Toward the Starting Line: A Systems Engineering Approach to Strong AI

TL;DR

This paper advocates for a systems engineering approach to AGI, emphasizing the need for a conceptual leap and identifying cross-disciplinary opportunities to advance towards human-level AI.

Contribution

It introduces a system-theoretic, engineering-based perspective to AGI research, highlighting new interdisciplinary research directions.

Findings

Identifies the need for a conceptual leap in AGI development.

Proposes a systems engineering framework for AGI.

Suggests cross-fertilization opportunities between systems disciplines and AI.

Abstract

Artificial General Intelligence (AGI) or Strong AI aims to create machines with human-like or human-level intelligence, which is still a very ambitious goal when compared to the existing computing and AI systems. After many hype cycles and lessons from AI history, it is clear that a big conceptual leap is needed for crossing the starting line to kick-start mainstream AGI research. This position paper aims to make a small conceptual contribution toward reaching that starting line. After a broad analysis of the AGI problem from different perspectives, a system-theoretic and engineering-based research approach is introduced, which builds upon the existing mainstream AI and systems foundations. Several promising cross-fertilization opportunities between systems disciplines and AI research are identified. Specific potential research directions are discussed.