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As Director of Innovation, I’m pleased to present a series of articles on computational thinking. The series is authored by Dauphin Flores, our resident expert in the field. Through a focused exploration of methodologies and applications, Dauphin aims to provide a nuanced understanding of computational thinking’s role in problem-solving, specifically as it pertains to the AEC industry. – Sean Turner

Within the continually evolving technological landscape, the architecture, engineering, and construction (AEC) industry experiences consistent transformation through innovation. Given the critical nature of the field, there’s an inherent cautiousness in adopting new methodologies, yet engineers and architects incessantly strive for advancement, aiming for a harmonious amalgamation of precision, efficacy, and ingenuity.

The transition from meticulous hand-drawn designs to the adoption of 2D and 3D modelling software signified a monumental advancement in efficiency and accuracy within the AEC industry. Similarly, enhancements in project management tools and communication platforms have fostered improved collaboration among stakeholders. Today, the integration of computers and machines working alongside humans serves as a testament to the fundamental importance of computational thinking (CT). The growing prevalence and sophistication of such technological integrations underscore a pivotal reality: those not adept in CT risk falling behind.

While programming languages function as a conduit for interaction between humans and machines, CT guides us through the formulation of meaningful instructions. It is more than a technical skill; it is a sophisticated language, a bridge fostering effective communication between humans and machines. More formally defined, CT is an analytical methodology for modelling a situation and creating executable instructions to achieve an objective within a set of boundary conditions. These instructions are carried out by a “computer”—a term that, while commonly associated with machines today, originally referred to humans performing calculations. This historical nuance highlights the lasting, reciprocal relationship between humans and machines in computational endeavors.

Business-Related Outcomes

Before we delve deeper into the intricacies and mechanisms of CT, we should first discuss the practical benefits, especially the tangible business-related outcomes. In the client-focused AEC industry, delivering the right product at the right time is paramount. Here, CT emerges as an invaluable tool, continually enhancing efficiency by allowing quick adjustments through design simulations and fostering the incorporation of automation. This consistently reduces time spent on calculations and design, boosting not only the financial outcomes of individual projects but also enabling engagement in larger, more complex projects and allowing for the exploration of new revenue streams.

Risk mitigation, a cornerstone for engineers entrusted with safeguarding public safety, is another area where CT shines. By delegating detailed engineering calculations to machines, CT reduces the potential for human errors. It also enhances the quality of engineering through simulations that uncover innovative design solutions, which might otherwise go unnoticed.

Moreover, the adoption of CT correlates with an increase in profits. The gained efficiencies can be strategically deployed for organizational growth or, if expansion isn’t a focal point, to enhance profit margins on an individual project basis. CT also plays a significant role in elevating employee morale and engagement. Automating routine tasks allows people to shift their focus towards more intellectually challenging and rewarding assignments, fostering a vibrant and productive work environment, and contributing to heightened job satisfaction.

Cognitive Collaboration

Far from the dystopian predictions of metallic humanoids overthrowing humanity, our reality is marked by a harmonious interplay between the computational prowess of machines and the intellectual versatility of humans. This partnership, known as cognitive collaboration, melds the unique strengths of both partners, producing outcomes that neither could achieve independently. And this isn’t just theoretical; it’s a tangible reality unfolding in our times.

The effectiveness of cognitive collaboration was demonstrated in a very public way at the 2005 Freestyle Chess Tournament. Freestyle chess, a variant conceived by Garry Kasparov—who holds the distinction of being the first world chess champion defeated by a computer—allows humans and computers to form partnerships and compete against other hybrid teams. Several teams of highly rated grandmasters paired with high-performance computers participated, but in the end, it was a New Hampshire-based team comprising two untitled amateurs and three consumer-grade computers who won the tournament. Steven Cramton, a member of the winning team, attributed their success to an effective methodology determining when to rely on computer analysis and when to trust human judgment. This exemplifies true synergy, where the collective capability surpasses the sum of individual contributions.

This A.I. generated work, “Théâtre D’opéra Spatial” by Matthew Allen, Public Domain, won first place in the Colorado State Fair, demonstrating the effectiveness of Cognitive Collaboration.

Effective interfacing enables the adjustment of the human-machine partnership to match the unique conditions of each encountered situation. Instead of being constrained by the limitations of mass-produced software, CT empowers humans to create situation-specific software integrations to meet the demands of complex workflows. This freedom to design more efficient, custom applications avoids the need to squeeze workflows into the constraints imposed by traditional software, offering tailored solutions for varied needs.

Further research substantiates the competitive edge offered by cognitive collaboration. A study conducted by researchers at Kyoto University compared the quality of haikus crafted by humans, AI, and their collaborations. The findings revealed that, while human and AI-generated haikus were comparable in quality, the collaborative compositions consistently received the highest evaluations, attesting to the remarkable potential of uniting human ingenuity with machine intelligence.

Cognitive collaboration also serves as a bulwark against the phenomenon known as “burnout,” wherein intense cognitive efforts are shown to hinder creative thinking and problem-solving abilities. Today, burnout is recognized in mainstream medicine as a medical disorder and has even been assigned a diagnosis code. By redistributing strenuous computational tasks from humans to machines, cognitive collaboration not only mitigates the risk of burnout but also minimizes stress. This, in turn, enables humans to realize their full creative and problem-solving potential.

Final Thoughts

CT serves as a common language that allows humans to work in unison with advanced technology to reach a common goal. In the AEC industry, this approach provides both a framework and tools for tackling complex problems, facilitating both innovation and efficiency.

In Part 2, we’ll look at the impact of computational thinking on the practice of engineering and organizational collective intelligence. We’ll also share tangible applications of CT in real-world projects within the AEC industry and here at Henderson. Stay tuned as we uncover how computational thinking is revolutionizing practices and outcomes in the AEC landscape.