intelligence, 2) human intelligence as one of many possible forms of general intelligence, and 3) the high potential impact of multiple forms of narrow-hybrid AI systems. For the time being, AI systems will have fundamentally different cognitive qualities and abilities than biological systems. For this reason, a most prominent issue is how we can use (and collaborate with) these systems as effectively as possible? For what tasks and under what conditions, decisions are safe to leave to AI and when is human judgement required? How can we capitalize on the strengths of human intelligence and how to deploy AI systems effectively to complement and compensate for the inherent constraints of human cognition. Should we pursue the development of AI ‘partners’ with human(-level) intelligence or should we focus at supplementing human constraints and limitations. In order to answer these questions, in professional settings and teams, humans collaborating with AI systems have to develop an adequate mental model of the underlying generic ‘psychological’ operating mechanisms of AI systems. So, in order to obtain well-functioning human-AI systems, Intelligence Awareness in humans needs to be addressed more emphatically.