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Costa, C., Joao Tiago Aparicio & Mnuela Aparicio (N/A). Socio-Economic Consequences of Generative AI: A Review of Methodological Approaches. In  Proceedings of 19th Iberian Conference on Information Systems and Technologies (CISTI 2024). (pp. 509-521).

C. M. Costa et al.,  "Socio-Economic Consequences of Generative AI: A Review of Methodological Approaches", in  Proc. of 19th Iberian Conf. on Information Systems and Technologies (CISTI 2024), N/A, pp. 509-521

@incollection{costaN/A_1776762875375,
	author = "Costa, C. and Joao Tiago Aparicio and Mnuela Aparicio",
	title = "Socio-Economic Consequences of Generative AI: A Review of Methodological Approaches",
	chapter = "",
	booktitle = " Proceedings of 19th Iberian Conference on Information Systems and Technologies (CISTI 2024)",
	year = "N/A",
	volume = "",
	series = "",
	edition = "",
	pages = "509-509",
	publisher = "",
	address = ""
}

TY  - CHAP
TI  - Socio-Economic Consequences of Generative AI: A Review of Methodological Approaches
T2  -  Proceedings of 19th Iberian Conference on Information Systems and Technologies (CISTI 2024)
AU  - Costa, C.
AU  - Joao Tiago Aparicio
AU  - Mnuela Aparicio
PY  - N/A
SP  - 509-521
DO  - 10.1007/978-3-032-12888-1_43
AB  - The widespread adoption of generative artificial intelligence (AI) has fundamentally transformed technological landscapes and societal structures in recent years. Our objective is to identify the primary methodologies that may be used to help predict the economic and social impacts of generative AI adoption. Through a comprehensive literature review, we uncover a range of methodologies poised to assess the multifaceted impacts of this technological revolution. We explore Agent-Based Simulation (ABS), Econometric Models, Input-Output Analysis, Reinforcement Learning (RL) for Decision-Making Agents, Surveys and Interviews, Scenario Analysis, Policy Analysis, and the Delphi Method. Our findings have allowed us to identify these approaches’ main strengths and weaknesses and their adequacy in coping with uncertainty, robustness, and resource requirements.
ER  -