人工智能赋能下产业创新生态系统的双重转型

Dual-transition of sectoral innovation ecosystem empowered by artificial intelligence

当前,人工智能赋能不断推进技术创新和应用创新进入“双拐点”时期,正在从要素构成、功能边界、生态互动等多个维度对产业创新生态系统理论提出新挑战。本文集成自然生态系统和产业创新系统等相关理论,基于“核心驱动层-样态变革层”构建人工智能赋能下产业创新生态系统双重转型的理论框架,并以无人驾驶为例,深入剖析产业创新生态系统双重转型的运行逻辑和实践变革。研究发现结论如下:一是创新主体生态功能延展催生多宿主体和次生群落的出现,使得产业创新生态系统新型生态互动关系逐渐形成,成为产业创新生态系统由“旧四螺旋创新”向“新四螺旋创新”演进的核心动源;二是产业创新生态系统核心驱动与样态变革的相互作用日益增强,多宿主体和次生群落不断推动产业样态快速变革,使得产业样态呈现出价值分配重构、智能制造升级、商业模式转变、组织决策变革的发展特征。

Nowadays,artificial intelligence(AI),as a main force leading the new round of disruptive industrial change,begin to spread and accelerate enabling in various fields.Meanwhile,the artificial intelligence enables the“double transition”of technology innovation and application innovation,which puts forward emerging challenges to sectoral innovation ecosystem(SIES)from multi-dimensions,such as the production factors,the function boundary,the interaction relationship,etc.The transitions of SIES empowered by AI leads to following thinking in this paper:what original changes will AI enable the main composition and biological community of SIES?What breakthrough changes will AI enabling make in the main ecological position and interactive relationship in SIES?What disruptive changes will take place in industrial pattern due to the transitions of SIES empowered by AI?Learning lessons from theories of nature ecosystem and SIES,this paper constructs the theoretical framework of dual-transition(including core driving layer-industrial pattern change layer)empowered by AI,and the operation logic and industrial revolution within SIES are analyzed by the case study of autonomous driving.It mainly includes two steps in this part.First,based on the theoretical framework of SIES transition,this paper reveals the dynamic process of“core drive leading to industrial change”,and explains the new interactions among innovators in the SIES.To explore the core driving layer,the article also draws the cross-sectional view of the evolution from“traditional quadruplex helix”to“emerging quadruplex helix”,which also explains the generation of multi-homing actor and secondary communities in the SIES.Second,taking autonomous driving as an example,this paper gives the keywords’co-occurrence network of autonomous driving SIES,and makes practical analysis on four aspects of SIES transition empowered by AI.The research findings are as follows:first,the emergence of multi-homing actor and secondary communities give rise to the new ecological interaction of SIES,and it becomes the core driver pushing SIES from traditional quadruplex helix to emerging quadruplex helix.Second,the interaction of core driving and industrial change are increasingly enhanced,and multi-homing actor and secondary communities continuously trigger industrial practice changes.These make characteristics of industrial patterns tend to reconstruct of value distribution,upgrade of intelligent manufacturing,adaptation of business model,and revolution of organizational decision-making.All in all,an emerging SIES integrating“core driving layer-industrial pattern change layer”empowered by AI is becoming clearer and clearer.This paper contributes to existing research in the following two aspects:first,it puts forward and demonstrates new concepts of multi-homing actor and secondary communities.And it explains the emerging quadruplex helix innovation by exploring secondary communities including technological innovation,product manufacturing,market application and policy regulation.By interpreting the existence of multi-homing actor and secondary communities,this paper break through the theoretical dilemma about the fuzzy function boundary in SIES.Second,by describing the industrial patterns and emerging characteristics empowered by AI,this paper verifies the practical transition(such as reconstruct of value distribution,upgrade of intelligent manufacturing,adaptation of business model,and revolution of organizational decision-making)of autonomous driving SIES,which strongly proves that AI enabling is triggering ubiquitous changes in industrial patterns.