Trustworthy Decentralized Autonomous Machines: A New Paradigm in Automation Economy

• URL: http://arxiv.org/abs/2504.15676v1
• Date: Tue, 22 Apr 2025 07:59:46 GMT
• Title: Trustworthy Decentralized Autonomous Machines: A New Paradigm in Automation Economy
• Authors: Fernando Castillo, Oscar Castillo, Eduardo Brito, Simon Espinola,
• Abstract summary: Decentralized Autonomous Machines (DAMs) are capable of managing both digital and physical assets.<n>We argue that DAMs are pivotal in transitioning from trust-based to trustless economic models.<n>The integration of AI-driven decision-making, IoT-enabled operational autonomy, and blockchain-based governance allows DAMs to decentralize ownership, optimize resource allocation, and democratize access to economic opportunities.
• Score: 45.55770948876387
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Decentralized Autonomous Machines (DAMs) represent a transformative paradigm in automation economy, integrating artificial intelligence (AI), blockchain technology, and Internet of Things (IoT) devices to create self-governing economic agents participating in Decentralized Physical Infrastructure Networks (DePIN). Capable of managing both digital and physical assets and unlike traditional Decentralized Autonomous Organizations (DAOs), DAMs extend autonomy into the physical world, enabling trustless systems for Real and Digital World Assets (RDWAs). In this paper, we explore the technological foundations, and challenges of DAMs and argue that DAMs are pivotal in transitioning from trust-based to trustless economic models, offering scalable, transparent, and equitable solutions for asset management. The integration of AI-driven decision-making, IoT-enabled operational autonomy, and blockchain-based governance allows DAMs to decentralize ownership, optimize resource allocation, and democratize access to economic opportunities. Therefore, in this research, we highlight the potential of DAMs to address inefficiencies in centralized systems, reduce wealth disparities, and foster a post-labor economy.

Related papers

• PromptChain: A Decentralized Web3 Architecture for Managing AI Prompts as Digital Assets [0.0]
  We present PromptChain, a decentralized Web3 architecture that establishes AI prompts as first-class digital assets with verifiable ownership, version control, and monetization capabilities.<n>Our design includes: (1) a comprehensive metadata schema for cross-model compatibility, (2) a stake-weighted validation mechanism to align incentives, and (3) a token economy that rewards contributors proportionally to their impact.
  arXiv  Detail & Related papers  (2025-07-13T11:10:39Z)
• Zero-Trust Foundation Models: A New Paradigm for Secure and Collaborative Artificial Intelligence for Internet of Things [61.43014629640404]
  Zero-Trust Foundation Models (ZTFMs) embed zero-trust security principles into the lifecycle of foundation models (FMs) for Internet of Things (IoT) systems.<n>ZTFMs can enable secure, privacy-preserving AI across distributed, heterogeneous, and potentially adversarial IoT environments.
  arXiv  Detail & Related papers  (2025-05-26T06:44:31Z)
• Confidence-Regulated Generative Diffusion Models for Reliable AI Agent Migration in Vehicular Metaverses [55.70043755630583]
  vehicular AI agents are endowed with environment perception, decision-making, and action execution capabilities.<n>We propose a reliable vehicular AI agent migration framework, achieving reliable dynamic migration and efficient resource scheduling.<n>We develop a Confidence-regulated Generative Diffusion Model (CGDM) to efficiently generate AI agent migration decisions.
  arXiv  Detail & Related papers  (2025-05-19T05:04:48Z)
• Trustless Autonomy: Understanding Motivations, Benefits and Governance Dilemma in Self-Sovereign Decentralized AI Agents [14.287042083260204]
  Recent trend of self-sovereign Decentralized AI Agents (DeAgents) combines Large Language Model (LLM)-based AI agents with decentralization technologies such as blockchain smart contracts and trusted execution environments (TEEs)<n>DeAgent eliminates centralized control and reduces human intervention, addressing key trust concerns inherent in centralized AI systems.<n>This study addresses this empirical research gap through interviews with DeAgents stakeholders-experts, founders, and developers-to examine their motivations, benefits, and governance dilemmas.
  arXiv  Detail & Related papers  (2025-05-14T19:42:43Z)
• Generative AI for Autonomous Driving: Frontiers and Opportunities [145.6465312554513]
  This survey delivers a comprehensive synthesis of the emerging role of GenAI across the autonomous driving stack.<n>We begin by distilling the principles and trade-offs of modern generative modeling, encompassing VAEs, GANs, Diffusion Models, and Large Language Models.<n>We categorize practical applications, such as synthetic data generalization, end-to-end driving strategies, high-fidelity digital twin systems, smart transportation networks, and cross-domain transfer to embodied AI.
  arXiv  Detail & Related papers  (2025-05-13T17:59:20Z)
• Redefining Hybrid Blockchains: A Balanced Architecture [0.0]
  This paper introduces a novel hybrid blockchain architecture that balances scalability, governance, and decentralization. The findings highlight the system's scalability, security, and economic viability, offering a robust framework for enterprise and government adoption.
  arXiv  Detail & Related papers  (2025-04-26T16:25:24Z)
• Governing the Agent-to-Agent Economy of Trust via Progressive Decentralization [0.0]
  I propose a research agenda to address the question of agent-to-agent trust using AgentBound Tokens.<n>By staking ABTs as collateral for autonomous actions within an agent-to-agent network via a proof-of-stake mechanism, agents may be incentivized towards ethical behavior.
  arXiv  Detail & Related papers  (2025-01-28T00:50:35Z)
• Decentralized Governance of Autonomous AI Agents [0.0]
  ETHOS is a decentralized governance (DeGov) model leveraging Web3 technologies, including blockchain, smart contracts, and decentralized autonomous organizations (DAOs) It establishes a global registry for AI agents, enabling dynamic risk classification, proportional oversight, and automated compliance monitoring. By integrating philosophical principles of rationality, ethical grounding, and goal alignment, ETHOS aims to create a robust research agenda for promoting trust, transparency, and participatory governance.
  arXiv  Detail & Related papers  (2024-12-22T18:01:49Z)
• Beyond the Sum: Unlocking AI Agents Potential Through Market Forces [0.0]
  AI agents have the theoretical capacity to operate as independent economic actors within digital markets.<n>Existing digital infrastructure presents significant barriers to their participation.<n>We argue that addressing these infrastructure challenges represents a fundamental step toward enabling new forms of economic organization.
  arXiv  Detail & Related papers  (2024-12-19T09:40:40Z)
• Autonomous Building Cyber-Physical Systems Using Decentralized Autonomous Organizations, Digital Twins, and Large Language Model [0.0]
  This paper introduces a novel Decentralized Autonomous Building Cyber-Physical System framework. It integrates Decentralized Autonomous Organizations, Large Language Models, and digital twins to create a smart, self-managed, operational, and financially autonomous building infrastructure. An artificial intelligence assistant is developed to provide intuitive human-building interaction for blockchain and building operation management-related tasks.
  arXiv  Detail & Related papers  (2024-10-25T02:34:54Z)
• Decentralised Governance for Autonomous Cyber-Physical Systems [0.24578723416255752]
  This paper examines the potential for Cyber-Physical Systems to be governed in a decentralised manner. By highlighting the considerations and challenges of decentralised governance in managing autonomous physical spaces, the study reveals that autonomy in the governance of autonomous CPS is not merely a technological feat but also involves a complex mesh of functional and social dynamics.
  arXiv  Detail & Related papers  (2024-07-18T14:40:06Z)
• Decentralized Multimedia Data Sharing in IoV: A Learning-based Equilibrium of Supply and Demand [57.82021900505197]
  Internet of Vehicles (IoV) has great potential to transform transportation systems by enhancing road safety, reducing traffic congestion, and improving user experience through onboard infotainment applications. Decentralized data sharing can improve security, privacy, reliability, and facilitate infotainment data sharing in IoVs. We propose a decentralized data-sharing incentive mechanism based on multi-intelligent reinforcement learning to learn the supply-demand balance in markets.
  arXiv  Detail & Related papers  (2024-03-29T14:58:28Z)
• Computing Power and the Governance of Artificial Intelligence [51.967584623262674]
  Governments and companies have started to leverage compute as a means to govern AI. compute-based policies and technologies have the potential to assist in these areas, but there is significant variation in their readiness for implementation. naive or poorly scoped approaches to compute governance carry significant risks in areas like privacy, economic impacts, and centralization of power.
  arXiv  Detail & Related papers  (2024-02-13T21:10:21Z)
• Unpacking How Decentralized Autonomous Organizations (DAOs) Work in Practice [54.47385318258732]
  Decentralized Autonomous Organizations (DAOs) have emerged as a novel way to coordinate a group of entities towards a shared vision. In just a few years, over 4,000 DAOs have been launched in various domains, such as investment, education, health, and research. Despite such rapid growth and diversity, it is unclear how theses actually work in practice and to what extent they are effective in achieving their goals.
  arXiv  Detail & Related papers  (2023-04-17T01:30:03Z)
• Regulation conform DLT-operable payment adapter based on trustless - justified trust combined generalized state channels [77.34726150561087]
  Economy of Things (EoT) will be based on software agents running on peer-to-peer trustless networks. We give an overview of current solutions that differ in their fundamental values and technological possibilities. We propose to combine the strengths of the crypto based, decentralized trustless elements with established and well regulated means of payment.
  arXiv  Detail & Related papers  (2020-07-03T10:45:55Z)
• Graph Neural Networks for Decentralized Controllers [171.6642679604005]
  Dynamical systems comprised of autonomous agents arise in many relevant problems such as robotics, smart grids, or smart cities. Optimal centralized controllers are readily available but face limitations in terms of scalability and practical implementation. We propose a framework using graph neural networks (GNNs) to learn decentralized controllers from data.
  arXiv  Detail & Related papers  (2020-03-23T13:51:18Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.