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Abstract Infrastructure systems have legacies that continue to define their priorities, goals, flexibility, and ability to make sense of their environments. These legacies may or may not align with future needs, but regardless of alignment, they may restrict viable pathways forward. Infrastructure ‘lock-in’ has not been sufficiently confronted in infrastructure systems. Lock-in can loosely be interpreted as internal and external pressures that constrain a system, and it encourages self-reinforcing feedback where the system becomes resistant to change. By acknowledging and recognizing that lock-in exists at small and large scales, perpetuated by individuals, organizations, and institutions, infrastructure managers can critically reflect upon biases, assumptions, and decision-making approaches. This article describes six distinct domains of lock-in: technological, social, economic, individual, institutional, and epistemic. Following this description, strategies for unlocking lock-in, broadly and by domain, are explored before being contextualized to infrastructure systems. Ultimately, infrastructure managers must make a decision between a locked in and faltering but familiar system or a changing and responsive but unfamiliar system, where both are, inevitably, accepting higher levels of risk than typically accustomed. 

Disruption of legacy infrastructure systems by novel digital and connected technologies represents not simply the rise of cyberphysical systems as hybrid physical and digital assets but, ultimately, the integration of legacy systems into a new cognitive ecosystem. This cognitive ecosystem, an ecology of massive data flows, artificial intelligence, institutional and intellectual structures, and connected technologies, is poised to alter how humans and artificial intelligence understand and control our world. Infrastructure managers need to be ready for this paradigm shift, recognizing their systems are increasingly being absorbed into an emerging suite of data, analytical tools, and decisionmaking technologies that will fundamentally restructure how legacy systems behave and are controlled, how decisions are made, and most importantly how workers interact with the systems. Infrastructure managers must restructure their organizations and engage in cross-organizational sensemaking if they are to be capable of navigating the complexity of the cognitive ecosystem. The cognitive ecosystem is fundamentally poised to change what infrastructures are, necessitating the need for managers to take a close look at the functions and actions of their own systems. The continuing evolution of the Anthropocene and the cognitive ecosystem has profound implications for infrastructure education. A sustained commitment to change is necessary that restructures and reorients infrastructure organizations within the cognitive ecosystem, where knowledge is generated, and control of services is wielded by myriad stakeholders.

 

Infrastructure systems must change to match the growing complexity of the environments they operate in. Yet the models of governance and the core technologies they rely on are structured around models of relative long-term stability that appear increasingly insufficient and even problematic. As the environments in which infrastructure function become more complex, infrastructure systems must adapt to develop a repertoire of responses sufficient to respond to the increasing variety of conditions and challenges. Whereas in the past infrastructure leadership and system design has emphasized organization strategies that primarily focus on exploitation (e.g., efficiency and production, amenable to conditions of stability), in the future they must create space for exploration, the innovation of what the organization is and does. They will need to create the abilities to maintain themselves in the face of growing complexity by creating the knowledge, processes, and technologies necessary to engage environment complexity. We refer to this capacity asinfrastructure autopoiesis. In doing so infrastructure organizations should focus on four key tenets. First, a shift to sustained adaptation—perpetual change in the face of destabilizing conditions often marked by uncertainty—and away from rigid processes and technologies is necessary. Second, infrastructure organizations should pursue restructuring their bureaucracies to distribute more resources and decisionmaking capacity horizontally, across the organization’s hierarchy. Third, they should build capacity for horizon scanning, the process of systematically searching the environment for opportunities and threats. Fourth, they should emphasize loose fit design, the flexibility of assets to pivot function as the environment changes. The inability to engage with complexity can be expected to result in a decoupling between what our infrastructure systems can do and what we need them to do, and autopoietic capabilities may help close this gap by creating the conditions for a sufficient repertoire to emerge.

 

Pervasive and accelerating climatic, technological, social, economic, and institutional change dictate that the challenges of the future will likely be vastly different and more complex than they are today. As our infrastructure systems (and their surrounding environment) become increasingly complex and beyond the cognitive understanding of any group of individuals or institutions, artificial intelligence (AI) may offer critical cognitive insights to ensure that systems adapt, services continue to be provided, and needs continue to be met. This paper conceptually links AI to various tasks and leadership capabilities in order to critically examine potential roles that AI can play in the management and implementation of infrastructure systems under growing complexity and uncertainty. Ultimately, various AI techniques appear to be increasingly well-suited to make sense of and operate under both stable (predictable) and chaotic (unpredictable) conditions. The ability to dynamically and continuously shift between stable and chaotic conditions is critical for effectively navigating our complex world. Thus, moving forward, a key adaptation for engineers will be to place increasing emphasis on creating the structural, financial, and knowledge conditions for enabling this type of flexibility in our integrated human-AI-infrastructure systems. Ultimately, as AI systems continue to evolve and become further embedded in our infrastructure systems, we may be implicitly or explicitly releasing control to algorithms. The potential benefits of this arrangement may outweigh the drawbacks. However, it is important to have open and candid discussions about the potential implications of this shift and whether or not those implications are desirable. 

Modern infrastructure have been a relatively stable force for decades, ensuring that basic and critical services are met, without significantly changing their core designs or management principles. At the dawn of the Anthropocene it appears that accelerating and increasingly uncertain conditions are poised to result in a paradigm shift for infrastructure, where the environments in which they operate are changing faster than the systems themselves. New approaches are needed in the education, governance, and physical structures that constitute infrastructure systems that can respond in pace. Principles of agility and flexibility appear well suited to help guide how we transform the management and design of infrastructure. In changing how we approach infrastructure we will need to respond to increasingly wicked challenges. Infrastructure must become a Fifth Discipline, focused on learning about the rapidly changing environments and demands in which they operate, and agility and flexibility in both governance and technology reconfiguration. KEYWORDS: Infrastructure, Anthropocene, agility and flexibility, adaptive, resilience 

Infrastructure are at the center of three trends: accelerating human activities, increasing uncertainty in social, technological, and climatological factors, and increasing complexity of the systems themselves and environments in which they operate. Resilience theory can help infrastructure managers navigate increasing complexity. Engineering framings of resilience will need to evolve beyond robustness to consider adaptation and transformation, and the ability to handle surprise. Agility and flexibility in both physical assets and governance will need to be emphasized, and sensemaking capabilities will need to be reoriented. Transforming infrastructure is necessary to ensuring that core systems keep pace with a changing world.