# Exploring the Societal and Economic Impacts of Artificial Intelligence: A Scenario Generation Methodology

arXiv: https://arxiv.org/abs/2504.01992 · HTML: https://mlsanity.com/paper/2504.01992/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 2 of its 28 references that are in the map.
- First posted on arXiv 31 Mar 2025.

## Builds on (most cited first, 2 of 2)

- [Predicting the Impact of Generative AI Using an Agent-Based Model](https://mlsanity.com/paper/2408.17268/) (2024)
- [Ethics and Artificial Intelligence Adoption](https://mlsanity.com/paper/2412.00330/) (2024)

## Built on by (most cited first, 2 of 2)

- [Agentic AI: A Comprehensive Survey of Architectures, Applications, and Future Directions](https://mlsanity.com/paper/2510.25445/) (2025)
- [The AI in the Mirror: LLM Self-Recognition in an Iterated Public Goods Game](https://mlsanity.com/paper/2508.18467/) (2025)

## Abstract (arXiv)

This paper explores artificial intelligence's potential societal and economic impacts (AI) through generating scenarios that assess how AI may influence various sectors. We categorize and analyze key factors affecting AI's integration and adoption by applying an Impact-Uncertainty Matrix. A proposed methodology involves querying academic databases, identifying emerging trends and topics, and categorizing these into an impact uncertainty framework. The paper identifies critical areas where AI may bring significant change and outlines potential future scenarios based on these insights. This research aims to inform policymakers, industry leaders, and researchers on the strategic planning required to address the challenges and opportunities AI presents