The Pivotal Role of Accounting in Civilizational Progress and the Age of Advanced AI: A Unified Perspective
DOI:
https://doi.org/10.71222/cee72027Keywords:
impact of accounting, social civilization, AGI, ASI, UBI, global progress, ethical advancementAbstract
This paper comprehensively explores the significant role that accounting plays in the progress of social civilization and delves into the profound impact of accounting on the advancement of social civilization, integrating its historical evolution and modern applications with emerging technological trends in Artificial Intelligence (AI), Artificial General Intelligence (AGI), Artificial Superintelligence (ASI), and Universal Basic Income (UBI). By examining accounting's role in fostering economic growth, corporate governance, governmental functioning, and social equity, alongside the transformative potential of advanced AI, the paper highlights how these domains interconnect to shape future societies. Comparative analyses between socialist and capitalist accounting systems underscore diverse approaches to leveraging AI technologies for equitable development and innovation. The findings illuminate the indispensable role of accounting as a cornerstone for global progress and ethical advancement in an AI-dominated era.
References
1. N. Bostrom, Superintelligence: Paths, Dangers, Strategies, Oxford University Press, 2014, ISBN: 978-0199678112.
2. Z. Ke, J. Xu, Z. Zhang, Y. Cheng, and W. Wu, "A Consolidated Volatility Prediction with Back Propagation Neural Network and Genetic Algorithm," arXiv preprint arXiv:2412.07223, 2024.
3. P. Dockrill, "AI Seems to Be Better at Distributing Wealth Than Humans Are, Study Hints," ScienceAlert, Jul. 4, 2022. [Online]. Available: https://www.sciencealert.com/ai-could-be-be-better-at-distributing-wealth-experiment-suggests. [Accessed: Jan. 22, 2025].
4. J. Rao, Q. Zhang, Z. Ke, S. Liu, and X. Liu, "Integrating Textual Analytics with Time Series Forecasting Models: Enhancing Predictive Accuracy in Global Energy and Commodity Markets," Innovations in Applied Engineering and Technology, pp. 1-7, 2023, doi: 10.62836/iaet.v2i1.265.
5. K. H. Nguyen, T. Comans, T. T. Nguyen, et al., "Cashing in: cost-benefit analysis framework for digital hospitals," BMC Health Serv. Res., vol. 24, no. 694, 2024, doi: 10.1186/s12913-024-11132-7.
6. D. M. Kammen, P. Hendricks, S. Pendleton-Knoll, V. Stanley, and R. Strand, "Patagonia's Path to Carbon Neutrality by 2025," Harvard Business Review, Apr. 1, 2018, doi: 10.4135/9781526464521.
7. Q. Yu, Z. Xu, and Z. Ke, "Deep Learning for Cross-Border Transaction Anomaly Detection in Anti-Money Laundering Systems," arXiv preprint arXiv:2412.07027, 2024.
8. S. C. Miller, Sustainable Trailblazing: A Comprehensive Analysis of Patagonia's Corporate Social Responsibility Initiatives and Their Ethical Implications, Belhaven University, Nov. 11, 2023, doi: 10.13140/RG.2.2.18295.60320.
9. D. Liu and M. Jiang, "Distance Recomputator and Topology Reconstructor for Graph Neural Networks," arXiv preprint arXiv:2406.17281, 2024.
10. D. Luo, "Optimizing Load Scheduling in Power Grids Using Reinforcement Learning and Markov Decision Processes," arXiv preprint arXiv:2410.17696, 2024.
11. Z. Ke and Y. Yin, "Tail Risk Alert Based on Conditional Autoregressive VaR by Regression Quantiles and Machine Learning Algorithms," arXiv preprint arXiv:2412.06193, 2024.
