AUTHOR=Sims Matthew 

TITLE=Self-Concern Across Scales: A Biologically Inspired Direction for Embodied Artificial Intelligence

JOURNAL=Frontiers in Neurorobotics

VOLUME=Volume 16 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/neurorobotics/articles/10.3389/fnbot.2022.857614

DOI=10.3389/fnbot.2022.857614

ISSN=1662-5218

ABSTRACT=Intelligence in current AI research is measured according to designer assigned tasks that lack any relevance for the agent itself. As such, tasks and their evaluation reveal a lot more about our intelligence than about the possible intelligence of the agents which we design and evaluate. As a possible first step in remedying this, this paper introduces the notion of ‘self-concern’, a property of a complex system that describes its tendency to bring about states that are compatible with its continued self-maintenance. Self-concern, it is argued, is the foundation of the kind of basic intelligence found across all biological systems because it reflects such systems' existential tasks of continued viability. This paper aims to cautiously progress a few steps closer to a better understanding of some of the necessary organizational conditions that are central to self-concern in biological systems. By emulating these conditions in embodied AI, perhaps something like genuine self-concern in machines can be implemented in machines, bringing AI one step closer to its original goal of emulating human-like intelligence.