Researchers urge AI field to drop AGI as its north-star goal
TL;DR
- A 16-author position paper argues that treating AGI as AI research's north star undermines the field's ability to choose effective goals.
- The paper names six specific traps it says AGI discourse aggravates, including Illusion of Consensus, Supercharging Bad Science, and Generality Debt.
- The authors' prescription: prioritize specificity, center pluralism across multiple worthwhile approaches, and widen disciplinary inclusion.
Sixteen researchers have put their names to a position paper arguing that the AI field should stop treating artificial general intelligence as its guiding goal.
The paper on arxiv, signed by a group that includes Margaret Mitchell and Shiri Dori-Hacohen, catalogs six 'traps' the authors say AGI discourse aggravates: Illusion of Consensus, Supercharging Bad Science, Presuming Value-Neutrality, Goal Lottery, Generality Debt, and Normalized Exclusion.
"Focusing on the highly contested topic of 'artificial general intelligence' ('AGI') undermines our ability to choose effective goals," the abstract reads.
Their prescription runs three lines: "prioritize specificity in engineering and societal goals," "center pluralism about multiple worthwhile approaches to multiple valuable goals," and "foster innovation through greater inclusion of disciplines and communities." The abstract's closing sentence states the demand plainly: "the AI research community needs to stop treating 'AGI' as the north-star goal of AI research."
The abstract names the six traps but leaves their definitions to the body of the paper.
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Originally reported by arxiv.org
Read the original article →Original headline: Stop treating `AGI' as the north-star goal of AI research