Hacia un nuevo esquema de incentivos en el contexto de la inteligencia artificial
Resumen
Este escrito examina la intersección entre la inteligencia artificial (IA) y las teorías de motivación humana, con un enfoque en las implicaciones para el futuro del trabajo y los sistemas de incentivos económicos. Analizamos cómo la rápida evolución de la IA desafía las teorías económicas tradicionales sobre la motivación, las cuales se basan principalmente en incentivos extrínsecos. A través de una revisión de la literatura y del análisis de estudios empíricos, mostramos la importancia creciente de la motivación intrínseca en un entorno laboral cada vez más automatizado. Al respecto, exploramos el efecto crowding out, donde los incentivos extrínsecos pueden disminuir la motivación intrínseca, y sus implicaciones para el diseño de sistemas de incentivos. Particularmente, presentamos dos escenarios potenciales: una simbiosis entre el trabajo humano y la IA, y una transformación radical que podría hacer que el trabajo humano sea opcional en muchos sectores. Concluimos que es necesario reevaluar y adaptar los modelos económicos y sistemas de incentivos para reflejar una comprensión más matizada de la motivación humana en el contexto de la IA. Este estudio subraya la importancia de un enfoque interdisciplinario para la transición hacia un futuro donde la relación entre los humanos, el trabajo y la tecnología deberá ser redefinida.
Citas
Achor, S., Reece, A., Kellerman, G. R., & Robichaux, A. (2018). 9 out of 10 people are willing to earn less money to do more-meaningful work. Harvard Business Review, 96(6), 82-89. https://hbr.org/2018/11/9-out-of-10-people-are-willing-to-earn-less-money-to-do-more-meaningful-work
Acemoglu, D., & Johnson, S. (2024). Learning from Ricardo and Thompson: Machinery and labor in the early industrial revolution, and in the age of AI. National Bureau of Economic Research. https://www.nber.org/papers/w32416
Agrawal, K. (2010). To study the phenomenon of the Moravec's paradox. https://doi.org/10.48550/arXiv.1012.3148
Altman, S. (2021). Moore’s law for everything. http://tcw.org/lefty/Short%20Stories/Moore's%20Law%20for%20Everything.pdf
Ariely, D., Bracha, A., & Meier, S. (2009). Doing good or doing well? Image motivation and monetary incentives in behaving prosocially. American economic review, 99(1), 544-555. https://doi.org/10.1257/aer.99.1.544
Ariely, D., Gneezy, U., Loewenstein, G., & Mazar, N. (2009). Large stakes and big mistakes. The Review of Economic Studies, 76(2), 451-469.
Bardsley, N., Cubitt, R., Loomes, G., Moffatt, P., Starmer, C., & Sugden, R. (2010). Incentives in Experiments. In Experimental Economics: Rethinking the Rules (pp. 244–285). Princeton University Press. http://www.jstor.org/stable/j.ctt7sgpt.9
Bellemare-Pepin, A., Lespinasse, F., Thölke, P., Harel, Y., Mathewson, K., Olson, J. A., Bengio, Y., & Jerbi, K. (2024). Divergent Creativity in Humans and Large Language Models. https://doi.org/10.48550/arXiv.2405.13012
Boussioux, L., Lane, J. N., Zhang, M., Jacimovic, V., & Lakhani, K. R. (2024). Generative AI and Creative Problem Solving. Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 24-005. http://dx.doi.org/10.2139/ssrn.4533642
Bruni, L., & Sugden, R. (2007). The road not taken: How psychology was removed from economics, and how it might be brought back. The Economic Journal, 117(516), 146-173. https://doi.org/10.1111/j.1468-0297.2007.02005.x
Cerón Uribe, J. F. (2023). Entrevista a Juan Felipe Cerón Uribe, desarrollador de ChatGPT en Open AI, por Fabrizio López de Pomar. Futuro Hoy, 4(1), 11-16. https://futurohoy.ssh.org.pe/
Charles-Leija, H., Aboites, G., y Llamas, I. (2018). Una revisión de aportaciones que contribuyeron al estudio de la utilidad y la felicidad en la economía. Análisis económico, 33(84), 57-76. https://www.scielo.org.mx/scielo.php?script=sci_arttext&pid=S2448-66552018000300057
Clark, J. M. (1918). Economics and modern psychology: I. Journal of Political Economy, 26(1), 1-30. https://www.journals.uchicago.edu/doi/10.1086/253060
Cervellati, E. M. (2018). Behavioral Re-Evolution: How Behavioral Economics has Evolved and is Evolving. In The Behavioural Finance Revolution: A New Approach to Financial Policies and Regulations. Edward Elgar Publishing Limited, Cheltenham (UK).
Coll, A. J. y Maceri, S. B. (2023). Las consecuencias indeseadas del dinero desde el punto de vista de la psicología y la Economía de la Felicidad. Cultura Económica, 41(105), 67-84. https://doi.org/10.46553/cecon.41.105.2023.p67-84Deci, E. L. (1971). Effects of externally mediated rewards on intrinsic motivation. Journal of personality and Social Psychology, 18(1), 105-115 http://dx.doi.org/10.1037/h0030644
Deci, E. L., & Ryan, R. M. (1985). The general causality orientations scale: Self-determination in personality. Journal of research in personality, 19(2), 109-134. https://doi.org/10.1016/0092-6566(85)90023-6
Deci, E. L., Koestner, R., & Ryan, R. M. (1999). A meta-analytic review of experiments examining the effects of extrinsic rewards on intrinsic motivation. Psychological Bulletin, 125(6), 627-668. https://doi.org/10.1037/0033-2909.125.6.627
Easterlin, R. A. (2021). An Economist’s Lessons on Happiness: Farewell Dismal Science! Springer Nature.
Epstein, D. (2021). Range: Why generalists triumph in a specialized world. Penguin.
Fitri, D., Ratnasari, S. L., Suyanto, & Sultan, Z. (2023). Enhancing employee productivity through technology system AI-based approaches. The 6th International Seminar on Business, Economics, Social Science, and Technology (ISBEST) 2023, 3, 77-82.
Frey, B. S., & Jegen, R. (2001). Motivation crowding theory. Journal of economic surveys, 15(5), 589-611. https://doi.org/10.1111/1467-6419.00150
Friedman, M. (1953). The methodology of positive economics. University of Chicago Press.
Girotra, K., Meincke, L., Terwiesch, C., & Ulrich, K. T. (2023). Ideas are dimes a dozen: Large language models for idea generation in innovation. https://dx.doi.org/10.2139/ssrn.4526071
Gneezy, U., & Rustichini, A. (2000a). Pay Enough or Don't Pay at All. Quarterly Journal of Economics, 115, 791-810. https://doi.org/10.1162/003355300554917
----. (2000b). A fine is a price. The journal of legal studies, 29(1), 1-17. https://www.journals.uchicago.edu/doi/10.1086/468061
Gull, A., Ashfaq, J., & Aslam, M. (2023). AI in the Workplace: Uncovering Its Impact on Employee Well-being and the Role of Cognitive Job Insecurity. International Journal of Business & Economic Affairs (IJBEA), 8(4). https://doi.org/10.24088/IJBEA-2023-84007
Harlow, H. F. (1950). Learning and satiation of response in intrinsically motivated complex puzzle performance by monkeys. Journal of comparative and physiological psychology, 43(4), 289. https://psycnet.apa.org/doi/10.1037/h0058114
Harris-McLeod, E. (2013). Incentives for public service workers and the implications of crowding out theory. Public Policy and Governance Review, 4(2), 5-21. https://ppgreview.ca/wp-content/uploads/2013/04/ppgr-volume-4-issue-2-2-emily-harris-mcleod.pdf
Ho, A., Besiroglu, T., Erdil, E., Owen, D., Rahman, R., Guo, Z. C., Atkinson, D., Thompson, N., & Sevilla, J. (2024). Algorithmic progress in language models. https://doi.org/10.48550/arXiv.2403.05812
Isaacson, W. (2023). Elon Musk. Penguin.
Jarrahi, M. H. (2018). Artificial intelligence and the future of work: Human-AI symbiosis in organizational decision making. Business Horizons, 61(4), 577-586. https://doi.org/10.1016/j.bushor.2018.03.007
Kamenica, E. (2012). Behavioral economics and psychology of incentives. ANNUAL REVIEW OF Economics, 4(1), 427-452. https://doi.org/10.1146/annurev-economics-080511-110909
Kohn, A. (1993). Punished by rewards: The trouble with gold stars, incentive plans, A's, praise, and other bribes. Houghton Mifflin Company.
Kurzweil, R. (2005). The singularity is near. In Ethics and emerging technologies (pp. 393-406). Palgrave Macmillan UK.
Latif, E., Mai, G., Nyaaba, M., Wu, X., Liu, N., Lu, G., ... & Zhai, X. (2023). Artificial general intelligence (AGI) for education. arXiv preprint arXiv:2304.12479.
Lepper, M. R., & Greene, D. (1978). The hidden costs of reward: New perspectives on the psychology of human motivation. Hillsdale, NJ: Lawrence Erlbaum Associates.
Lepper, M. R., Greene, D., & Nisbett, R. E. (1973). Undermining children's intrinsic interest with extrinsic reward: A test of the "overjustification" hypothesis. Journal of Personality and Social Psychology, 28(1), 129. https://doi.org/10.1037/h0035519
List, J. A., Livingston, J. A., & Neckermann, S. (2018). Do financial incentives crowd out intrinsic motivation to perform on standardized tests? Economics of Education Review, 66, 125-136. https://doi.org/10.1016/j.econedurev.2018.08.002
Loureiro, S. M. C., Bilro, R. G., & Neto, D. (2023). Working with AI: can stress bring happiness? Service Business, 17(1), 233-255. https://doi.org/10.1007/s11628-022-00514-8
Mollick, E. (2024). Co-Intelligence: Living and Working with AI. Penguin Publishing Group.
Moore, G. E. (1998). Cramming more components onto integrated circuits. Proceedings of the IEEE, 86(1), 82-85. https://doi.org/10.1109/JPROC.1998.658762
Pink, D. H. (2011). Drive: The surprising truth about what motivates us. Penguin.
Ryan R. (2009). Self-Determination Theory and Wellbeing. Social Psychology, 84, 822-848.
Ryan, R. M., Bradshaw, E., Deci, E. L., Sternberg, R., & Pickren, W. (2019). A history of human motivation theories. The Cambridge handbook of the intellectual history of psychology, 391-411.
Ryan, R. M., Deci, E. L. (2000). Self-determination theory and the facilitation of intrinsic motivation, social development, and well being. American Psychologist, 55, 68-78.
Stigler, G. J., & Becker, G. S. (1977). De gustibus non est disputandum. The American economic review, 67(2), 76-90.
Titmuss, R. M. (1970). The gift relationship (vol. 220). Allen & Unwin.
Visaria, S., Dehejia, R., Chao, M. M., & Mukhopadhyay, A. (2016). Unintended consequences of rewards for student attendance: Results from a field experiment in Indian classrooms. Economics of Education Review, 54, 173-184. https://doi.org/10.1016/j.econedurev.2016.08.001
Wu, J., & Lu, X. (2013). Effects of Extrinsic and Intrinsic Motivators on Using Utilitarian, Hedonic, and Dual-Purposed Information Systems: A Meta-Analysis. Journal of the Association for Information Systems, 14(3). https://aisel.aisnet.org/jais/vol14/iss3/1
Zarifhonarvar, A. (2023). Economics of ChatGPT: A Labor Market View on the Occupational Impact of Artificial Intelligence. ZBW - Leibniz Information Centre for Economics, Kiel, Hamburg. https://hdl.handle.net/10419/268826
Zhang, C., Zhang, C., Li, C., Qiao, Y., Zheng, S., Dam, S. K., & Hong, C. S. (2023). One small step for generative ai, one giant leap for agi: A complete survey on chatgpt in aigc era. arXiv preprint arXiv:2304.06488. https://doi.org/10.48550/arXiv.2304.06488