AI, Society and Environment: a Possible Complex System Framework
Resumo
The large-scale deployment of AI models introduces significant uncertainty regarding their systemic behaviour. While these models have the potential to boost productivity and advance fields such as health and climate science, they also pose risks, including the reinforcement of biases, the spread of misinformation, and support for autocratic regimes. This paper examines the interaction between social, environmental, and AI systems from the perspective of a complex system’s agent framework, using a resource-impact lens to explore these dynamics.
Palavras-chave:
Artificial Intelligence and Society, Complex Systems, Systemic Risks of AI
Referências
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Lam, R., Sanchez-Gonzalez, A., Willson, M., Wirnsberger, P., Fortunato, M., Alet, F., Ravuri, S., Ewalds, T., Eaton-Rosen, Z., Hu, W., et al. (2023). Learning skillful medium-range global weather forecasting. Science, page eadi2336.
Levin, S. A., Carpenter, S. R., Godfray, H. C. J., Kinzig, A. P., Loreau, M., Losos, J. B., Walker, B., and Wilcove, D. S. (2009). The Princeton guide to ecology. Princeton University Press.
Macal, C. M. and North, M. J. (2009). Agent-based modeling and simulation. In Proceedings of the 2009 winter simulation conference (WSC), pages 86–98. IEEE.
Masterman, T., Besen, S., Sawtell, M., and Chao, A. (2024). The landscape of emerging ai agent architectures for reasoning, planning, and tool calling: A survey. arXiv preprint arXiv:2404.11584.
Stokes, J. M., Yang, K., Swanson, K., Jin, W., Cubillos-Ruiz, A., Donghia, N. M., MacNair, C. R., French, S., Carfrae, L. A., Bloom-Ackermann, Z., et al. (2020). A deep learning approach to antibiotic discovery. Cell, 180(4):688–702.
Thurner, S. Hanel, R. and Klimek, P. (2018). Introduction to the theory of complex systems. Oxford University Press.
Wang, Q., Li, Y., and Li, R. (2024). Ecological footprints, carbon emissions, and energy transitions: the impact of artificial intelligence (ai). Humanities and Social Sciences Communications, 11(1):1043.
Wooldridge, M. and Jennings, N. R. (1995). Intelligent agents: Theory and practice. The knowledge engineering review, 10(2):115–152.
Fieguth, P. (2021). An Introduction to Complex Systems Society, Ecology, and Nonlinear Dynamic. Springer Cham.
Keynes, J. M. (1930). Economic possibilities for our grandchildren. In Essays in persuasion, pages 321–332. Springer.
Lam, R., Sanchez-Gonzalez, A., Willson, M., Wirnsberger, P., Fortunato, M., Alet, F., Ravuri, S., Ewalds, T., Eaton-Rosen, Z., Hu, W., et al. (2023). Learning skillful medium-range global weather forecasting. Science, page eadi2336.
Levin, S. A., Carpenter, S. R., Godfray, H. C. J., Kinzig, A. P., Loreau, M., Losos, J. B., Walker, B., and Wilcove, D. S. (2009). The Princeton guide to ecology. Princeton University Press.
Macal, C. M. and North, M. J. (2009). Agent-based modeling and simulation. In Proceedings of the 2009 winter simulation conference (WSC), pages 86–98. IEEE.
Masterman, T., Besen, S., Sawtell, M., and Chao, A. (2024). The landscape of emerging ai agent architectures for reasoning, planning, and tool calling: A survey. arXiv preprint arXiv:2404.11584.
Stokes, J. M., Yang, K., Swanson, K., Jin, W., Cubillos-Ruiz, A., Donghia, N. M., MacNair, C. R., French, S., Carfrae, L. A., Bloom-Ackermann, Z., et al. (2020). A deep learning approach to antibiotic discovery. Cell, 180(4):688–702.
Thurner, S. Hanel, R. and Klimek, P. (2018). Introduction to the theory of complex systems. Oxford University Press.
Wang, Q., Li, Y., and Li, R. (2024). Ecological footprints, carbon emissions, and energy transitions: the impact of artificial intelligence (ai). Humanities and Social Sciences Communications, 11(1):1043.
Wooldridge, M. and Jennings, N. R. (1995). Intelligent agents: Theory and practice. The knowledge engineering review, 10(2):115–152.
Publicado
27/11/2024
Como Citar
COSTA, Kleyton da; MODENESI, Bernardo; BLAY, Enio Alterman; MUNOZ, Cristian.
AI, Society and Environment: a Possible Complex System Framework. In: CONFERÊNCIA LATINO-AMERICANA DE ÉTICA EM INTELIGÊNCIA ARTIFICIAL, 1. , 2024, Niteroi.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2024
.
p. 145-148.
DOI: https://doi.org/10.5753/laai-ethics.2024.32473.
