The deepening integration of social-technical systems creates immensely complex environments, creating increasingly uncertain and unpredictable circumstances. Given this context, policymakers have been encouraged to draw on complexity science-informed approaches in policymaking to help grapple with and manage the mounting complexity of the world. For nearly eighty years, complexity-informed approaches have been promising to change how our complex systems are understood and managed, ultimately assisting in better policymaking. Despite the potential of complexity science, in practice, its use often remains limited to a few specialised domains and has not become part and parcel of the mainstream policy debate. To understand why this might be the case, we question why complexity science remains nascent and not integrated into the core of policymaking. Specifically, we ask what the non-technical challenges and barriers are preventing the adoption of complexity science into policymaking. To address this question, we conducted an extensive literature review. We collected the scattered fragments of text that discussed the non-technical challenges related to the use of complexity science in policymaking and stitched these fragments into a structured framework by synthesising our findings. Our framework consists of three thematic groupings of the non-technical challenges: (a) management, cost, and adoption challenges; (b) limited trust, communication, and acceptance; and (c) ethical barriers. For each broad challenge identified, we propose a mitigation strategy to facilitate the adoption of complexity science into policymaking. We conclude with a call for action to integrate complexity science into policymaking further.

社会技术系统的深化整合创造了极其复杂的环境，造成了越来越不确定和不可预测的情况。鉴于这种背景，政策制定者被鼓励在政策制定中利用复杂性科学方法来帮助应对和管理世界日益复杂的情况。近八十年来，基于复杂性的方法一直有望改变我们对复杂系统的理解和管理方式，最终有助于更好的决策。尽管复杂性科学具有潜力，但在实践中，它的使用往往仍然仅限于几个专门领域，并且尚未成为主流政策辩论的重要组成部分。为了理解为什么会出现这种情况，我们质疑为什么复杂性科学仍然处于萌芽阶段并且没有融入政策制定的核心。具体来说，我们询问哪些非技术挑战和障碍阻碍了复杂性科学在政策制定中的采用。为了解决这个问题，我们进行了广泛的文献回顾。我们收集了分散的文本片段，讨论了与在政策制定中使用复杂性科学相关的非技术挑战，并通过综合我们的发现将这些片段缝合到一个结构化框架中。我们的框架由非技术挑战的三个主题组组成：(a) 管理、成本和采用挑战； (b) 有限的信任、沟通和接受； (c) 道德障碍。对于所确定的每一个广泛的挑战，我们提出了缓解策略，以促进将复杂性科学应用于政策制定。最后，我们呼吁采取行动，进一步将复杂性科学纳入政策制定。