A1 Refereed original research article in a scientific journal
AI-assisted teams outperform AI-led teams but not human-only teams in assessing research reproducibility in quantitative social science
Authors: Brodeur, Abel; Valenta, David; Marcoci, Alexandru; Aparicio, Juan P.; Mikola, Derek; Barbarioli, Bruno; Alexander, Rohan; Deer, Lachlan; Stafford, Tom; Vilhuber, Lars; Bensch, Gunther; Motoki, Fabio; Abdelhady, Mohamed; Abdelmoula, Yousra; Baki, Ghina Abdul; Aguirre, Tomás; Aiyer, Sriraj; Akhtar, Shumi; Akhtar, Farida; Albada, Melle R.; Altman, Micah; Angenendt, David; Arjmandi Lari, Zahra; De León Tejada, Jorge Armando; Arana, David Rodriguez; Asanov, Igor; Noha, Anastasiya-Mariya; Ashong, Rebecca; Auer, Tobias; Bahamonde-Birke, Francisco J.; Baker, Bradley J.; Bartram, Söhnke M.; Bao, Dongqi; Batinovic, Lucija; Batistoni, Tommaso; Beeder, Monica; Beland, Louis-Philippe; Gero Bienz, Carsten; Aryanto, Christ Billy; Bolibaugh, Cylcia; Bonander, Carl; Bravo, Ramiro; Bronnikov, Egor; Bruns, Stephan; Buliskeria, Nino; Caicedo-Silva, Sara; Calef, Andrea; Sebastian Cano Arias, Juan; A. Castillo Alvarez, Gustavo; Caulker, Solomon; Cepenas, Simonas; Chatton, Arthur; Chen, Zirou; Chioma Ewurum, Ngozi; Ciocîrlan, Anda-Bianca; Clouth, Felix J.; Collins, Jason; Cook, Nikolai; Cornejo, Cesar; Craveiro, João; Créchet, Jonathan; Cui, Jing; Chalil Vayalabron, Niveditha; Czymara, Christian; Bermúdez Jaramillo, Carlos Daniel; Datta, Hannes; Denoo, Lien; Dhaliwal, Arshia; Dhameja, Nency; Djemai, Elodie; Dujeancourt, Erwan; Dündar, Uǧurcan; Duprey, Thibaut; Eissa, Yasmine; El Fassi, Youssef; El Fassi, Ismail; Ellis, Keaton; Elminejad, Ali; Elsherif, Mahmoud; Emirmahmutoglu, Aysil; Etingin-Frati, Giulian; Eze, Emeka; Dollbaum, Jan Fabian; Feld, Jan; Felipe Rengifo Jaramillo, Andres; Fenig, Guidon; Fernandes, Victoria; Fiala, Lenka; Fink, Lukas; Firouzjaeiangalougah, Mojtaba; Fish, Sara; Fitzgerald, Jack; Forshaw, Rachel; Fortier-Chouinard, Alexandre; Fréget, Louis; Frese, Joris; Gabani, Jacopo; Gallegos, Sebastian; Gamill, Max C.; Gáspár, Attila; Gauriot, Romain; Gavrilova, Evelina; Geraldes, Diogo; Cantone, Giulio Giacomo; Gibson, Grant; Goldschmitt, Dirk; Gourdon-Kanhukamwe, Amélie; Gregor de Varda, Andrea; Grigoryeva, Idaliya; Gugushvili, Alexi; Fletcher, Aaron H. A.; Habermann, Florian; Hablicsek, Márton; Haddad, Joanne; Hall, Jonathan D.; Hammar, Olle; Hassouneh, Malek; Hausladen, Carina I.; Hendrikse, Sophie C. F.; Hepplewhite, Matthew; Ho, Anson T. Y.; Hogan-Hennessy, Senan; Howley, Elliot; Huang, Gaoyang; Hulstaert, Héloïse; Ilchovska, Zlatomira G.; Jaimes Santamaria, Paola; Jakobsson, Niklas; Jansson, Joakim; Jarosz, Ewa; Jebeli, Hossein; Jiang, Yanchen; Junaid, Hiba; Kalluraya, Rohan; Karim, Sunny; Kelly, Edmund; Kimel, Eva; Kingsuwankul, Sorravich; Klotzbücher, Valentin; Krähmer, Daniel; Krūminas, Pijus; Kruus, Nicholas; Kujansuu, Essi; Kurz, Christoph F.; Küster, Stephan; Lee-Whiting, Blake; Lewandowski, Felix; Li, Tongzhe; Li, Ruoxi; Liu, Dan; Liu, Jiacheng; Lo, Helix; Loter, Katharina; Macedo Dias, Felipe; Madan, Christopher R.; Mäder, Nicolas; Mandas, Marco; Mantilla, Cesar; Marcus, Jan; Marino Fages, Diego; Martin, Xavier; McWay, Ryan; Medina-Gaspar, Daniel; Meng, Sisi; Meng, Lingyu; Merz, Simon; Miller, Alex P.; Mirabel, Thibault; Mishra, Dibya Deepta; Mishra, Sumit; Moges, Belay W.; Mohandes Mojarrad, Morteza; Mohnen, Myra; Morin, Louis-Philippe; Muehlenbachs, Lucija; Mullin, Gastón; Musulan, Andreea; Muzzì, Sara; Myers, James A. C.; Neubauer, Florian; Nguyen, Tuan; Niazi, Ali; Nordstrom, Ardyn; Nowak, Bartłomiej; O’Habib, Daneal; Ölkers, Tim; Ong, Justin; Orozco Castiblanco, Valeria; Özak, Ömer; Ozkes, Ali I.; Paaso, Mikael; Pandey, Shubham; Papazoglou, Varvara; Penheiro, Romeo; Pham, Linh; Phieler, Ulrike; Pütz, Peter; Qi, Quan; Qiu, Jingyi; Rein, Manuel T.; Reinstein, David A.; Repo, Juuso; Rudolf, Nicolas; Saha, Shree; Saka, Orkun; Saponaro, Chiara; Sator, Georg; Schoenmakers, Martijn; Seri, Raffaello; Shah, Meet; Sibille, Paul; Siemroth, Christoph; Skavysh, Vladimir; Slater, Ben; Song, Wenting; Staubli, Stefan; Steindl, Tobias; Waongo, Nomwendé Steven; Stott, Paul; Strobel, Stephenson; Sudhaharan, Roshini; Sun, Pu; Swain, Scott D.; Talavera, Oleksandr; Tantiangco, Hanz M.; Tarasenko, Georgy; Tarlinton, Boyd; Tarraf, Mariam; Teoh, Ken; Thériault, Rémi; Thompson, Bethan; Tian, Tonghui; Tian, Wenjie; Tolani, Emmanuel; Borgen, Nicolai; Topstad Borgen, Solveig; Torralba, Javier; Velez-Ospina, Carolina; Mak, Man Wai; Wallrich, Lukas; Wang, Zeyang; Ward, Leah; Webb, Matthew D.; Webb, Duncan; Weber, Bryan S.; Weber, Christoph; Weng, Wei-Chien; Westheide, Christian; Wilkinson, Tom; Wong, Kwong-Yu; Wroński, Marcin; Wu, Zhuangchen; Wu, Qixia; Wu, Victor Y.; Xiao, Bohan; Xu, Feihong; Xu, Cong; Yadav, Pranav; Yang, Chou Yu; Yap, Luther; Yazbeck, Myra; Yao, Bo; Zagrodzka, Zuzanna; Zahra, Tahreen; Zaneva, Mirela; Zhang, Xiaomeng; Zhao, Ziwei; Zhong, Han; Zirgulis, Aras; Zou, Jiacheng; Zoutman, Floris; Zozoungbo, Christelle
Publisher: National Academy of Sciences
Publication year: 2026
Journal: Proceedings of the National Academy of Sciences of the United States of America
Article number: e2524747123
Volume: 123
Issue: 22
ISSN: 0027-8424
eISSN: 1091-6490
DOI: https://doi.org/10.1073/pnas.2524747123
Publication's open availability at the time of reporting: No Open Access
Publication channel's open availability : Partially Open Access publication channel
Web address : https://doi.org/10.1073/pnas.2524747123
Additional information: Correction to this article: https://doi.org/10.1073/pnas.2621051123 ; DOI:10.1073/pnas.2621051123
Large Language Models (LLMs) such as ChatGPT are transforming how scientists conduct and validate research, offering promise as tools to improve scientific reproducibility. However, computational reproducibility and error detection remain expensive and labor-intensive. We experimentally test how collaboration between researchers and LLM assistants influences the reproduction of quantitative social science findings across different levels of AI autonomy. We randomly assigned 288 researchers to 103 teams working under three conditions: human-only, AI-assisted (using ChatGPT as a collaborative tool), or AI-led (ChatGPT operating with minimal human oversight). Teams reproduced published results from leading social science journals, detected coding errors, and proposed robustness checks. Human-only and AI-assisted teams achieved comparable reproduction rates (94% vs. 91%) and performed similarly on most outcomes, except human-only teams identified significantly more major coding errors. Both substantially outperformed AI-led teams, which achieved only a 37% reproduction rate, detected fewer errors across all categories, proposed weaker robustness checks, and required more time. This autonomous approach, however, likely represents only a lower bound of AI capabilities. Despite rapid model advances, expert human judgment currently remains indispensable for reliable empirical verification. While AI assistance did not degrade most outcomes, it provided no measurable advantages and was associated with reduced detection of major errors. However, the 37% autonomous reproduction rate indicates that AI could provide value in settings where scale or cost constraints preclude human review of papers, even though general-purpose LLMs offer no immediate advantages for human-supervised verification.
Funding information in the publication:
This research and AI replication games were funded by Coefficient Giving project “Benchmarking LLM agents on real-world tasks: Reproducibility” and the Alfred P. Sloan Foundation Foundation grant G-2023-22326. We also benefited from funding to host games from the Universities of Toronto, Ottawa, Cornell, and Tilburg. Mahmoud Elsherif acknowledges funding from Leverhulme Early Career Research Fellowship-ECF-2022-761. S. Akhtar acknowledges funding DP200102935 awarded by the Australian Research Council Grant. R. Seri acknowledges funding from project “Dipartimento di Eccellenza 2023-2027” awarded by the Ministero dell’Università e della Ricerca.
