Position: Stop treating ‘AGI’ as the north-star goal of AI research

Borhane Blili-Hamelin, Christopher Graziul, Leif Hancox-Li, Hananel Hazan, El-Mahdi El-Mhamdi, Avijit Ghosh, Katherine A Heller, Jacob Metcalf, Fabricio Murai, Eryk Salvaggio, Andrew J Smart, Todd Snider, Mariame Tighanimine, Talia Ringer, Margaret Mitchell, Shiri Dori-Hacohen
Proceedings of the 42nd International Conference on Machine Learning, PMLR 267:81090-81117, 2025.

Abstract

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 scientific, 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.

Cite this Paper

BibTeX
@InProceedings{pmlr-v267-blili-hamelin25a, title = {Position: Stop treating ‘{AGI}’ as the north-star goal of {AI} research}, author = {Blili-Hamelin, Borhane and Graziul, Christopher and Hancox-Li, Leif and Hazan, Hananel and El-Mhamdi, El-Mahdi and Ghosh, Avijit and Heller, Katherine A and Metcalf, Jacob and Murai, Fabricio and Salvaggio, Eryk and Smart, Andrew J and Snider, Todd and Tighanimine, Mariame and Ringer, Talia and Mitchell, Margaret and Dori-Hacohen, Shiri}, booktitle = {Proceedings of the 42nd International Conference on Machine Learning}, pages = {81090--81117}, year = {2025}, editor = {Singh, Aarti and Fazel, Maryam and Hsu, Daniel and Lacoste-Julien, Simon and Berkenkamp, Felix and Maharaj, Tegan and Wagstaff, Kiri and Zhu, Jerry}, volume = {267}, series = {Proceedings of Machine Learning Research}, month = {13--19 Jul}, publisher = {PMLR}, pdf = {https://raw.githubusercontent.com/mlresearch/v267/main/assets/blili-hamelin25a/blili-hamelin25a.pdf}, url = {https://proceedings.mlr.press/v267/blili-hamelin25a.html}, abstract = {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 scientific, 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.} }
Endnote
%0 Conference Paper %T Position: Stop treating ‘AGI’ as the north-star goal of AI research %A Borhane Blili-Hamelin %A Christopher Graziul %A Leif Hancox-Li %A Hananel Hazan %A El-Mahdi El-Mhamdi %A Avijit Ghosh %A Katherine A Heller %A Jacob Metcalf %A Fabricio Murai %A Eryk Salvaggio %A Andrew J Smart %A Todd Snider %A Mariame Tighanimine %A Talia Ringer %A Margaret Mitchell %A Shiri Dori-Hacohen %B Proceedings of the 42nd International Conference on Machine Learning %C Proceedings of Machine Learning Research %D 2025 %E Aarti Singh %E Maryam Fazel %E Daniel Hsu %E Simon Lacoste-Julien %E Felix Berkenkamp %E Tegan Maharaj %E Kiri Wagstaff %E Jerry Zhu %F pmlr-v267-blili-hamelin25a %I PMLR %P 81090--81117 %U https://proceedings.mlr.press/v267/blili-hamelin25a.html %V 267 %X 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 scientific, 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.
APA
Blili-Hamelin, B., Graziul, C., Hancox-Li, L., Hazan, H., El-Mhamdi, E., Ghosh, A., Heller, K.A., Metcalf, J., Murai, F., Salvaggio, E., Smart, A.J., Snider, T., Tighanimine, M., Ringer, T., Mitchell, M. & Dori-Hacohen, S.. (2025). Position: Stop treating ‘AGI’ as the north-star goal of AI research. Proceedings of the 42nd International Conference on Machine Learning, in Proceedings of Machine Learning Research 267:81090-81117 Available from https://proceedings.mlr.press/v267/blili-hamelin25a.html.

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