AGI Performance Measure

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An AGI Performance Measure is a AI performance measure for AGIs.

  • Context:
    • It can (typically) assess the generality and performance of AGI systems across a wide range of tasks and conditions.
    • It can (often) evaluate an AGI's ability to perform cognitive and meta-cognitive tasks, including learning new skills and adapting to new environments.
    • It can measure the autonomy of AGI systems, distinguishing between various levels such as AI as a tool, consultant, collaborator, expert, and agent.
    • It can focus on real-world tasks that humans value, ensuring ecological validity in performance metrics.
    • It can involve benchmarks like the "Coffee Test," which tests an AGI's flexibility and reliability by requiring it to operate competently in an arbitrary kitchen.
    • It can combine performance and generality to provide a comprehensive framework for AGI evaluation, distinguishing between narrow AI and true AGI.
    • It can use frameworks like DeepMind's Levels of AGI, which introduce five levels of AGI performance, ranging from No AI to Superhuman, based on percentile performance compared to skilled adults.
    • It can incorporate concepts like Suleyman’s Artificial Capable Intelligence (ACI), which involves economic and strategic benchmarks such as turning capital into profit.
    • It can range from being simple task-specific tests to complex, multi-dimensional evaluations involving cognitive, physical, and strategic tasks.
    • ...
  • Example(s):
  • Counter-Example(s):
    • Narrow AI Benchmarks, which focus on evaluating AI systems specialized in specific tasks rather than general intelligence.
    • Traditional AI Metrics, which may not adequately capture the breadth and depth required for AGI assessment.
    • ...
  • See: AGI Level.


References

2023

2023

2023