Marco Piumetti & Nik Lygeros

Beyond Efficiency: Towards a Sustainable and Robust Synergy Between Natural and Artificial Intelligence

pp 440–449

Intelligent Systems Conference Lecture Notes in Networks and Systems ((LNNS,volume 2075))

Abstract

The accelerating convergence between natural (NI) and artificial intelligence (AI) requires a re-examination of what it means to think, learn and understand in order to define a strategic mix. While AI systems now surpass humans in processing and analytical tasks, they still lack the capacity for meaning, intentionality and awareness that characterize natural cognition as we can see it even with strategic games like chess or go. This paper develops a comparative framework for NI and AI across different dimensions showing that humans learn through meaning while machines learn through correlation. Drawing on cognitive psychology (Kahneman’s dual-process theory), AI paradigms (symbolic, neural and neurosymbolic) and sustainability science, the paper explores how natural adaptability and ethical discernment can inform the development of artificial systems that combine analysis with contextual understanding. This approach seeks to guide the development of cognitive systems that are not only efficient but also sustainable and robust.

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