Systems Thinking and Design, Architecture, and Strategy for Sustainability Business
/We can reflect upon the last century of infrastructure and see clearly the impact of each choice, positive or negative, and analyze the implicit ideological commitments that drove them. As we begin the long process of updating our infrastructure, we should consider the business model, the methodological and technological perspectives that have led to such brittle and unsustainable systems. By confronting the infrastructure challenge in a novel way—both with the methods and technologies we employ as well the way we conceive the infrastructure business model—our built systems stand a better chance of enduring an opaque future.
Such a shift in method is, of course, all the more vital today given current climate change projections. Not only will our infrastructure be subject to heavier use in the coming century, but the latest climate science gives us good reason to believe that it will also face increasingly extreme weather events. The type and frequency of such events are, to a degree, unknowable and, given their nature, engineers cannot rely on historical weather records to furnish enough information to avoid catastrophic failure altogether. In other words, not only must we rebuild our infrastructure to meet our present and future needs, but it must also be more robust, resilient, and adaptable than ever before.
In this initiative, we develop a systems philosophy of infrastructure and systems thinking and design, architecture, and strategy for sustainability business via a critique of historical methods used in infrastructure and their social, technical, and ecological implications. We demonstrate that these methods—in design, planning, and funding—and their associated assumptions, while perhaps adequate at the time, are responsible for many of the problems facing our infrastructure today. This, we believe, amounts to an infrastructure paradigm failure. We aim for a set of general principles and methods to remedy this failure, rooted in systems theory, for application in future infrastructure system development.
Complex Cyber-Human-Physical Systems (CHPS) are part of the solution. CHPS (e.g., networks of intelligent vehicles and sensors, multiscale adaptive sensor-data fusion algorithms with humans in the loop) can help solve these global challenges. For instance, an affordable sensor web consisting of a combination of small satellites, unmanned aerial vehicles, and ground vehicles can help us tackle the food-water-energy challenge by providing the frequent, low-latency, multiscale resolution and high-accuracy measurements of soil moisture, precipitation, vegetation state, land use, and other parameters needed to increase efficient and productive water management and precision agriculture practices.
Among the most important and often ignored challenges in the design and operation of CHPS are those related to human behavior, and the interaction of humans with the components of the CHPS. The response to, and adoption of, disruptive technology depends not only on how the technology is engineered, but also on the preferences and attitudes that shape our decision making and behavior as users and non-users of the technology. Human behavior is complex, with gaps between intended actions and actual behavior, heterogeneous preferences, and differing decision rules and heuristics applied when individuals make choices, as well as network effects that force or reinforce specific actions.
In addition, communication between humans and systems is currently poor, slow, and ineffective, which limits the performance of CPHS. Furthermore, current functional allocations typically assign the roles of master and slave to either the humans or the systems, limiting the exploration of mixed-initiative strategies in which humans and systems truly collaborate as peers, which may lead to unprecedented levels of performance and resilience (e.g., when they compensate for weaknesses of both humans and systems).
In terms of design, the traditional way of developing complex systems is to derive requirements and design the most affordable system that satisfies those requirements. However, deriving requirements from stakeholders is not trivial due to latent needs; stakeholders are often not conscious of or able to adequately express their real needs. Thus, new ways must be developed to elicit and capture needs that are more effective and lead to more nuanced and intelligent designs. Moreover, computational tools can be used to search the space of design alternatives, but it is often too large to be searched effectively. Expert knowledge can accelerate the search, but we need methods that foster the discovery and leveraging of knowledge without sacrificing exploration of promising new designs.
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