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<p>Artificial intelligence (AI) is no longer just a decision-support tool; it is now a powerful agent reshaping social and economic behavior by interacting with and modifying human psychology. This article explores how AI technologies rewrite the traditional rules of economic decision-making by amplifying cognitive biases, reshaping preferences, and even altering emotional responses. Building on the foundations of behavioral economics and bounded rationality, this paper relies on the concept of algorithm-induced cognitive adaptation to describe how sustained AI interaction can reconfigure cognitive processes. It then examines three emerging dynamics: the micro-management of labor incentives through algorithmic nudging, the construction of preferences in attention-based economies, and the emotional influence of affective computing. These developments challenge classical notions of autonomy, rationality, and consumer sovereignty. Moreover, this paper addresses ethical and regulatory dilemmas, including privacy, transparency, bias, and inequality. Finally, it outlines future strategies for aligning AI systems with human well-being, emphasizing education, governance, and cooperative design. As AI-mediated environments continue to evolve, understanding their psychological impact becomes essential for designing systems that empower rather than exploit human behavior.</p>

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Artificial intelligence and economic psychology: toward a theory of algorithmic cognitive influence

  • 期刊论文

  • 发表日期：

    2025年9月8日

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  • Francisco Rodriguez-Fernandez

摘要

Artificial intelligence (AI) is no longer just a decision-support tool; it is now a powerful agent reshaping social and economic behavior by interacting with and modifying human psychology. This article explores how AI technologies rewrite the traditional rules of economic decision-making by amplifying cognitive biases, reshaping preferences, and even altering emotional responses. Building on the foundations of behavioral economics and bounded rationality, this paper relies on the concept of algorithm-induced cognitive adaptation to describe how sustained AI interaction can reconfigure cognitive processes. It then examines three emerging dynamics: the micro-management of labor incentives through algorithmic nudging, the construction of preferences in attention-based economies, and the emotional influence of affective computing. These developments challenge classical notions of autonomy, rationality, and consumer sovereignty. Moreover, this paper addresses ethical and regulatory dilemmas, including privacy, transparency, bias, and inequality. Finally, it outlines future strategies for aligning AI systems with human well-being, emphasizing education, governance, and cooperative design. As AI-mediated environments continue to evolve, understanding their psychological impact becomes essential for designing systems that empower rather than exploit human behavior.