# Referencias

**Sobre IA en la investigación (2023-2026)**

- Alizadeh, M. et al. (2026). AI coding agents can reproduce social science findings. *arXiv:2606.11447*. [Enlace](https://arxiv.org/html/2606.11447)
- Ansari, S. (2026). Compound deception in elite peer review: A failure mode taxonomy of 100 fabricated citations at NeurIPS 2025. *arXiv:2602.05930*. [Enlace](https://arxiv.org/abs/2602.05930)
- Atari, M., Xue, M. J., Park, P. S., Blasi, D. E. y Henrich, J. (2023). Which humans? *PsyArXiv*.
- Bastani, H. et al. (2025). Generative AI without guardrails can harm learning. *PNAS*.
- Batista, R. y Griffiths, T. (2026). Documento de trabajo sobre complacencia y descubrimiento de reglas (Princeton, sin revisión por pares).
- Budzyń, K. et al. (2025). Endoscopist deskilling risk after exposure to artificial intelligence in colonoscopy: A multicentre, observational study. *The Lancet Gastroenterology & Hepatology*.
- Cheng, M. et al. (2026). Sobre la complacencia de los modelos de lenguaje. *Science*.
- Hewitt, L., Ashokkumar, A., Ghezae, I. y Willer, R. Large language models can predict results of social science experiments. *Nature*. [Enlace](https://www.gsb.stanford.edu/faculty-research/publications/large-language-models-can-predict-results-social-science-experiments)
- Kohler, B., Zollikofer, D., Einsiedler, J., Hoyle, A. y Ash, E. (2026). Read the paper, write the code: Agentic reproduction of social-science results. *arXiv:2604.21965*. [Enlace](https://arxiv.org/html/2604.21965v2)
- Korinek, A. (2025). AI agents for economic research. *NBER Working Paper 34202*. [Enlace](https://www.nber.org/papers/w34202)
- Kosmyna, N. et al. (2025). Your brain on ChatGPT: Accumulation of cognitive debt when using an AI assistant for essay writing task. *arXiv:2506.08872*.
- Lehmann, M., Cornelius, P. B. y Sting, F. J. (2024). AI meets the classroom: When do large language models harm learning? *arXiv:2409.09047*.
- Leiden Declaration on Artificial Intelligence and Mathematics (2026). [Enlace](https://www.leidendeclaration.ai/)
- Lu, C. et al. (2026). Towards end-to-end automation of AI research. *Nature*, 651, 914-919. [Enlace](https://ora.ox.ac.uk/objects/uuid:92d16200-fbe1-4564-b4d4-694e96223b39)
- OpenAI (2026). On the Navier-Stokes Millennium Prize Problem. [Enlace](https://openai.com/index/navier-stokes-solution/)
- Pew Research Center (2026). Can AI stand in for human survey-takers? Not really. [Enlace](https://www.pewresearch.org/data-labs/2026/09/30/methodology-silicon-samples/)
- Sharma, M. et al. (2024). Towards understanding sycophancy in language models. *International Conference on Learning Representations (ICLR)*.
- Shen, J. H. y Tamkin, A. (2026). How AI assistance impacts the formation of coding skills. Anthropic.
- Tao, T. (2026). Ensayo para el Congreso Internacional de Matemáticos. Reseña en [The Decoder](https://the-decoder.com/terence-tao-says-ai-could-trigger-maths-biggest-crisis-since-godel/).
- Zhang, L. T. y Zhu, Z. (2026). Diagnosing silent errors in replication packages: Evidence from an AI agent. *Economics Letters*. [Enlace](https://www.sciencedirect.com/science/article/abs/pii/S0165176526004623)

**Notas periodísticas**

- Quanta Magazine (2026). AI has solved one of math's $1 million Millennium Prize problems. [Enlace](https://www.quantamagazine.org/ai-has-solved-one-of-maths-1-million-millennium-prize-problems-20260908/)
- Fortune (2026). NeurIPS accepted research papers with 100+ AI-hallucinated citations. [Enlace](https://fortune.com/2026/01/21/neurips-ai-conferences-research-papers-hallucinations/)
- Axios (2025). AI "workslop" sabotages productivity, study finds. [Enlace](https://www.axios.com/2025/09/24/ai-workslop-workplace-efficiency-study)
- TechCrunch (2025). MIT disavows doctoral student paper on AI's productivity benefits. [Enlace](https://techcrunch.com/2025/05/17/mit-disavows-doctoral-students-paper-on-ai-productivity-benefits)

**De los flujos de trabajo**

- Buehler, R., Griffin, D. y Ross, M. (1994). Exploring the "planning fallacy": Why people underestimate their task completion times. *Journal of Personality and Social Psychology*, 67(3), 366-381.
- Camerer, C., Loewenstein, G. y Weber, M. (1989). The curse of knowledge in economic settings: An experimental analysis. *Journal of Political Economy*, 97(5), 1232-1254.
- Chang, A. C. y Li, P. (2022). Is economics research replicable? Sixty published papers from thirteen journals say "often not". *Critical Finance Review*, 11(1), 185-206.
- Chen, P., Ellsworth, P. C. y Schwarz, N. (2015). Finding a fit or developing it: Implicit theories about achieving passion for work. *Personality and Social Psychology Bulletin*, 41(10), 1411-1424.
- Flower, L. y Hayes, J. R. (1981). A cognitive process theory of writing. *College Composition and Communication*, 32(4), 365-387.
- Herndon, T., Ash, M. y Pollin, R. (2014). Does high public debt consistently stifle economic growth? A critique of Reinhart and Rogoff. *Cambridge Journal of Economics*, 38(2), 257-279.
- Iyengar, S. S. y Lepper, M. R. (2000). When choice is demotivating: Can one desire too much of a good thing? *Journal of Personality and Social Psychology*, 79(6), 995-1006.
- Liang, W. et al. (2024). Can large language models provide useful feedback on research papers? A large-scale empirical analysis. *NEJM AI*, 1(8).
- O'Keefe, P. A., Dweck, C. S. y Walton, G. M. (2018). Implicit theories of interest: Finding your passion or developing it? *Psychological Science*, 29(10), 1653-1664.
- Peng, S., Kalliamvakou, E., Cihon, P. y Demirer, M. (2023). The impact of AI on developer productivity: Evidence from GitHub Copilot. *arXiv:2302.06590*.
- Risko, E. F. y Gilbert, S. J. (2016). Cognitive offloading. *Trends in Cognitive Sciences*, 20(9), 676-688.
- Rozenblit, L. y Keil, F. (2002). The misunderstood limits of folk science: An illusion of explanatory depth. *Cognitive Science*, 26(5), 521-562.
- Ruan, S., Wobbrock, J. O., Liou, K., Ng, A. y Landay, J. A. (2018). Comparing speech and keyboard text entry for short messages in two languages on touchscreen phones. *Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies*, 1(4), 159.
- Rugg, D. (1941). Experiments in wording questions: II. *Public Opinion Quarterly*, 5(1), 91-92.
- Sarasvathy, S. D. (2001). Causation and effectuation: Toward a theoretical shift from economic inevitability to entrepreneurial contingency. *Academy of Management Review*, 26(2), 243-263.
- Scheibehenne, B., Greifeneder, R. y Todd, P. M. (2010). Can there ever be too many options? A meta-analytic review of choice overload. *Journal of Consumer Research*, 37(3), 409-425.
- Simkin, M. V. y Roychowdhury, V. P. (2003). Read before you cite! *Complex Systems*, 14(3), 269-274.
- Tourangeau, R. y Yan, T. (2007). Sensitive questions in surveys. *Psychological Bulletin*, 133(5), 859-883.
- Walters, W. H. y Wilder, E. I. (2023). Fabrication and errors in the bibliographic citations generated by ChatGPT. *Scientific Reports*, 13, 14045.

**Otras referencias**

- Bloom, N. y Van Reenen, J. (2010). Why do management practices differ across firms and countries? *Journal of Economic Perspectives*, 24(1), 203-224.
- Franklin, S. W. (2023). *The cult of creativity: A surprisingly recent history*. University of Chicago Press.
- Li, X., Chan, S., Zhu, X., Pei, Y., Ma, Z., Liu, X. y Shah, S. (2023). Are ChatGPT and GPT-4 general-purpose solvers for financial text analytics? A study on several typical tasks. *Proceedings of EMNLP 2023: Industry Track*. arXiv:2305.05862.
- Mollick, E. (2020). *The unicorn's shadow*. Wharton School Press.
- Pashler, H., McDaniel, M., Rohrer, D. y Bjork, R. (2008). Learning styles: Concepts and evidence. *Psychological Science in the Public Interest*, 9(3), 105-119.

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*Nota de transparencia: la búsqueda de evidencia reciente, la organización y los borradores de varias secciones de esta guía se hicieron con apoyo de Claude (Anthropic); las ideas y la revisión final son del autor.*