368I_Josh Rands, Co-Founder and CEO at TerraCity
🎯 Summary
Podcast Episode Summary: 368I_Josh Rands, Co-Founder and CEO at TerraCity
This episode of the “What is the Future for Cities” podcast features an in-depth conversation with Josh Rands, Co-Founder and CEO of TerraCity, focusing on integrating environmental sustainability with urban planning, particularly through the lens of transportation and land use, powered by AI modeling.
1. Focus Area
The discussion centers on Urban Planning, Transportation Modeling, and Sustainability. Key themes include defining the modern “city” (physical vs. digital community), the complex interplay between transportation and land use, the role of technology (specifically AI/ML) in informing public sector decision-making, and reframing sustainability through economic principles like True Cost Accounting and minimizing the Green Premium.
2. Key Technical Insights
- AI in Public Planning: TerraCity is developing AI-powered modeling tools to help cities integrate complex data sets (transportation, land use, environmental factors) to inform comprehensive decision-making, moving beyond traditional planning processes.
- Holistic Transportation Definition: Transportation is defined not just by vehicle movement, but by the movement of people and goods necessary for daily life (work, errands, services), acknowledging both physical modes (car, transit, walking) and emerging digital modes (remote work/communication).
- Quantifying Secondary Impacts: A major technical opportunity lies in using data analytics and modeling to quantify the often-unmeasured secondary and tertiary benefits (e.g., social, environmental) of infrastructure projects like public transit, pulling these metrics into the planning process.
3. Business/Investment Angle
- Innovation in Public Sector: There is a growing trend of state DOTs and cities actively seeking and funding innovation programs, signaling a shift away from slow, traditional planning toward incorporating modern data analytics.
- Financial Incentives for Sustainability: Progress is accelerated when sustainable options become financially advantageous (low or zero “green premium”). Innovation should focus on driving down the cost of sustainable choices to incentivize behavioral change.
- Risk and Public Sector: Innovation in the public sector is inherently constrained by the duty to maintain quality and serve the public, meaning risk-taking must be managed carefully, unlike purely private sector innovation.
4. Notable Companies/People
- Josh Rands (TerraCity): Co-founder and CEO, driving AI-powered modeling for integrated urban planning.
- TerraCity: The company developing the AI tools, named to reflect the necessary cohesion between the Terra (Earth/Environment) and the City (Urbanism).
- Colorado Department of Transportation (CDOT): Mentioned as an example of a public agency funding innovation programs, specifically looking at AI for first-last-mile access to new rail systems.
- RethinkX (Adam Do, Richard Gale): Mentioned in context regarding transformative change driven by cheaper, superior solutions creating financial incentives for behavioral shifts.
5. Future Implications
The future of cities hinges on successfully integrating environmental health with urban prosperity. This requires a shift from planning around single modes (like the car) to holistic, data-informed planning that accounts for land use, environmental impact, and community well-being. The successful application of AI in modeling these complex, multi-layered systems will be crucial for maximizing public investment returns and achieving long-term sustainability goals.
6. Target Audience
This episode is highly valuable for Urban Planners, Municipal Leaders, Transportation Engineers, Public Sector Technology Implementers, and Investors focused on Smart Cities, Urban Tech, and ESG/Sustainability initiatives within the built environment.
🏢 Companies Mentioned
💬 Key Insights
"What's really cool what you can do after you've trained that model to match those inputs to those outputs is you can then pull it out of this training system, put it somewhere else, and tweak the city. So you can add new bus lines, you can add new developments, you could change housing, you could add new commercial districts, you can change the environment in which the model is deployed based on all the information it's learned from observed data..."
"We try to quantify all these things as best we can and then look at real-world observed data. So what was the ridership of this bus line? What was the ridership of this train? How many people drove across this street? And then we use machine learning with all these different inputs and the actual observed data that people for things that people did, and we ask the model, hey, can you figure out how all these different inputs influence decision-making?"
"AI and all the progress that's being made in the tech sector, I think this is a really great application, and something that I wish I saw more people doing. So I see it as an opportunity to take this amazing technology that so much money is going into, which is AI, and try to apply it to city planning."
"To me, that's a huge opportunity because if we can start to quantify these things, then we can start to pull them into our planning process, and we can actually use that to inform decision-making and actually try and have numbers and data behind all the decisions we make."
"part of that is because the benefits span beyond just Starbucks revenue. When I think about opportunities, something we're doing at Tera City is using data analytics and modeling to try and quantify all of these different secondary, tertiary impacts and benefits of systems like transit."
"looking at how we can use artificial intelligence to help improve first-last-mile access to their planned front-range passenger rail system."