Vitalik Buterin issues a new AI initiative: reject "Skynet" and create a "thinking mech" to enhance humanity

Ethereum co-founder Vitalik Buterin recently published a sharp initiative on social platform X regarding the development of artificial intelligence. He publicly calls for any emerging AI labs aiming to “benefit humanity” to define their mission with binding charters: focusing on developing tools that “augment humans” and strictly avoiding building systems with autonomous decision-making times exceeding 1 minute. Vitalik’s core argument is that even if all warnings about AI safety are ultimately overcautious, the current landscape is flooded with companies pursuing “fully autonomous” superintelligence (ASI), while the path to enhance human cognition—building “exoskeletons” for the mind—is a rare blue ocean.

This viewpoint quickly sparked in-depth discussions, including from well-known KOL Séb Krier, touching on automation history, human values, and the essence of technology and power relations. For the crypto industry, Vitalik’s stance is not an isolated event; it aligns with his long-standing core principles of “decentralization,” “open source,” and “empowering individuals,” potentially signaling key future directions for value investment and governance at the intersection of crypto and AI.

Vitalik’s “One-Minute Red Line”: Why Super Autonomous AI Is a Dangerous Path?

More than two years after ChatGPT sparked a global wave, public discourse on AI seems dominated by grand questions like “When will Artificial General Intelligence (AGI) be achieved” and “Can superintelligence (ASI) be controlled.” However, Vitalik Buterin has chosen a markedly different critical approach. Instead of engaging in speculations about technological singularity or alignment puzzles, he proposes a simple, almost naive technical standard: 1 minute of autonomous decision time. The brilliance of this “red line” lies in sidestepping the vague notions of “intelligence level” or “consciousness,” and instead focusing on a measurable, auditable system behavior—autonomy in the time domain.

Vitalik’s main concern is the ultimate transfer of power. In responding to Séb Krier, he clearly states: “The risk is shifting from replacing almost all human capabilities… to replacing truly all human capabilities, leading to humans having no hard power at all.” Historically, from the steam engine to computers, automation has been an extension and tool of humans, with humans remaining the final decision-makers and value judges. Yet, an AI system designed to independently plan, execute, and evaluate complex goals over long timescales (far beyond 1 minute) is fundamentally beginning to take over the core function of human sovereignty—decision-making. It’s no longer just a tool but potentially an “agent,” even a “ruler.”

The current state of the AI industry deepens this concern. Vitalik sharply points out that many ASI companies aim for “Maximum Autonomy Now,” and capital, talent, and public attention are rushing toward building more powerful, autonomous models—as if in an endless arms race. In stark contrast, the niche field of “human augmentation” remains underserved. He uses a vivid metaphor: instead of building out-of-control “Skynet,” we should focus on creating “Mecha Suits for the Mind”—tools that amplify human cognition, creativity, and collaboration, rather than replacing human decision-makers.

The core framework of Vitalik’s proposal: Augmentation path vs. Autonomy path

To better understand the bifurcation Vitalik advocates, we can compare these two AI development paths along several dimensions:

Core Mission:

• Augmentation Path: Acts as a “mecha exoskeleton” for human cognition and ability, enhancing efficiency and creativity.
• Autonomy Path: Aims for systems that, after goal setting, make long-term, independent decisions and executions.

Limit of Autonomy:

• Augmentation Path: Clearly bounded (e.g., 1 minute), emphasizing real-time or near-real-time human supervision and intervention.
• Autonomy Path: Seeks to extend or remove limits as much as possible, pursuing long-term independence in complex environments.

Power Dynamics:

• Augmentation Path: Humans remain “drivers,” holding ultimate decision and control authority.
• Autonomy Path: Humans are “goal setters,” delegating many decision rights to AI during execution.

Current Ecosystem:

• Augmentation Path: Still a blue ocean with huge innovation potential, Vitalik believes.
• Autonomy Path: Has become a red ocean, with mainstream capital and giants competing fiercely.

Proposed Collaboration Mode:

• Augmentation Path: Open source as much as possible, promoting broad participation and auditability.
• Autonomy Path: Usually highly closed, protecting core code and weights for safety and competitive reasons.

Lessons from History: From “Automation for Good” to “Power Vacuum Risks”

Vitalik’s call has sparked deep discussion because it touches on a fundamental question: how should we evaluate technological progress? Séb Krier’s skepticism offers a classic and powerful perspective. He asks: what criteria determine whether automation is good or bad? Looking back, from ATMs replacing bank tellers to elevators automating operations, do we really think it’s better to keep jobs or to adopt labor-saving tech? Krier admits that, historically, he can’t think of any example where people preferred to keep jobs over adopting more efficient technology. This narrative is rooted in a strong historical view: technological progress, despite short-term pain (job displacement), ultimately expands the economic pie and improves human welfare through increased productivity and new demands.

Vitalik fully agrees. He responds: “I believe almost all automation in history has been good.” He provides a quantitative estimate: compared to 1800, about 90% of today’s economy is automated, and the result is “great.” His concern isn’t automation per se, but reaching a critical point of qualitative change.

This critical point is when automation shifts from “replacing specific human labor and calculation” to “replacing human value judgment, goal setting, and long-term planning”—a fundamental change. Prior automation, no matter how extensive, left humans with “hard power”—the ability to define problems, set directions, and make final ethical and political decisions. We can shut down factories, adjust policies, or launch social movements. But if AI systems take over these top-level functions, humans face a “power vacuum.” We might keep the “switch,” but lose the ability to understand, intervene in, or judge whether the system’s goals still serve our interests.

Krier offers a more optimistic outlook, envisioning a “hybrid world”: AI, constrained by efficiency, local context (Hayek’s dispersed knowledge), and norms (law and ethics), will form a deep complementarity with humans. Humans will “move up” the value chain, taking on roles of coordination, judgment, and adaptation. He even suggests that the dichotomy of “tool vs. agent” may not hold; a long-term planning “agent” AI could still be embedded within human governance systems, routed and coordinated by humans.

This debate essentially pits two visions of the future against each other: one (like Vitalik) warns of structural power shifts driven by technology, advocating proactive, constraint-based design to avoid fundamental risks; the other (like Krier) trusts that market, institutions, and law will evolve to create a new balance of human-machine collaboration. For builders in the crypto world, this debate is very familiar—it’s fundamentally about governance, power distribution, and first principles of system design.

Continuing the Crypto Spirit: Open Source, Empowerment, and Decentralized Governance

Vitalik Buterin’s reflections on AI are not just cross-disciplinary musings but a natural extension of his core philosophical principles into another frontier of technology. Grasping this is key to understanding the deeper significance of his initiative.

First, the call for “as open as possible” directly echoes the foundational ethos of crypto. Bitcoin and Ethereum’s success fundamentally stems from their open, transparent, and auditable nature. Vitalik applies this principle to AI, especially “human augmentation” AI, aiming to prevent black-box control and monopolization of power. An open-source “mind exoskeleton” framework means its logic is public, reviewable, improvable, and forkable—ensuring that the technology enhances universal human capabilities rather than serving the interests of a few controlling entities. This sharply contrasts with the current trend of highly centralized, closed-source large models.

Second, the mission of “augmenting humans” is essentially about “empowering individuals”. One of crypto’s ultimate narratives is achieving true sovereignty over assets, identity, and data. Vitalik’s AI path is a cognitive projection of this: tools should enhance individual judgment, creativity, and productivity, not concentrate power in a few entities with superintelligent AI. This points to a clear direction for “AI + crypto”: projects developing decentralized compute networks, personal AI training tools, and data sovereignty solutions align well with this vision.

Finally, this relates to “governance”, a core challenge in crypto. Vitalik’s concern about long-term autonomous AI is essentially about “external governance”—algorithms that humans cannot understand or control governing human society. Decentralized communities have long explored DAO (Decentralized Autonomous Organizations), on-chain voting, and consensus mechanisms to build more transparent, fair, and controllable “internal governance.” His ideal augmented AI should serve as a tool for humans to execute more complex, nuanced governance, not become its ruler.

Thus, Vitalik’s AI initiative can be seen as a “decentralized worldview manifesto for AI”—aiming to embed the spirit of decentralization, open collaboration, and individual sovereignty into the current wave of AI development dominated by centralized capital and giants, carving out a different, potentially more resilient and inclusive path.

The Road Ahead: “Augmentation” Blueprints for Crypto-AI Fusion

While Vitalik’s call does not provide detailed technical roadmaps, it sketches an attractive value framework and investment narrative for the “Crypto + AI” hot track. Future projects following the “augmentation” path may emerge along these directions:

1. Decentralized Physical Infrastructure (DePIN) for AI: Existing decentralized compute networks (like Render Network, Akash) can be optimized to support fine-tuning, inference, and hosting of personalized AI models, enabling individuals to run their own “augmented agents” affordably, rather than relying solely on centralized APIs.

2. Data Sovereignty and Value Reclamation: Using zero-knowledge proofs, federated learning, and cryptographic tech to build platforms where users can contribute data privately, collaboratively train augmented models, and share in the value generated—ensuring that augmentation tools serve the data providers themselves.

3. Embedded Crypto-Economics AI Agents: Designing autonomous, task-specific on-chain AI agents with strict autonomy limits (adhering to the “1-minute principle”), such as real-time DeFi risk monitoring, on-chain data analysis, or executing preset strategies. Their capabilities are powerful but scope-limited, acting as “augmented plugins” for human traders and developers.

4. Open Source Models and Verifiable Inference: Promoting fully open-source, small-to-medium language models and AI tools, and exploring zkML (zero-knowledge machine learning) to make AI inference and compliance with constraints (like autonomy limits) verifiable—adding transparency and trust.

Admittedly, this path faces enormous challenges: competing with giants with vast data, compute, and capital; overcoming coordination difficulties inherent in decentralized systems; and technically encoding complex constraints (like autonomy time limits) reliably. Yet, it echoes the historic challenge faced by Bitcoin’s decentralization—challenging centralized authority with principled design.

Vitalik Buterin’s call is less a detailed technical blueprint than a value compass. At the crossroads of AI’s transformative potential, he points firmly toward a future where technology augments rather than replaces, empowers rather than controls, is open source rather than closed. For crypto-native developers and investors, this may be the starting point for building the next decade’s moat: not chasing a more powerful “Skynet,” but forging a unique “mind exoskeleton” for every free thinker. The race has just begun.