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Mammalian Value Systems

Authors: Gopal P. Sarma; Nick J. Hay;

Mammalian Value Systems

Abstract

Characterizing human values is a topic deeply interwoven with the sciences, humanities, political philosophy, art, and many other human endeavors. In recent years, a number of thinkers have argued that accelerating trends in computer science, cognitive science, and related disciplines foreshadow the creation of intelligent machines which meet and ultimately surpass the cognitive abilities of human beings, thereby entangling an understanding of human values with future technological development. Contemporary research accomplishments suggest increasingly sophisticated AI systems becoming widespread and responsible for managing many aspects of the modern world, from preemptively planning users' travel schedules and logistics, to fully autonomous vehicles, to domestic robots assisting in daily living. The extrapolation of these trends has been most forcefully described in the context of a hypothetical "intelligence explosion," in which the capabilities of an intelligent software agent would rapidly increase due to the presence of feedback loops unavailable to biological organisms. The possibility of superintelligent agents, or simply the widespread deployment of sophisticated, autonomous AI systems, highlights an important theoretical problem: the need to separate the cognitive and rational capacities of an agent from the fundamental goal structure, or value system, which constrains and guides the agent's actions. The "value alignment problem" is to specify a goal structure for autonomous agents compatible with human values. In this brief article, we suggest that ideas from affective neuroscience and related disciplines aimed at characterizing neurological and behavioral universals in the mammalian class provide important conceptual foundations relevant to describing human values. We argue that the notion of "mammalian value systems" points to a potential avenue for fundamental research in AI safety and AI ethics.

Country
Slovenia
Keywords

FOS: Computer and information sciences, Computer Science - Machine Learning, Artificial Intelligence and Robotics, Computer Science - Artificial Intelligence, Economics, Political Science, FOS: Political science, Computer Science - Human-Computer Interaction, Psychiatry and Psychology, Social and Behavioral Sciences, Science and Technology Studies, Human-Computer Interaction (cs.HC), Machine Learning (cs.LG), Behavior and Behavior Mechanisms, Computer Science - Computers and Society, Computer Science - Robotics, Engineering, Sociology, Computers and Society (cs.CY), Medicine and Health Sciences, Physical Sciences and Mathematics, Psychology, International Economics, Computer Engineering, Biology, Computer Sciences, International Relations, Organisms, Life Sciences, Robotics, Political Economy, FOS: Sociology, Politics and Social Change, FOS: Psychology, Sociology of Culture, Artificial Intelligence (cs.AI), Political Theory, Anthropology, Animal Studies, Robotics (cs.RO)

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
8
Top 10%
Average
Top 10%
Green
hybrid