Coordinating paradox: Strategic choices in artificial intelligence “functionality-safety” framework

Abstract

Abstract:

The rapid development of Artificial Intelligence (AI) technology creates opportunities while simultaneously intensifying concerns regarding its safety risks and alignment problems. Existing research often discusses AI functionality (the technical capability for automated decision-making) and AI safety (the responsible attribute for risk prevention) in isolation, overlooking their inherent paradoxical relationship. This study aims to explore how to coordinate the tension between functionality and safety through strategic design to achieve sustainable competitive advantage. We propose an AI "Functionality-Safety" paradox framework and identify four core scenarios of interaction between functionality and safety. Meanwhile, by integrating perspectives from paradox theory and dynamic capability theory, we formulate the core viewpoints on the AI "Functionality-Safety" paradox. On this basis, the study puts forward dynamically matched strategic paths for different scenarios, explains the non-linear relationships and balance mechanisms among AI application timing, internal and external capabilities, and corporate performance under different strategies. The main contributions of this study lie in constructing an AI technology analysis framework that integrates the functionality and safety dimensions, forming dynamic synergy perspectives on the AI "Functionality-Safety" paradox, and establishing the dynamic matching between AI scenarios and collaborative strategies. This study provides theoretical guidance and practical implications for firms' paradox collaborative management and AI strategies.

Key words: artificial intelligence, AI functionality, AI safety, dynamic capabilities, paradox theory

摘要：

人工智能(AI)技术的快速发展在创造机遇的同时,也加剧了对其安全风险与对齐问题的担忧。现有研究常将AI智能性(执行自动化决策的技术能力)与AI安全性(防范风险的责任属性)割裂讨论,忽视其内在悖论关系。本研究旨在探究如何通过战略设计协调智能性与安全性的张力并获取可持续竞争优势。本研究提出AI“智能-安全”悖论框架,识别出智能与安全交互的四类核心情境;同时,整合悖论理论与动态能力理论,形成AI“智能-安全”悖论核心观点;在此基础上,针对不同情境提出动态匹配的战略路径,阐释了不同战略下AI应用时间、内外能力与企业绩效的非线性关系及平衡机制。本研究主要贡献在于构建了整合智能与安全维度的AI技术分析框架,形成了AI“智能-安全”悖论的动态协同观点,建立了AI情境与协同战略的动态匹配。本研究为企业悖论协同管理和AI情境适配战略提供了理论指导和实践启示。

关键词: 人工智能, AI智能性, AI安全性, 动态能力, 悖论理论

CLC Number:

LI Yuan, LI Ping, XU Ya-nan. Coordinating paradox: Strategic choices in artificial intelligence “functionality-safety” framework[J]. Studies in Science of Science, 2026, 44(10): 2017-2027.

李垣, 李平, 许雅楠. 协调悖论:人工智能“智能-安全”的战略选择[J]. 科学学研究, 2026, 44(10): 2017-2027.

Figures/Tables 2

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状态组合		低智能-低安全	低智能-高安全	高智能-低安全	高智能-高安全
对应战略		整体突破	智能强化	安全提升	持续平衡
能力建设	内部	寻求突破	提升智能水平	安全能力建设	持续创新协同
能力建设	外部	游说外部支持	呼吁安全门槛	优化合作生态	构建标准与扩展优势
绩效影响		负向	U型	倒U型	正向
理论假说		1a, 1b, 1c	2a, 2b, 2c, 2d	3a, 3b, 3c, 3d	4a,4b,4c

状态组合		低智能-低安全	低智能-高安全	高智能-低安全	高智能-高安全
对应战略		整体突破	智能强化	安全提升	持续平衡
能力建设	内部	寻求突破	提升智能水平	安全能力建设	持续创新协同
能力建设	外部	游说外部支持	呼吁安全门槛	优化合作生态	构建标准与扩展优势
绩效影响		负向	U型	倒U型	正向
理论假说		1a, 1b, 1c	2a, 2b, 2c, 2d	3a, 3b, 3c, 3d	4a,4b,4c