It is an exciting time to be a robot. They are becoming promptable, not programmed. They are stepping onto factory floors, into warehouses, restaurants, and homes. For sixty years, the answer to keeping us safe around robots was a cage: bolt the machine down, fence it off, keep people out. It worked because the robot was blind and repetitive. The cage kept the risk contained. Dangerous inside, safe outside. Today's robots can see, plan, and work on their own, alongside people. The prize is the largest market on earth: labor itself. But what replaces the cage? Every dangerous machine in the past, from the steam boiler to the elevator to the car, won its place the same way. Its risk became legible: measurable, comparable, priceable. Robot risk today is not legible. But a robot among people today must be compliant and insured from day one. Legibility takes instrumentation to measure, standards to compare, and insurance priced on evidence, turning as one circuit: evidence prices insurance, insurance feeds the standard, and the standard writes the next round of evidence. We call it the Evidence Loop. As a system, it has not started. What follows is our answer: the 17 things robot makers, deployers, insurers, and policymakers can do by 2030 to start the loop that replaces the cage. It is published open for review: we invite you to shape it and join its reviewers.
For sixty years, we knew exactly how to keep a robot safe. It came down to one simple idea: keep people out.
A robot used to wait for instructions. It worked because it was predictable, repetitive, and blind. Now imagine one deciding what happens next.
That assumption is now breaking. The robot is leaving the cage. AI is giving it the ability to see, plan, and act without a script or program for every move. every move.
These machines are moving into warehouses, restaurants, factories, and homes, working alongside the people the cage was built to keep away.
But what replaces the cage?
The machines that changed the world all faced a version of the same problem: how do you make something dangerous safe enough to use around people?
Every dangerous machine in the past, from the steam boiler to the elevator to the car, won its place the same way. Their risks became something people could inspect, compare, and eventually price.
Their risk became legible.
Robot risk isn't there yet.
A robot working around people has to be compliant and insured from day one. But a safety assessment can only tell you what was true when the robot was assessed.
It cannot tell you what happened after the machine went to work: how often it stopped, how often a person had to intervene, what changed after an update, or whether the same problem appeared across deployments.
That matters because insurers cannot price what they cannot measure. And without a history of real-world performance, every new deployment starts with uncertainty.
The missing piece is evidence: a record of what the robot actually did in service, measured in a way that different deployments can be compared.
Once that record exists, the pieces can start reinforcing one another.
It can help insurers price risk, give standards bodies better data, and give deployers a track record they can take to their next renewal.
We call this the Evidence Loop.
This article lays out 17 things robot makers, deployers, insurers, standards bodies, and policymakers can do by 2030 to start the loop that replaces the cage.
It is published open for review: we invite you to shape it and join its reviewers.