When Will Robots Be Sentient?

Zohar Bronfman, Simona Ginsburg, Eva Jablonka

פרסום מחקרי: פרסום בכתב עתמאמרביקורת עמיתים


The current failure to construct an artificial intelligence (AI) agent with the capacity for domain-general learning is a major stumbling block in the attempt to build conscious robots. Taking an evolutionary approach, we previously suggested that the emergence of consciousness was entailed by the evolution of an open-ended domain-general form of learning, which we call unlimited associative learning (UAL). Here, we outline the UAL theory and discuss the constraints and affordances that seem necessary for constructing an AI machine exhibiting UAL. We argue that a machine that is capable of domain-general learning requires the dynamics of a UAL architecture and that a UAL architecture requires, in turn, that the machine is highly sensitive to the environment and has an ultimate value (like self-persistence) that provides shared context to all its behaviors and learning outputs. The implementation of UAL in a machine may require that it is made of "soft"materials, which are sensitive to a large range of environmental conditions, and that it undergoes sequential morphological and behavioral co-development. We suggest that the implementation of these requirements in a human-made robot will lead to its ability to perform domain-general learning and will bring us closer to the construction of a sentient machine.

שפה מקוריתאנגלית
עמודים (מ-עד)183-203
מספר עמודים21
כתב עתJournal of Artificial Intelligence and Consciousness
מספר גיליון2
מזהי עצם דיגיטלי (DOIs)
סטטוס פרסוםפורסם - 1 ספט׳ 2021

הערה ביבליוגרפית

Publisher Copyright:
© 2021 World Scientific Publishing Company.

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