Artificial intelligence decision-making and human decision-making from an evolutionary game perspective:exploring new pathways for sustainable development
As environmental challenges intensify,there is a growing demand for strategies that not onlv foster economic growth but also promote sustainable development.In light of these urgent issues,the rapid advancement of Artificial Intelligence(AI)technology presents innovative solutions that can make a substantial impact on sustainability initiatives.This study examines the interactions between AI-based decision-making systems and those guided by human judgment in the context of sustainable development.Utilizing evolutionary game theory,along with concepts from prospect theory and mental accounting,the research conducted a series of simulations in MATLAB to model the behavior of human decision-makers,especially when they make irrational choices.In scenarios where AI facilitates decision-making,both businesses and governments utilize AI to evaluate a range of influencing factors—including additional benefits,tax structures,regulatory costs,and environmental impacts—on their strategic choices.Conversely,in scenarios driven by human decision-making,these entities depend on human insights to address the irrational tendencies identified in prospect theory and mental accounting.They evaluate how factors such as decision sensitivity,risk preferences,and potential damage to reputation influence outcomes.The findings highlight AI's exceptional capability to improve decision-making speed and logical analysis,especially when managing large datasets and rapidly identifying changes in environmental conditions and market trends.In contrast,human decision-making excels in areas that require a deeper consideration of ethics,complexity,and reputation,making it essential for addressing broader moral and contextual issues.The unique contribution of this paper lies in its use of simulation analysis to investigate the performance of the two decision-making systems under varying parameters.This approach reveals the dynamic process of strategy selection rather than simply presenting generalized conclusions.Furthermore,this paper not only compares the strengths and weaknesses of both systems but also explores the synergistic effects of AI and human decision-making in environmental management.The results indicate that the combination of AI decision-making by enterprises and human decision-making by the government is more effective in achieving green collaborative development than relying on either AI or human decision-making alone.
basic disciplines of environmental science and technologysustainable developmentprospect theorypsychological accounting theoryevolutionary game theory
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