[2A2-PS-2] When AI Meets the Oldest Engineering Discipline

[2A2-PS-2-01] When AI Meets the Oldest Engineering Discipline

Renate Fruchter¹ (1. Stanford University)

Builders represent one of the oldest engineering disciplines. Since the dawn of humanity people have built shelters, and then cities and infrastructure. They constantly shape and reshape our built environment and the way we live. We spend 90% of our time in buildings. Buildings consume 73% of U.S. electricity and generate 40% of U.S. greenhouse gas emissions. Building industry contributes a 5%-9% increase in the gross domestic product (GDP). According to UN and World Bank, approx. 56% of the world's population (4 billion people) resides in urban areas today. By 2030, 2 billion people will have migrated to cities, creating unprecedented pressure on infrastructure and resources, that will impact the environment.
What role can AI play in the building industry as an enabler of a more ecologically, economically, and socially sustainable future built environment?
We will explore scenarios how AI can be an integral part of innovative holistic approaches in the building industry to address challenges such as climate change, globalization, digitalization, and skilled workforce shortage.
We are in the midst of the 4th industrial revolution that is transforming the building industry as well. It is a time when the physical and digital worlds merge; where the world becomes a big data set as everyone and everything that is connected to the Internet becomes data source; where AI, machine learning, VR/AR/MR/XR, robotics, autonomous mobility will continuously reshape how and where we live. Convergence of these emergent technologies can act as exponential accelerators. How will they transform the building industry? How will they empower the knowledge worker to explore broader solution spaces, augment co-creation and collaboration, and make evidence-based, agile, joint decisions? How will they: (1) increase productivity, engagement, well-being, safety, and create digital value chain; (2) replace labor-intensive processes; and (3) reduce cost, schedule, time to market, energy consumption, carbon emission?