Research map / Large language models / AI and society
Position: Stop treating `AGI' as the north-star goal of AI research
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A position paper arguing that the AI research community should stop treating AGI as its north-star goal, identifying six goal-setting traps and recommending specificity, pluralism, and inclusion.
Problem
AGI discourse is contested and vague, which undermines the field's ability to set scientifically, engineering-wise, and societally justified research goals.
Approach
Identifies six traps (Illusion of Consensus, Supercharging Bad Science, Presuming Value-Neutrality, Goal Lottery, Generality Debt, Normalized Exclusion) aggravated by AGI discourse and recommends goal specificity, pluralism of goals and approaches, and greater inclusion in goal setting, rather than a single AGI north star.
Key results
- Identifies six traps (Illusion of Consensus, Supercharging Bad Science, Presuming Value-Neutrality, Goal Lottery, Generality Debt, Normalized Exclusion) that AGI discourse aggravates.
- Proposes three recommendations: goal specificity, pluralism of goals and approaches, and greater inclusion in goal setting.
- Rebuts the alternative view that improved AGI definitions could serve as north-star goal, offering supporting human beings as an alternative overarching goal.
Limitations
- Argument is conceptual and not empirically tested
- Authors explicitly avoid providing their own definition of AGI
- Reasons against AGI are pro-tanto rather than definitive
Experimental setup
Baselines: AGI as north-star goal (alternative view)
Builds on: essentially contested concepts (fairness, privacy) technical debt hardware lottery
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