The case for psychometric artificial general intelligence
Mark McPherson
TL;DR
This paper reviews existing methods for measuring artificial general intelligence, critically evaluates proposed benchmarks, and suggests promising directions for future research to improve detection and assessment of AGI.
Contribution
It provides a critical evaluation of current AGI benchmarks and proposes new promising approaches and future research directions.
Findings
Identified limitations in current AGI measurement benchmarks
Highlighted promising approaches for AGI detection
Suggested useful directions for future AGI research
Abstract
A short review of the literature on measurement and detection of artificial general intelligence is made. Proposed benchmarks and tests for artificial general intelligence are critically evaluated against multiple criteria. Based on the findings, the most promising approaches are identified and some useful directions for future work are proposed.
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Taxonomy
TopicsComputability, Logic, AI Algorithms · Cognitive Science and Mapping · Reinforcement Learning in Robotics