Autonomous robots may sound like sci-fi concepts that are decades away, but large-scale language models and generative AI are now allowing machines to plan, learn, and think. More than that – the same software that can win math olympics and write novels can also control physical robots, allowing a digital persona to function in both the digital and physical worlds. So yes, the robots walking around your neighborhood, or working next to you, will have consistent opinions and actions on X/Twitter, in prediction markets, and in the real world.
But there is a big gap. How do we integrate thinking machines into human society, from schools, hospitals, factories to our homes and everyday lives? Most of the systems we build are for other people and make strong assumptions that there are fingerprints, parents, and dates of birth, none of which are true for thinking machines. There is also widespread uncertainty about how to regulate thinking machines – do we ban them, pause their development, or try to limit their ability to synthesize emotions people understand (as in the European Union)? Which regional laws apply to a 200B parameter LLM running a computer in low earth orbit, controlling the actions of a trading bot, 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 people and computers to come together to vote and set rules, is immutable and public, and resilient. Fortunately, thousands of innovators and developers have spent the past 16 years building exactly that – a parallel framework for decentralized governance and finance. From the very beginning, the point is to support “non-geographic communities experimenting with new economic paradigms“by building a system that”doesn’t care who it’s talking to” (Satoshi 2/13/09). It’s now much clearer what this means – unlike other human-focused tech, financial, and regulatory stacks, blockchains and smart contracts don’t care whether they’re used by humans or computing machines. -thinking, and accommodating us all nicely. . For this reason, decentralized crypto networks offer the essential infrastructure necessary to allow this emerging sector to thrive. The benefits can be seen across healthcare, education and defence.
Many obstacles have to be overcome. Continuous human<>machine and machine<>machine collaboration is essential — especially in high-stakes 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 exchange (e.g. in robot taxis) will take place off-chain, for example in virtual private networks, but the steps leading to that, such as the detection of humans and robots that can drive you to the airport, is suitable for decentralized markets and actions. Scaling solutions like Optimism will be critical to accommodate these transactions and traffic.
Fragmented regulations around the world are another factor slowing down 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 programmable, blockchain-based rule sets that deliver much-needed uniformity. Creating global standards for safety, ethics and operations is critical for ensuring that autonomous robots can be rolled out across boundaries at scale, without compromising safety or compliance.
Decentralized autonomous organizations, otherwise known as DAOs, help accelerate research and development in robotics and AI. Traditional sources of funding are both slow and siloed, holding the industry back. Token-based models such as the DeSci DAO platform remove these bottlenecks, while giving everyday investors potential incentives to participate. Also, some of the emerging business models for AI involve micropayments and revenue sharing with data or model providers, which can be accommodated by smart contracts.
Combined, these advantages will help fast-track the development of autonomous robots, which have so many compelling use cases.
A new paradigm for robotics and thinking machines
It’s easy to fear that cognition is a zero sum game, and that the widespread availability of intelligent machines will compete directly with humans. But the reality is that there is a severe shortage of well-educated people in education, health care, and many other sectors.
UNESCO research recently revealed a global teacher shortage that there is an “urgent need for 44 million primary and secondary teachers worldwide by 2030” — and that’s before you consider assistants offering one-to-one support in classrooms and help struggling students keep up with their peers. Autonomous robots can deliver huge benefits here, addressing significant shortages across the education sector. Imagine a child learning about a complex concept with a robot sitting next to them, to lead them to a new skill concept — strengthening their understanding of a subject while improving their social skills. We’re used to people teaching robots, and it’s a one way street, but that’s changing.
Meanwhile, warns the WHO of a “health workforce crisis.” There is a total shortage of 7.2 million professionals in 100 countries — and as the world faces an aging population, this gap is expected to reach 12.9 million by 2035. The industry faces shortages in critical areas such as of nursing, primary care, and allied health. This crisis affects the quality of care that patients receive and threatens the ability of health care professionals to do their jobs. From monitoring chronically ill patients, assisting with surgical procedures, to offering companionship for the elderly, autonomous robots can play an important role in easing nurses’ workloads and doctor. Without prompting, they can monitor supplies of drugs and equipment — ordering additional stock when needed. When you consider other use cases like transporting medical waste, cleaning treatment rooms and assisting in surgeries, it’s clear to see that robotics can drive greater productivity — and consistency. both – at a time when the healthcare sector needs it.
Autonomous systems are already transforming the defense sector, primarily involving swarms of drones and naval surface assets, and we’ve barely scratched the surface of the benefits that robotics can bring — performing tasks that might otherwise be unsafe or impossible for humans.
From prototypes to practical use
All of this may seem abstract and straight out of the 22nd century, but Ethereum is now used to store decisions and guardrail actions for AIs and robots, and as Coinbase reportedAI agents use crypto to transact among themselves.
The open and auditable structure of decentralized crypto networks allows robotics developers to securely share data, models, and achievements. This accelerates the transition of autonomous robots from prototypes to real-world applications, enabling their deployment in critical areas such as hospitals and schools faster than ever before. When you walk down the street with a humanoid robot, and people stop and ask – “Hey aren’t you scared” you can tell them – not me, because the laws governing the actions of this machine are public and not modifiable, and then you can give them a link to the address of the Ethereum contract where those rules are stored.
Decentralized ledgers can also act as coordination hubs, allowing robots in heterogeneous systems to find each other and coordinate without centralized intermediaries. It is conceptually similar to standard defense technology C3 (command, communication, and control), except that the infrastructure is decentralized and public. Immutable records ensure that every exchange and action is traceable, creating a trusted foundation for collaboration.
For robot-to-robot interactions, smart contracts streamline task allocation and resource sharing, enabling efficient coordination. In robot-to-human interactions, privacy-centric decentralized systems can secure sensitive data, such as biometric or medical information, fostering trust and accountability.
This new world can bring fear – what does it all mean for us? – but everyone reading this article has been working to make it a reality for nearly 2 decades now, by building the infrastructure that will handle the management, collaboration, communication, and coordination of humans with computing machines. thought.
