In interactions between robots, smart contracts can simplify task allocation and resource sharing, enabling efficient coordination.
Author: Jan Liphardt
Compiled by: Deep Tide TechFlow
The original author is Jan Liphardt, an associate professor in the Department of Bioengineering at Stanford University, who earned a Ph.D. from the University of Cambridge.
He is also the founder of OpenMind. OpenMind focuses on developing multi-agent open-source software aimed at making robots smarter and ensuring that humans can inspect and understand the decision-making processes of robots. He is also one of the main authors of the ERC-7777 standard, a protocol co-developed by OpenMind and Nethermind.io, designed to regulate the interactions in a society of human-robot collaboration.
Main text
Autonomous intelligent robots were once seen as an unreachable sci-fi concept, but now, large language models (LLMs) and Generative AI have equipped machines with the ability to plan, learn, and think. Moreover, these programs that can win math competitions and write novels can also control physical robots, allowing a digital character to seamlessly switch between the digital and physical worlds. Therefore, in the future, robots walking in your community or working alongside you will be able to exhibit consistent viewpoints and behaviors in X/Twitter, prediction markets, and real life.
However, we face an important challenge: how to integrate these intelligent machines into human society, from schools, hospitals, and factories to homes and daily life? Most existing systems are designed for humans and default to requiring fingerprints, parental information, and birth dates, which are clearly not applicable to intelligent machines. Additionally, there remains significant debate about how to regulate these machines—should we ban their development, pause their research, or restrict them from generating human-understandable emotions (as proposed by the EU)? More complex is the question of which region's laws should govern the behavior of a large language model with 200 billion parameters running on a computer in low Earth orbit and controlling a trading robot or a physical robot in an SEC office.
We urgently need a global system that can support financial transactions, allow humans and intelligent machines to vote together on rule-making, while ensuring immutability, transparency, and strong resilience. Fortunately, over the past 16 years, thousands of developers and innovators have built such a system—a parallel framework for decentralized governance and finance. From the beginning, the goal of blockchain has been to support 'non-geographic communities exploring new economic models' by creating a system that 'can interact with any user' (Satoshi, February 13, 2009). Today, this vision has become clearer—unlike other human-centered technologies, financial, and regulatory systems, blockchain and smart contracts can indiscriminately support both humans and intelligent machines. Therefore, decentralized cryptographic networks provide crucial infrastructure for this emerging field, and their benefits will be fully realized in areas such as healthcare, education, and defense.
Of course, there are still many obstacles to overcome in this process. Achieving seamless connectivity for human-machine collaboration and inter-machine collaboration is crucial, especially in high-risk areas such as transportation, manufacturing, and logistics. Smart contracts can help autonomous machines discover one another, communicate securely, and form teams to complete complex tasks. Low-latency data exchange (such as communication between robot taxis) may take place off-chain, for example through virtual private networks, but earlier steps, such as finding a robot or human that can take you to the airport, are very suitable for completion through decentralized markets and mechanisms. Scaling solutions like Optimism will be key to supporting these transactions and traffic.
Moreover, fragmented regulations around the world are a major barrier to innovation. While regions like Ontario are leading in the field of autonomous robots, most areas still lag far behind. Decentralized governance provides the much-needed standardization in this field by establishing a blockchain-based programmable rule set. Developing global standards for safety, ethics, and operation is crucial to ensuring that autonomous intelligent robots can be deployed on a large scale across countries without compromising safety and compliance.
Decentralized Autonomous Organizations (DAOs) are accelerating the research and development of robots and AI. Traditional funding channels are inefficient and relatively closed, limiting the rapid development of the industry. Token-based models (such as the DeSci DAO platform) break through these bottlenecks while providing ordinary investors with incentives to participate. Additionally, some emerging AI business models introduce micropayments and revenue-sharing mechanisms with data or model providers, all of which can be implemented through smart contracts.
These combined advantages will drive the rapid development of autonomous intelligent robots and bring many anticipated practical applications.
A new paradigm for robots and intelligent machines
Many may worry that the proliferation of intelligent machines will compete with humans, viewing cognition as a zero-sum game. However, the reality is that there is still a severe shortage of well-educated talent in various fields such as education and healthcare.
A study by UNESCO points out that the global teacher shortage is severe, stating that 'by 2030, an additional 44 million primary and secondary school teachers are needed globally'—this does not even include teaching assistants who provide one-on-one tutoring and help struggling students catch up. In this context, autonomous intelligent robots can bring tremendous advantages to the education sector, alleviating the crisis of teacher shortages. Imagine a child learning complex concepts through a nearby robot, which patiently guides them step by step to master new skills—not only deepening their understanding of the subject but also enhancing their social skills. We have been accustomed to humans teaching robots, but this one-way relationship is gradually changing.
Meanwhile, the World Health Organization (WHO) warns that the healthcare industry is facing a 'human resource crisis.' Currently, the medical systems in 100 countries worldwide are short of approximately 7.2 million professionals, a gap that is expected to widen to 12.9 million by 2035 due to the aging population. The shortage of talent is especially severe in nursing, primary care, and related health fields. This crisis not only affects the quality of care that patients receive but also threatens the efficiency of healthcare practitioners. In this context, autonomous intelligent robots can play an important role in several aspects, such as monitoring chronic disease patients, assisting in surgical procedures, and providing companionship services for the elderly. They can also automatically monitor drug and equipment inventories, replenishing them in a timely manner when needed. Furthermore, robots can significantly improve efficiency and consistency in tasks such as transporting medical waste, cleaning treatment rooms, and assisting in complex surgeries. In the current urgent need for increased productivity in the healthcare industry, robots are undoubtedly an important aid.
In the defense sector, the application of autonomous systems has already shown results, particularly in drone swarms and maritime combat assets. The potential of robots in performing high-risk tasks or tasks that humans cannot accomplish (such as disaster rescue or hazardous operations) is just beginning to be tapped.
From prototype to real-world application
These ideas may sound somewhat distant, like a science fiction plot from the 22nd century, but in reality, Ethereum has long been used to store the decision-making and action rules of AI and robots. According to Coinbase, AI agents have already begun to trade among themselves using cryptocurrency.
The openness and auditability of decentralized cryptographic networks provide a secure platform for robotics developers to share data, models, and technological breakthroughs. This mechanism significantly accelerates the transition of autonomous robots from prototypes to real-world applications, enabling them to be deployed more quickly in critical fields such as hospitals and schools. Imagine walking down the street with a humanoid robot, and a passerby might stop to ask you, 'Aren't you afraid?' You can confidently respond, 'No, I am not afraid because the behavioral rules of this machine are public and unchangeable.' Then, you might even provide them with a link to the Ethereum contract address that stores these rules.
Decentralized ledgers can also serve as coordination centers, allowing heterogeneous systems composed of different types of robots to find each other and collaborate without centralized intermediaries. This mechanism is conceptually similar to traditional defense C3 technologies (Command, Control, and Communication), but its infrastructure is decentralized and transparent. Immutable records ensure that every interaction and action can be tracked, establishing a trustworthy foundation for collaboration.
In interactions between robots, smart contracts can simplify task allocation and resource sharing, enabling efficient coordination. In human-robot interactions, privacy-focused decentralized systems can securely manage sensitive data, such as biometric information or medical records, thus enhancing user trust in data security while clarifying accountability.
This new world may raise some questions—what does all this mean for us?—but in fact, every reader of this article has been working towards this realization for nearly the past 20 years by building the infrastructure that can handle governance, collaboration, communication, and coordination between humans and intelligent machines.
Note: The views expressed in this article are solely those of the author and do not necessarily reflect the positions of CoinDesk, Inc. or its owners and affiliates.
