Autumn 2030: Rapid Recovery
The following speculative scenario is the final installment of four short stories developed by Autodesk Research in the office of the CTO. The scenario is the outcome of a project exploring how automation will shape the future landscape of our customer’s jobs, industries, and the nature of their work. The greater aim of this effort is to ensure that our nascent perspective on the Future of Work is made as relevant and tangible as possible, so that we can better understand how humans and machines can partner to achieve more than either could alone.
Research and development of this scenario conducted in collaboration with Jessy Escobedo. Illustrations by YimeIsGreat.
What’s the best way to do this? — That’s a relatively reasonable question to respond to when you have perhaps a large team of experts, great depths of background knowledge, and enough time to assess the options and develop a plan of action to execute. This is not often the case for Natasha Kohli and her small team (which also includes retrofit engineers, systems architects, and community data advocates) when they land on a construction site.
“We’ll ultimately end up with more workers in about another day or two, but it’s still not enough boots on the ground. And it’s definitely not enough when we first get to the site, but we make it work,” Kohli says this as if she’s trying to put us at ease, but I wonder if it’s more of an affirmation for herself.
Kohli works as a Nomadic Architect for an international government agency that aims to protect refugees and displaced communities, aiding in their integration or resettlement. Her job is to come in soon after a natural disaster has occurred like an earthquake, hurricane, or typhoon. “We typically get in right after the first responders,” she tells me. The ease with which Kohli describes the nature of her work makes it sound like it’s smooth, seamless. It’s not. Kohli’s composure is a testament to her character. She comes across as a quiet leader, preferring action to what she describes as ‘talking about talking.’ “I’ve been told I don’t really make a great first impression, that I can come across as being quite callous at times,” she adds with a laugh. I’ve witnessed none of these qualities so far. Granted we’ve only just met, and it’s about 72 hours into the aftermath of a catastrophic earthquake, with the threat of aftershocks still looming.
At this very moment, we’re in a remote town, nested somewhere along the Himalayan mountains. This is one of the poorest districts in the region, with a population of about 200,000. An initial assessment by a local government aid agency estimates that around 80–85% of the structures here have collapsed. A majority of the collapsed houses in these areas were brick and mud structures that had become weak with age. These were densely built neighborhoods with narrow streets. “Conditions like this make the process of rebuilding seem impossible at times, we can’t even think about construction until we manage the rubble,” says Kohli. It’s almost as if you can see her connecting the logistical dots in her head, trying to navigate complexity with compassion. Further out in the rural hamlets the roads become even less passable, we end up having to walk the final 1.5 miles because the destruction has made it impossible for large vehicles to continue on. Families in these areas have lost most of their grain stock, usually stored inside the house. Some are trying to dig through the rubble to salvage what they can.
Kohli and her team waste no time in assessing the landscape and configuring a course of action. It’s not yet apparent how extensive all the structural damage actually is, we only know of what we can see. Timing is everything here though, that much is obvious. “Things have changed pretty drastically in the 15 years I’ve been doing this work” says Kohli, as she walks over to the remnants of a house and starts moving aside rubble to clear a path forward. When Kohli first started working the field a few years out of college, in an attempt to escape a stagnant career in architecture, most of the assessments were still done manually. “Sometimes we’d have access to aerial imagery of the affected areas. That made it a little easier to know what was here before and what wasn’t. But that was only if a plane or helicopter could fly over. We were still starting from square one when it came to design and construction. And it sometimes felt like you were walking forward in a foggy stupor, like we never really knew what the best way forward was, but we had no choice except to just build. People needed shelter, they needed to get back to their lives. That part hasn’t changed, I guess.”
The way Kohli describes the process now sounds like it might be something out of a science fiction novel, well science fiction or Silicon Valley. As we continue to carefully make our way around the area, there’s a faint but familiar buzz in the air. “Drones?” I ask. We look up and there, about 20 feet above where we stand, is a small swarm of drones. “They’re getting a lay of the land, scanning the area. We’ll be able to use that information to generate an accurate digital model of the site. No more surveying with clipboards and tape measures.”
Delivery drones have now also begun to make their way over to this site with medical supplies and foldable shelter structures. “These were actually manufactured just over the border. A while back, a designer had devised a way to manufacture a boat/shelter. He publicly released the design code for it and for the virtual factory toolsets, so we’ve been able to repurpose the method regionally for factories here, which means we face fewer shortages and we’re not having to store them somewhere far away in anticipation of their use. Access to shelter is usually the most critical challenge following something like this, that and clean water,” Kohli tells me.
More efficient access to shelter modules and the benefit of a drone’s eye view isn’t the only thing that’s changed. One of the issues that made the process of construction so arduous was not knowing how to best build. “There was a lot guess work, and we’d ultimately just end up building more of the same because we just didn’t have enough resources, skills, labor. What we should’ve been doing was building better and stronger, not just faster.”
Kohli and her team now work through what’s called a Configurable Neighborhood Model. The model is more of a platform for remote collaboration. It’s linked to insights from construction projects around the world. “Think of it as an automated, shape-shifting version of SimCity. The model changes based on who’s accessing it, and what constraints and data inputs have been fed into the system, things like retrofitting needs, for example.” Kohli and her team use the model to help them devise a best possible solution scheme given local site conditions, existing construction methods, and material constraints. “The construction process is a lot faster if we’re able reuse some of the existing materials or work with local materials and manufacturing processes. The Configurable Neighborhood Model allows us to bring all of that into consideration. It feels pretty magical sometimes.”
With each hour I spend with Kohli and the rest of her team, I understand more and more that the “critical challenges” in this line of work are often more abundant than there are brains and bodies to help address them. “The co-bots are our friends…maybe don’t include that, it might sound disturbing to folks who aren’t here…who don’t understand,” Kohli says, as if unsure of herself. It’s the first time I’ve seen her second-guess something she’s said all day. The co-bots that Kohli is referring to are configurable micro-bots that can be deployed to remote areas to aid the clearing and construction process. The bots are hardy but agile. They’re able to navigate past road blocks and rubble that would stop a 4-wheel-drive dead in its tracks. Once they arrive on site, the bots can assemble into larger configurations depending on the task at hand. Sometimes this means clearing away rubble, other times it might be breaking down debris into raw material to be re-used for new construction. Such as crushing broken bricks to a clay-state that can be reformed for new builds.
The co-bots help to supplement some of the labor shortages as part of the rebuilding process in remote areas like this, but it’s still not enough help. “’Not enough’ feels like it’s my mantra most days. That phrase comes out of my mouth at least 5 times a day. Look, in places like this, in situations like this we most definitely will have a labor shortage. It’s expensive to transport, feed, and house 40–50 builders. What’s faster and cheaper is dropping in a couple hundred AR kits so that we can upskill local residents via virtual immersions.” Most of the residents in remote parts like this have been building their own homes for generations with the help of their neighbors. They know the fundamental principles of construction, sometimes they know better when it comes to how to leverage local materials or what parts of the land are prone to flooding for example. However, as new construction methods arise, promising more robust structures that can withstand stronger natural disasters, there is often a skills gap when it comes to the capabilities of local residents. “Training tools using AR help to close the gap between the knowledge they already have, and new methods of construction for more resilient structures. It’s a lighter touch way of addressing the labor shortage, and it’s worked well so far,” says Kohli.
We’ve started to make our way along the footpath again, back to the improvised headquarters structure at the base of the hill where I first met Natasha Kohli and her team earlier. In the darkness, you can hardly tell that something so catastrophic has just taken place. For a moment there is an eerie sense of calm around us. It can make one forget what lies behind, in front, and all around really. I can’t help but wonder that even with all the newness, the technology, the tools — what is the best way to move forward in a situation like this? Kohli pauses to look around before she gets in the car. Then as if she’s heard what I was thinking, and without hesitation she says, “We’ll make it work.”
// END
If you haven’t already, read “Winter 2030: A Metropolis in Transit” , “Spring 2030: Robot Trainers and Small Town Mayors”, and “Summer 2030: Microfactories as First Responders”
More on Autodesk.com
For more information on this project, please contact: Radha Mistry, radha.mistry@autodesk.com
