OpenMind founder writes: From science fiction to reality, crypto will reshape a new era of human-machine collaboration
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OpenMind founder writes: From science fiction to reality, crypto will reshape a new era of human-machine collaboration
In interactions between robots, smart contracts can streamline task allocation and resource sharing, enabling efficient coordination.
Navigating Web3 tides with focused insightsAuthor: Jan Liphardt
Translation: TechFlow
The original author is Jan Liphardt, an associate professor in the Department of Bioengineering at Stanford University, who earned his Ph.D. from the University of Cambridge.
He is also the founder of OpenMind, which focuses on developing open-source multiagent software to make robots smarter while ensuring humans can inspect and understand robotic decision-making processes. He is one of the primary authors of the ERC-7777 standard—a protocol jointly developed by OpenMind and Nethermind.io aimed at defining interaction norms in a society where humans and robots collaborate.
Main Text
Autonomous intelligent robots were once seen as distant science fiction concepts. Today, large language models (LLMs) and generative AI have endowed machines with the ability to plan, learn, and reason. Moreover, software capable of winning math Olympiads or writing novels can now control physical robots, enabling digital entities to seamlessly operate across both digital and physical realms. In the future, robots walking through your neighborhood or working alongside you will exhibit consistent views and behaviors across X/Twitter, prediction markets, and real life.
However, we face a critical challenge: How do we integrate these intelligent machines into human society—from schools, hospitals, factories, homes, to daily life? Most existing systems are designed for humans and default to requiring fingerprints, parents, or birth dates—criteria clearly inapplicable to intelligent machines. Furthermore, significant controversy remains over how such machines should be regulated—should we ban their development, pause research, or restrict them from simulating human-understandable emotions (as proposed by the EU)? More complex still: if a 200-billion-parameter large language model runs on a computer in low Earth orbit and controls a trading bot or a physical robot inside the SEC office in New York, whose jurisdiction governs its behavior?
We urgently need a global system that supports financial transactions, enables joint voting by humans and intelligent machines to shape rules, and offers immutability, transparency, and strong resilience. Fortunately, over the past 16 years, thousands of developers and innovators have already built such a system—a parallel framework for decentralized governance and finance. From the start, blockchain’s goal has been to support “non-geographic communities exploring new economic models,” by building a system “that can interact with any user” (Satoshi, February 13, 2009). Today, this vision is clearer than ever: unlike other human-centric technologies, financial systems, and regulatory frameworks, blockchains and smart contracts can support both humans and intelligent machines equally. Thus, decentralized crypto networks provide essential infrastructure for this emerging domain, with benefits poised to manifest fully in healthcare, education, and defense.
Of course, many obstacles remain. Seamless connectivity between human-machine collaboration and machine-to-machine coordination is crucial, especially in high-risk areas like transportation, manufacturing, and logistics. Smart contracts can help autonomous machines discover each other, communicate securely, and form teams to accomplish complex tasks. Low-latency data exchange—such as communication between robotaxis—might occur off-chain via private networks, but prior steps like discovering available robots or humans to take you to the airport are ideal for decentralized markets and mechanisms. Scaling solutions like Optimism will be key to supporting these transactions and traffic flows.
In addition, fragmented regulations worldwide are major barriers to innovation. While regions like Ontario lead in autonomous robotics, most others lag far behind. Decentralized governance provides much-needed standardization through programmable rule sets built on blockchain. Establishing global standards for safety, ethics, and operations is vital to ensure autonomous intelligent robots can be deployed at scale across borders without compromising safety or compliance.
Decentralized Autonomous Organizations (DAOs) are accelerating robotics and AI R&D. Traditional funding channels are inefficient and relatively closed, limiting rapid industry growth. Token-based models—such as those on DeSci DAO platforms—overcome these bottlenecks while incentivizing broader investor participation. Additionally, emerging AI business models featuring micropayments and revenue-sharing with data or model providers can be implemented via smart contracts.
Together, these advantages will drive rapid advancement in autonomous intelligent robots and unlock numerous promising real-world applications.
A New Paradigm for Robots and Intelligent Machines
Many may fear widespread intelligent machines will compete with humans, viewing cognition as a zero-sum game. Yet reality shows severe shortages of skilled professionals in fields like education and healthcare.
A UNESCO study highlights the severity of the global teacher shortage: “By 2030, 44 million additional primary and secondary school teachers will be needed globally”—not even counting teaching assistants required to provide one-on-one tutoring or help struggling students catch up. In this context, autonomous intelligent robots offer tremendous potential to alleviate teacher shortages. Imagine a child learning complex concepts from a personal robot that patiently guides them step-by-step—deepening subject understanding while improving social skills. We’re used to humans teaching robots, but this one-way relationship is beginning to shift.
Meanwhile, the World Health Organization (WHO) warns of a “workforce crisis” in healthcare. Currently, around 100 countries face a shortfall of approximately 7.2 million health professionals. With aging populations, this gap is expected to grow to 12.9 million by 2035. Shortages are particularly acute in nursing, primary care, and allied health services. This crisis not only affects patient care quality but also burdens healthcare workers’ efficiency. Here, autonomous intelligent robots can play vital roles—monitoring chronic disease patients, assisting in surgeries, providing companionship for seniors, automatically tracking and replenishing medicine and equipment inventories, transporting medical waste, cleaning treatment rooms, and aiding complex surgical procedures—significantly boosting efficiency and consistency. As the healthcare sector urgently needs productivity gains, robots are undoubtedly powerful allies.
In defense, autonomous systems are already proving effective, particularly in drone swarms and maritime combat assets. The potential for robots in high-risk missions or tasks beyond human capability—such as disaster rescue or hazardous operations—is only beginning to be realized.
From Prototype to Real-World Use
This may sound like distant, 22nd-century science fiction, but Ethereum is already being used to store decision-making and behavioral rules for AIs and robots. And according to Coinbase, AI agents have already begun using cryptocurrency to transact with one another.
The openness and auditability of decentralized crypto networks provide robot developers with a secure platform to share data, models, and technical breakthroughs. This mechanism dramatically accelerates the transition of autonomous robots from prototypes to real-world deployment, enabling faster integration into critical sectors like hospitals and schools. Imagine walking down the street with a humanoid robot when someone stops you and asks, “Aren’t you afraid?” You could confidently reply, “No, I’m not afraid—because this machine’s behavioral rules are public and immutable.” Then, you could even show them a link to the Ethereum contract address storing those rules.
Decentralized ledgers can also serve as coordination hubs, allowing heterogeneous systems composed of different types of robots to discover each other and collaborate without centralized intermediaries. Conceptually similar to traditional defense C3 systems (command, control, and communications), this infrastructure is decentralized and transparent. Immutable records ensure every interaction and action is traceable, establishing a trustworthy foundation for collaboration.
In interactions among robots, smart contracts can streamline task allocation and resource sharing, enabling efficient coordination. In human-machine interactions, privacy-preserving decentralized systems can securely manage sensitive data—such as biometric information or medical records—enhancing user trust in data security while clearly assigning accountability.
This new world may raise questions—what does all this mean for us?—but in fact, every reader of this article has spent nearly two decades helping build the infrastructure needed to enable governance, collaboration, communication, and coordination between humans and intelligent machines.
Note: The views expressed in this article are those of the author and do not necessarily reflect the opinions of CoinDesk, Inc. or its owners and affiliates.
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