AI时代的享乐适应：关于技术采用中满意度回报递减的一个视角
Hedonic Adaptation in the Age of AI: A Perspective on Diminishing Satisfaction Returns in Technology Adoption
AI总结：
本文提出用享乐适应理论解释AI技术进步与用户满意度不匹配的现象，指出满意度呈对数增长并形成长期缺口，主张AI发展应从单纯扩展技术规模转向维持用户感知价值。
摘要：
人工智能（AI）通过将不断上升的计算能力与性能提升相联系的规模定律实现了快速进步，带来了巨大的技术突破。然而，这些突破并未转化为相应的用户满意度提升，从而造成了一种普遍的不匹配。本研究提出，享乐适应——即人们在剧烈变化后恢复到幸福感基线状态的心理过程——为理解这一现象提供了一个合适的模型。我们认为，用户对AI的满意度遵循对数路径，因此随着人们迅速将新能力视为预期，会形成长期的“满意度缺口”。这一过程通过离散阶段发生：初始兴奋、回报递减、稳定以及偶发性回升，具体取决于适应速度和能力引入节奏。这些过程对AI研究、用户体验设计、市场营销和伦理具有深远影响，表明需要从单纯的技术规模扩展转向在人类适应过程中维持感知价值的方法的范式转变。这一视角重新框定了AI发展，要求采用使技术进步与人们的主观体验相一致的做法。
英文摘要：
The fast paced progress of artificial intelligence (AI) through scaling laws connecting rising computational power with improving performance has created tremendous technological breakthroughs. These breakthroughs do not translate to corresponding user satisfaction improvements, resulting in a general mismatch. This research suggests that hedonic adaptation the psychological process by which people revert to a baseline state of happiness after drastic change provides a suitable model for understanding this phenomenon. We argue that user satisfaction with AI follows a logarithmic path, thus creating a longterm "satisfaction gap" as people rapidly get used to new capabilities as expectations. This process occurs through discrete stages: initial excitement, declining returns, stabilization, and sporadic resurgence, depending on adaptation rate and capability introduction. These processes have far reaching implications for AI research, user experience design, marketing, and ethics, suggesting a paradigm shift from sole technical scaling to methods that sustain perceived value in the midst of human adaptation. This perspective reframes AI development, necessitating practices that align technological progress with people's subjective experience.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
