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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
  • Ansari, S. (2026). Compound deception in elite peer review: A failure mode taxonomy of 100 fabricated citations at NeurIPS 2025. arXiv:2602.05930. Enlace
  • 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
  • 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
  • Korinek, A. (2025). AI agents for economic research. NBER Working Paper 34202. Enlace
  • 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
  • Lu, C. et al. (2026). Towards end-to-end automation of AI research. Nature, 651, 914-919. Enlace
  • OpenAI (2026). On the Navier-Stokes Millennium Prize Problem. Enlace
  • Pew Research Center (2026). Can AI stand in for human survey-takers? Not really. Enlace
  • 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.
  • Zhang, L. T. y Zhu, Z. (2026). Diagnosing silent errors in replication packages: Evidence from an AI agent. Economics Letters. Enlace

Notas periodísticas

  • Quanta Magazine (2026). AI has solved one of math's $1 million Millennium Prize problems. Enlace
  • Fortune (2026). NeurIPS accepted research papers with 100+ AI-hallucinated citations. Enlace
  • Axios (2025). AI "workslop" sabotages productivity, study finds. Enlace
  • TechCrunch (2025). MIT disavows doctoral student paper on AI's productivity benefits. Enlace

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.

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.