Build the Ecosystem, Not Just the Robot
In “Grasping the World,” from the October 2026 issue of Scientific American Magazine, author Adam Rogers highlights the immense challenge of creating an all-purpose robot that can operate in a world designed for humans.
While a robot can master a backflip by focusing on its own body mechanics, tasks like scrambling eggs, folding laundry, or handling grapes are far harder because they require the robot to navigate an infinitely variable external environment.
Google DeepMind is working to solve this through AI that generalizes skills across different tasks and robot bodies, yet even seemingly trivial human activities remain a hurdle—in one test, a robot successfully used a dustpan only 32 percent of the time.
We may be approaching the problem from the wrong direction.
Most household-robot research treats the environment as fixed. Because our houses are filled with objects designed over centuries to accommodate the human body—doorknobs, light switches, utensils, and tools—we assume the challenge is to build a robot smart enough to operate all this equipment.
Instead, we should work both sides of the problem: Don’t build robots that can function in our existing houses.
Start building houses that work with robots.
Consider something as simple as hanging a picture. A human installs screw eyes and wire on the frame, decides where the picture should go, handles a tiny hook and nail, pounds the nail into the wall, lifts the picture, catches the wire on the hook and straightens the frame.
Teaching a robot to perform all those operations would require considerable visual, tactile and manipulative ability.
But why should a robot hang a picture that way?
A robot-compatible wall might contain an invisible mounting grid. Picture frames could have standardized attachment systems. The robot merely places the picture against the desired portion of the wall; the mounting system grabs it and levels it.
An extremely difficult robotics problem has almost disappears—not because the robot became smarter, but because the environment cooperated.
The same principle applies throughout the house. We should not teach a robot to fold laundry. We should solve the clothing-cleaning-and-storage problem, perhaps designing clothing and storage systems that make folding unnecessary or do the folding themselves.
We should not teach a robot to load a dishwasher. We should solve the eating-vessel problem. Dishes might remain in an integrated cleaning-and-storage system. Inexpensive dishes might be fabricated ad hoc, and their material recycled afterward.
We should not teach a robot to climb a ladder and replace a roof shingle. We should design roofs with standardized, machine-accessible, self-replacing modules.
We should not teach a robot to shovel snow. The objective is to keep necessary outdoor surfaces usable after snowfall. Snow shoveling is merely the historical human solution to that problem.
This suggests a fundamental rule: Don’t automate the task. Identify the task’s purpose, then redesign the system to accomplish it.
That changes the meaning of the “smart house.” Today a smart house generally means a conventional house with added intelligence: thermostats, lights, locks, cameras and appliances that communicate electronically.
The house we are describing would be fundamentally different. Its physical architecture would be designed from the beginning for cooperation among humans, stationary machinery and mobile robots.
And the concept would extend far beyond the house.
Consider food. The objective “prepare dinner” conceals an enormous chain of activities. Menus must be selected. Recipes must be developed. Ingredients must be inventoried, ordered and paid for. Food must be delivered, accepted, stored, retrieved, prepared, cooked and served. Leftovers must be stored. Eating utensils and vessels must be cleaned or recycled. Waste must be processed.
Every link could be redesigned. Why should groceries arrive in bags designed for human hands? Why should a refrigerator consist of shelves behind a large door? Why should mustard come in a jar that a robot must grasp, open, manipulate, close and replace? Why should a delivery person leave packages on a porch designed around a human opening a front door?
The robot-compatible house eventually implies the robot-compatible store, warehouse, delivery vehicle, package, food container and waste system.
The same would be true of the duties we now assign to a maid, cook, handyman, gardener and butler. Instead of reproducing their physical actions, identify their objectives: keep the house clean; provide meals; maintain the structure; maintain the grounds; manage goods entering and leaving the household. Then design the entire system around achieving those objectives.
This immediately creates a chicken-and-egg problem. Why would a food manufacturer produce robot-compatible containers when few houses can use them? Why would builders install robotic maintenance systems when few suitable robots exist? Why would robot manufacturers design for interfaces that houses don’t yet have?
There probably can be no master plan. The possibilities and their collateral effects are too numerous. We likely will slink into the robot ecosystem.
The first innovations will be things useful even without sophisticated robots: standardized machine-readable packaging, automated package receivers, modular plumbing, self-diagnosing appliances, machine-accessible service spaces, improved household sensors and standardized attachment systems. Older houses will acquire adapters. New houses will incorporate successful ideas directly.
Manufacturers will discover that one innovation makes another profitable. Competing systems will appear; some will disappear; standards gradually will emerge.
The automobile developed much the same way. The automobile brought roads, garages, gasoline stations, parking lots, traffic lights, repair shops, insurance systems, and now, charging stations. Society didn’t merely invent the car; over decades it created an automobile ecosystem.
Household robotics may follow the same path. This is where AI may have another, even more important, role. AI needs not merely to control the household robot. It can help design the ecosystem.
Change the food container, and you may affect manufacturing, shipping, retailing, refrigeration, robotic manipulation, household storage, cooking and recycling. Change the wall system, and you affect construction, electrical wiring, plumbing, decoration, repair and robotic access.
Each solution produces collateral problems and opportunities elsewhere.
The number of interactions approaches what we call Universal Engineering: Don’t merely ask whether a proposed solution works. Ask: If we do this, what happens to everything else?
Ultimately, we may discover that the household robot itself was the wrong unit of thought. A house could contain thousands of sensors reporting temperature, moisture, structural stress, electrical loads, water flow, food inventories and equipment condition.
Specialized machines could clean floors, handle food, maintain the grounds or inspect service spaces. A mobile general-purpose robot might perform only those tasks requiring mobility and manipulation. In that arrangement, asking where the robot ends and the house begins becomes increasingly arbitrary.
The house is part of the robot, and the robot is part of the house.
Rogers describes the extraordinary effort required to make a robot understand and manipulate the complicated world humans have created for themselves. We should continue that work—while also making the world easier for robots to understand and manipulate.
Biology offers an interesting precedent. Organisms did not evolve independently and then get dropped into an unrelated environment. Organisms and environments changed together.
Robotics eventually must do something similar. The objective shouldn’t merely be: “Build the perfect robot.” It should be: Build an ecosystem in which robots work.
That last distinction—task versus purpose—is one of the idea’s strongest parts. It prevents us from spending enormous effort teaching machines to reproduce human methods that exist only because of the peculiarities of human bodies and human history.
Finally, we focused on the house. But the same thinking can apply to the office, and to some degree, already has applied to manufacturing, which actually provides the proof of concept for the whole idea.
Factories long ago recognized that forcing a robot to replicate human movements in a traditional workspace is inefficient and unnecessarily complex. Instead, factories evolved to meet automation halfway by redesigning the environment to cooperate with the technology.
By implementing assembly lines, standardized parts, fixed-position jigs, conveyors, and machine-readable identifiers, manufacturers transformed the factory floor into an integrated system where the infrastructure itself facilitates robotic performance.
The office is somewhere in between. We still design offices largely for human bodies—desks, keyboards, screens, filing systems, meeting rooms—but the information environment already is being redesigned for machines.
Electronic documents eliminated much physical filing. Databases eliminated countless searches through cabinets. Email changed message delivery. Calendars, accounting systems, workflow software and AI increasingly allow information to move directly from machine to machine without somebody physically carrying or retyping it. Electronic meeting systems have replaced meeting rooms.
Offices have begun to focus on the overall goal, which may not require people to travel to a central location. That is why “work-from-home” and the equipment that enables it have gained some traction.
For generations, we implicitly defined “work” as something like: travel to a building, sit at an assigned location for eight hours, interact with coworkers there, then travel home. Once that became customary, we designed an enormous supporting system around it—office towers, desks, elevators, parking garages, commuter trains, highways, downtown restaurants, business clothing, and so forth.
But none of those is the objective. The objective is to produce the work.
As communications technology became better, we asked the equivalent of our dustpan question: Why are we transporting the worker? For many jobs, what really needs to move is information.
So instead of making transportation more efficient—better highways, faster trains, larger parking garages—some businesses have eliminated the transportation task altogether. Computers, broadband, video conferencing, shared documents, cloud storage, electronic signatures and collaborative software constitute the environmental redesign that makes that possible.
Of course, some work benefits from physical proximity, and some requires it. But that simply means the system should distinguish between activities whose purpose requires colocation and activities for which colocation was merely the traditional method.
That gives us an even more general Universal Engineering rule. Don’t begin by asking how to perform an existing task more efficiently. First ask why the task exists. Sometimes the best robot won’t be one that has learned how to use the dustpan. Sometimes the best solution is no dustpan. And sometimes the best commute is no commute.
Our principle isn’t really about houses, offices or even robots. It is much broader. When automating a human activity, don’t design a machine that only can operate in the existing environment. Redesign the environment, the tools, the objects and the process together with the machine.
Factories are farthest along because they are controlled environments, and economic incentives for automation are enormous. Offices are undergoing the same transformation primarily in their informational architecture. Homes lag because they are extraordinarily diverse, cluttered, personal and filled with objects inherited from generations of human-centered design.
Hospitals would be another fascinating example. So would hotels, restaurants, warehouses, farms, construction sites, airports and stores. A hospital designed simultaneously with its robots might look very different from a present hospital into which robots subsequently are introduced.
And eventually the idea extends to the city. Sidewalks, curbs, doors, elevators, delivery points, garbage collection, traffic systems and buildings could acquire standardized machine interfaces.
So even “Build an ecosystem in which robots work” is slightly too narrow. The larger engineering principle might be, “Don’t adapt the machine to the system. Identify the goal; then design the machine and the system together to reach that goal.”
That would require diverse industries to work together, rather than each trying to solve disparate problems.
That is the Universal Engineering principle.
Rodger Malcolm Mitchell
