Autonomous robots may seem like science fiction concepts that are decades away, but large language models and generative AI now allow machines to plan, learn and think. More than that: the same software that can win the math Olympics and write novels can also control physical robots, allowing a digital person to operate in the digital and physical worlds. So yes, robots walking around your neighborhood or working alongside you will have consistent opinions and actions on X/Twitter, in prediction markets, and in the real world.
But there is an important gap. How do we integrate thinking machines into human society, from schools, hospitals, factories to our homes and daily lives? Most of the systems we have built are for other humans and make strong assumptions about having fingerprints, parents, and date of birth, none of which are true for thinking machines. There is also great uncertainty about how to regulate thinking machines: do we ban them, pause their development, or try to limit their ability to synthesize emotions intelligible to humans (as in the European Union)? What regional laws apply to a 200B parameter LLM running on a computer in low Earth orbit, controlling the actions of a trading robot or a physical robot in the New York SEC office on Pearl Street?
What is needed is a global system that supports financial transactions, allows humans and computers to come together to vote and set rules, is immutable and public, and is resilient. Fortunately, thousands of innovators and developers have spent the last 16 years building exactly that: a parallel framework for decentralized finance and governance. From the beginning the question was to support”Non-geographic communities experimenting with new economic paradigms.“by building a system that”He doesn’t care much who he talks to.(Satoshi 02/13/09). Now it’s clearer what that means: unlike the rest of human-centered financial and regulatory technology, blockchains and smart contracts don’t care much whether they’re used by humans or thinking machines, and they adapt elegantly to all of us. . For this reason, decentralized crypto networks offer the vital infrastructure needed to allow this burgeoning sector to flourish. The benefits will be tangible in healthcare, education and defense.
Several obstacles will need to be overcome. Seamless collaboration between human<>machine and machine<>machine is essential, especially in high-risk environments such as transportation, manufacturing and logistics. Smart contracts allow autonomous machines to discover each other, communicate securely, and form teams to complete complex tasks. Presumably, low-latency data sharing (for example, between robotaxis) will occur off-chain, for example in virtual private networks, but the steps leading up to this, such as the discovery of humans and robots capable of taking you to the airport , are very suitable for decentralized markets and stocks. Scalable solutions like Optimism will be critical to accommodating these transactions and traffic.
Fragmented regulations around the world are another factor holding back innovation. While some jurisdictions like Ontario are ahead of the curve when it comes to autonomous robotics, most are not. Decentralized governance addresses this by establishing blockchain-based programmable rule sets that provide much-needed uniformity. Creating global safety, ethics, and operations standards is critical to ensuring that autonomous robots can be deployed at scale across borders, without compromising safety or compliance.
Decentralized autonomous organizations, also known as DAOs, help accelerate research and development in robotics and artificial intelligence. Traditional funding sources are slow and isolated, holding the industry back. Token-based models, like the DeSci DAO platform, eliminate these bottlenecks while giving everyday investors potential incentives to get involved. Similarly, some of the business models under development for AI involve micropayments and revenue sharing with data or model providers, which can be adapted into smart contracts.
Combined, these advantages will help accelerate the development of autonomous robots, with a host of attractive use cases.
A new paradigm for robotics and thinking machines
It is easy to fear that cognition is a zero-sum game and that the widespread availability of intelligent machines will directly compete with humans. But the reality is that there is a serious shortage of well-educated people in education, healthcare and many other sectors.
Research by UNESCO recently revealed a global teacher shortage and that there is an “urgent need for 44 million primary and secondary teachers worldwide by 2030”, and that’s without considering assistants who offer personalized support in the classrooms and help struggling students keep up with their peers. Autonomous robots can offer enormous advantages in this regard, addressing a significant shortage across the education sector. Imagine that a child can learn about a complicated concept with a robot sitting next to them, to guide them through a new skill concept, reinforcing their understanding of a topic while also improving their social skills. We’re used to humans teaching robots, and this is a one-way street, but that’s changing.
Meanwhile, the WHO has warned of a “health workforce crisis.” There is a total shortfall of 7.2 million professionals across 100 countries, and as the world faces an aging population, this gap is expected to accelerate to 12.9 million by 2035. The industry faces shortages in critical areas such as nursing , primary care and related health services. . This crisis is affecting the quality of care patients receive and threatening the ability of healthcare professionals to do their jobs. From monitoring patients with chronic illnesses, assisting in surgical procedures to offering companionship to the elderly, autonomous robots can play a crucial role in easing the workload of nurses and doctors. Without being prompted, they can monitor supplies of medications and equipment and order additional stock when necessary. When you consider other use cases, such as transporting medical waste, cleaning treatment rooms, and assisting in surgeries, it is clear that robotics can drive greater productivity (and consistency) at a time when the industry of health you need it.
Autonomous systems are already reshaping the defense sector, primarily involving swarms of drones and surface naval assets, and we are barely scratching the surface when it comes to the advantages that robotics can bring: executing tasks that may be unsafe or impossible for the humans.
From prototypes to practical use
All of this may seem abstract and straight out of the 22nd century, but Ethereum is used today to store decision and action barriers for AI and robots, and as Coinbase reported, AI agents are using cryptocurrencies to transact with each other.
The open and auditable structure of decentralized crypto networks allows robotics developers to securely share data, models, and advancements. This accelerates the transition of autonomous robots from prototypes to real-world applications, allowing them to be deployed in critical areas such as hospitals and schools faster than ever. When you walk down the street with a humanoid robot and people stop and ask you, “Hey, aren’t you afraid?”, you can tell them: no, I’m not, because the laws that govern the actions of this machine are public and immutable rules, and then you can give them a link to the Ethereum contract address where those rules are stored.
Decentralized ledgers can also act as coordination centers, allowing robots in heterogeneous systems to find each other and coordinate without centralized intermediaries. This is conceptually similar to standard C3 (command, communication and control) defense technology, except that the infrastructure is decentralized and public. Immutable logs ensure that every exchange and action is traceable, creating a trusted foundation for collaboration.
For interactions between robots, smart contracts streamline task assignment and resource sharing, enabling efficient coordination. In robot-human interactions, privacy-focused decentralized systems can protect sensitive data, such as biometric or medical information, fostering trust and accountability.
This new world can provoke fear: what does it all mean for us? – but everyone reading this article has been working to make it a reality for nearly two decades, by building the infrastructure that will handle governance, team building, communication, and coordination of humans with thinking machines.
