2024/11/14 by Carlos J. Costa, Costa, Carlos J., João Tiago Aparício +5 · 1 voice · 1 citation
Computer Science · Social Sciences · #Computers and Society (cs.CY) #Ethics and Social Impacts of AI #FOS: Computer and information sciences #cs.CY
paper · pdf · doi:10.48550/arxiv.2411.09313
openalex publication_date 2024/11/14 · arxiv published 2024/11/14 · arxiv updated 2024/11/14 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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.