Stop treating `AGI' as the north-star goal of AI research

Fuente: arXiv
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Auteurs principaux: Blili-Hamelin, Borhane, Graziul, Christopher, Hancox-Li, Leif, Hazan, Hananel, El-Mhamdi, El-Mahdi, Ghosh, Avijit, Heller, Katherine, Metcalf, Jacob, Murai, Fabricio, Salvaggio, Eryk, Smart, Andrew, Snider, Todd, Tighanimine, Mariame, Ringer, Talia, Mitchell, Margaret, Dori-Hacohen, Shiri
Format: Preprint
Publié: 2025
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author Blili-Hamelin, Borhane
Graziul, Christopher
Hancox-Li, Leif
Hazan, Hananel
El-Mhamdi, El-Mahdi
Ghosh, Avijit
Heller, Katherine
Metcalf, Jacob
Murai, Fabricio
Salvaggio, Eryk
Smart, Andrew
Snider, Todd
Tighanimine, Mariame
Ringer, Talia
Mitchell, Margaret
Dori-Hacohen, Shiri
author_facet Blili-Hamelin, Borhane
Graziul, Christopher
Hancox-Li, Leif
Hazan, Hananel
El-Mhamdi, El-Mahdi
Ghosh, Avijit
Heller, Katherine
Metcalf, Jacob
Murai, Fabricio
Salvaggio, Eryk
Smart, Andrew
Snider, Todd
Tighanimine, Mariame
Ringer, Talia
Mitchell, Margaret
Dori-Hacohen, Shiri
contents The AI research community plays a vital role in shaping the scientific, engineering, and societal goals of AI research. In this position paper, we argue that focusing on the highly contested topic of `artificial general intelligence' (`AGI') undermines our ability to choose effective goals. We identify six key traps -- obstacles to productive goal setting -- that are aggravated by AGI discourse: Illusion of Consensus, Supercharging Bad Science, Presuming Value-Neutrality, Goal Lottery, Generality Debt, and Normalized Exclusion. To avoid these traps, we argue that the AI research community needs to (1) prioritize specificity in engineering and societal goals, (2) center pluralism about multiple worthwhile approaches to multiple valuable goals, and (3) foster innovation through greater inclusion of disciplines and communities. Therefore, the AI research community needs to stop treating `AGI' as the north-star goal of AI research.
format Preprint
id arxiv_https___arxiv_org_abs_2502_03689
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Stop treating `AGI' as the north-star goal of AI research
Blili-Hamelin, Borhane
Graziul, Christopher
Hancox-Li, Leif
Hazan, Hananel
El-Mhamdi, El-Mahdi
Ghosh, Avijit
Heller, Katherine
Metcalf, Jacob
Murai, Fabricio
Salvaggio, Eryk
Smart, Andrew
Snider, Todd
Tighanimine, Mariame
Ringer, Talia
Mitchell, Margaret
Dori-Hacohen, Shiri
Computers and Society
The AI research community plays a vital role in shaping the scientific, engineering, and societal goals of AI research. In this position paper, we argue that focusing on the highly contested topic of `artificial general intelligence' (`AGI') undermines our ability to choose effective goals. We identify six key traps -- obstacles to productive goal setting -- that are aggravated by AGI discourse: Illusion of Consensus, Supercharging Bad Science, Presuming Value-Neutrality, Goal Lottery, Generality Debt, and Normalized Exclusion. To avoid these traps, we argue that the AI research community needs to (1) prioritize specificity in engineering and societal goals, (2) center pluralism about multiple worthwhile approaches to multiple valuable goals, and (3) foster innovation through greater inclusion of disciplines and communities. Therefore, the AI research community needs to stop treating `AGI' as the north-star goal of AI research.
title Stop treating `AGI' as the north-star goal of AI research
topic Computers and Society
url https://arxiv.org/abs/2502.03689