Intuition 백서 전문

ms like IPFS, Filecoin, and Arweave, participants are rewarded for contributing storage resources and maintaining data over time. For example, in Filecoin, storage providers earn FIL tokens for storing and retrieving data. The economic model encourages providers to oﬀer reliable and secure storage services, as their ﬁnancial rewards depend on their performance and reputation within the network. This incentivization model creates a robust and resilient storage system that is decentralized and free from single points of failure. The relationship between trustless economic incentives and decentralized systems is intrinsically symbiotic. While trustless consensus, execution, and storage are reliant on trustless economic incentives, these mecha- nisms are conversely necessary for the creation, upkeep, and transaction of trustless economic rewards. These mechanisms enable the existence and transaction of ‘provably scarce digital assets’ for the ﬁrst time in his- tory, allowing decentralized assets to maintain signiﬁcant economic value, as exempliﬁed by cryptocurrencies like Bitcoin and Ether. Without these mechanisms, the properties that make these assets valuable would be compromised, reducing the incentives for participation. When viewed holistically, these foundational elements—decentralized identiﬁers, PKI proliferation, trustless consensus, trustless execution, trustless storage, and trustless economic incentives—enable society to transi- tion towards increasingly objective trust systems. However, as the rest of this paper will outline, building a comprehensive trust stack necessitates addressing a broader scope of issues. The following sections will 16 delve into how Intuition aims to solve these challenges, creating a robust and resilient framework for the decentralized web. 2.6.4 The Role of Social Consensus in Blockchain Systems A critical aspect not often mentioned in discussions about trustless systems is the role of social consensus. In the blockchain world, nearly everything, including the ‘trustless’ consensus mechanisms, ultimately relies on social consensus. At its core, even the most decentralized blockchain systems depend on the collective agreement of their participants. Consensus Mechanisms and Social T rust Consensus mechanisms, such as Proof of Work (PoW) and Proof of Stake (PoS), are foundational to blockchain security. These mechanisms enable decentralized net- works to agree on the state of the blockchain without relying on a central authority. However, the eﬀectiveness of these mechanisms hinges on the collective behavior and integrity of the network participants. Miners and validators must act in the best interest of the network, and the community must reach a social consensus on which blockchain protocol to follow and which upgrades to implement. For example, Bitcoin and Ethereum, the two largest blockchain networks, are secured by PoW and PoS respectively. Their resilience and security are testaments to the robustness of these consensus mechanisms. Despite being constantly attacked and scrutinized, they have maintained their integrity and uptime, show- casing the power of decentralized consensus. However, this resilience is also a result of the social consensus among the community of developers, miners, validators, and users who collectively work to uphold and improve the network. Intersubjective Fault T olerance Intersubjectivity refers to the shared understanding and agreement among multiple individuals, and can be likened to social consensus. It plays a crucial role in our daily lives as it forms the basis of social interactions, collective decision-making, and consensus building. Unlike purely objective facts that can be independently veriﬁed, intersubjective agreements depend on the collective perceptions, beliefs, and judgments of people. Eigenlayer’s introduction of the intersubjective work token, EIGEN, represents a signiﬁcant advancement in recognizing the limitations of purely deterministic and cryptographic veriﬁcation systems. While the blockchain conversation has largely been focused on the development of trustless, objective mechanisms (which are still, to some extent, reliant on social consensus, as outlined above), the EIGEN whitepaper acknowledges that numerous tasks and decisions require human judgment and social consensus. EIGEN highlights the critical role of social consensus in the decentralized web, emphasizing that many systems cannot be entirely ‘trustless’ . Instead, they require broad-based agreement among participants. This shift from purely objective veriﬁcation to incorporating human judgment is essential for handling complex, context-dependent scenarios that cannot be reduced to algorithmic determinations. Social Consensus Beyond T echnical Protocols The concept of social consensus extends beyond the conﬁnes of technical protocols and permeates society at large. In everyday life, intersubjective faults—errors in judgment due to misunderstandings, biases, or insuﬃcient information—are commonplace. These errors occur because our decisions are shaped by subjective perspectives, social interactions, and the lack of high- quality, relevant, and interpretable data. To address these faults, systems need to be developed that not only prevent them but also enhance society’s ability to tolerate and manage them when they do occur. The need for fault-preventative intersubjective consensus is particularly critical in the context of the de- centralized web, where it signiﬁcantly inﬂuences decisions and interactions, and where poor decisions can lead to catastrophic consequences. Choices regarding which platforms to use, which decentralized applica- tions (dApps) to trust, which protocol upgrades to implement, and which information sources to rely on are typically inﬂuenced by collective social agreements, informed heavily by social cues, endorsements, and reputations. For instance, the popularity and trustworthiness of a decentralized application are often established more through community endorsements and social proof than through purely technical merits. Inﬂuencers, devel- opers, and early adopters play pivotal roles in building trust and driving adoption. Therefore, users must place a signiﬁcant degree of trust in these individuals and communities, despite the decentralized web’s foundational aim to minimize the need for trust. This reliance highlights the importance of developing ro- bust systems that can support and enhance social consensus, ensuring that collective decision-making in the decentralized web is as reliable and informed as possible. 17 2.7 Trustless Code vs T rustful Interaction As we can see, the promise of a decentralized web is enticing, but the reality of interacting within this ecosystem can still be daunting and fraught with risk. Despite the maturation of the foundational layers of trustless technology, users continue to face signiﬁcant challenges and trust assumptions when navigating Web3. For example - a typical user’s journey in Web3 begins with setting up and managing a wallet. This process involves several trust assumptions, such as ensuring the software installation is from a legitimate source, securely storing private keys or seed phrases, and trusting the integrity of the wallet software. Risks such as phishing, human error, and software vulnerabilities pose signiﬁcant threats. Fake wallet applications and websites can steal users’ private keys, while misplacing a seed phrase or falling victim to social engineering attacks can result in the loss of all assets. Additionally, vulnerabilities in wallet software can be exploited by hackers to steal funds, underscoring the necessity for users to trust the software developers and their security practices. When interacting with decentralized applications (dApps), users must trust the security of smart contracts and the respective chain(s) they live on, navigate to the correct URLs, and rely on the integrity of oracles that fetch oﬀ-chain data. The risks include, but are not limited to, smart contract exploits, phishing attacks, and oracle manipulation. Bugs or vulnerabilities in smart contracts can lead to signiﬁcant ﬁnancial losses, while users can be tricked into interacting with fake dApps designed to steal their funds. Malicious or faulty oracles can provide incorrect data, leading to unintended consequences in smart contract execution. Navigating ecosystem information adds another layer of complexity. Users rely on information from various sources, such as social media, forums, and inﬂuencers, to make informed decisions. They must trust the accuracy of this information, the validity of reviews and endorsements, and the reliability of reputation systems. Misinformation, review manipulation, and reputation abuse can mislead users, resulting in poor decision-making and potential losses. With this, despite the trustless infrastructure provided by blockchain technology, users must still place signiﬁcant trust in people. Expecting every user to meticulously read and understand every line of code and every concept they interact with is unrealistic and impractical. Instead, users must trust that developers have written secure and reliable code and rely on the intersubjective consensus of their trusted communities to vet the things they interact with. This reliance on human trust means that, for the foreseeable future, the decentralized web must still be underpinned by traditional subjective trust mechanisms. 2.8 The T rust Paradox of ‘T rustless’ Systems As exempliﬁed, despite the advancements in decentralized platforms aimed at reshaping digital trust, a paradox remains at the core of these systems: while decentralized technologies strive to transition the world away from subjective trust systems and towards more ‘objective’ trust systems (AKA ‘trustless’ systems), the decentralized web still fundamentally relies on human behaviors and decision-making. Paradoxically, because the lower levels of the stack are trustless, we often require much stronger subjective trust—since if something goes wrong, the results can be catastrophic, with no method for reversing transactions or paths to recourse. This inherent paradox creates a nuanced and complex trust landscape that remains largely unaddressed. Although the promise of these technologies is to enable direct peer-to-peer interactions, theoretically elimi- nating the need for third-party intermediaries, the reality is more complex. The eﬀective functioning of these platforms still heavily relies on human factors, including the integrity of developers, the behavior of network participants, and the community’s ability to reach consensus on key issues. This interplay between technology and human elements highlights the limitations of achieving a fully trustless environment. While Web3 technologies enable the migration to less subjective trust systems, they do not completely eradicate the necessity for trust. Users still need to trust that they are interacting with the ‘right’ things, that smart contracts are coded correctly, that oracles provide accurate data, that the community will act in the network’s best interest, and so forth. As such, achieving a more ‘trustful’ stack is a complex endeavor that requires innovative solutions to navigate the intricate challenges of establishing and maintaining digital trust in a decentralized environment. 18 2.9 The T rustful Interaction Layer To address the limitations and complexities identiﬁed in achieving a trustful decentralized environment, Intuition’s primary focus is the conceptualization and implementation of a ‘trust ful interaction layer’ . While the trustless backbone of decentralized systems provides a robust foundation, these alone are insuﬃcient for creating a secure and user-friendly ecosystem. The current landscape still presents signiﬁcant challenges in ensuring trustful interactions for users navigating Web3. Therefore, the next step involves developing a trustful interaction layer that addresses these issues more comprehensively. This trustful interaction layer seeks to bridge the gap between trustless protocols and the practical needs of users by combining the strengths of decentralized technologies with mechanisms that enhance user trust and safety. By integrating trust-enhancing features and facilitating more informed interactions, we can create a decentralized environment that not only preserves the core principles of Web3 but also ensures a more reliable and secure user experience. 2.9.1 The Spectrum of Approaches To eﬀectively construct a trustful interaction layer, it is essential to examine the spectrum of potential approaches, ranging from entirely centralized to entirely decentralized systems. Centralized Gatekeepers: The Extreme of Centralization At one extreme of the spectrum lies the entirely centralized approach, reminiscent of the early days of the internet and exempliﬁed by platforms like AOL. In this model, centralized gatekeepers exert signiﬁcant control over the ecosystem, dictating who and what users can interact with. This approach oﬀers a curated and controlled user experience, theoretically ensuring security and trust by ﬁltering out malicious actors and content. However, it comes with severe drawbacks: • Centralized Power : Gatekeepers hold disproportionate power, potentially leading to censorship, data monopolies, and abuse of authority. This concentration of control is antithetical to the decen- tralization ethos, where power is distributed to avoid single points of failure and abuse. • Single Points of Failure : Centralized systems are vulnerable to attacks and failures, risking the security and accessibility of user data. • User Disempowerment : Users have limited control over their interactions and data, conﬂicting with the fundamental principles of decentralization. This centralized model, while oﬀering some degree of security and trust, stands in stark contrast to the values of the decentralized web, which aims to empower users and distribute control. Wisdom of the Crowds: The Extreme of Decentralization At the opposite end of the spectrum is the entirely decentralized approach, relying on the collective wisdom of the crowds. In this model, decisions and trust are established through widespread social interactions and user-generated content. This approach includes: • Personal Interactions: Engaging with peers directly, especially over calls, at conferences, and at events, to gather insights and recommendations. This method leverages personal trust networks but lacks scalability and can be geographically and temporally limited. • Social Media and Online Platforms: Scrolling through platforms like Twitter, Reddit, and others to gauge sentiment and gather opinions. While democratizing information dissemination, these platforms are rife with misinformation, echo chambers, and manipulation. • User Reviews and Ratings: Utilizing platforms like Yelp, Amazon, and Google Reviews to make informed decisions based on collective user feedback. Although useful, these reviews can be biased, manipulated, or overwhelmed by low-quality content. While this approach aligns with the ethos of decentralization and empowers individuals, it also has signiﬁcant limitations: • Information Overload: Users are inundated with vast amounts of unstructured data, making it diﬃcult to extract meaningful insights. The sheer volume of information can overwhelm users, leading to decision fatigue and analysis paralysis. 19 • Misinformation and Bias: User-generated content can be manipulated, biased, or inaccurate, leading to poor decision-making. The lack of veriﬁcation mechanisms can result in the spread of false information, undermining trust. • Lack of Structure: The decentralized nature of this approach lacks the necessary structure to eﬃciently ﬁlter and validate information. Without a coherent framework, it is challenging to establish reliable and consistent trust metrics. Finding Balance Building a trustful interaction layer requires a nuanced approach that transcends the binary choice between centralization and decentralization. By integrating the strengths of both models, we can create a system that is secure, user-friendly, and aligned with the core values of the decentralized web. This balanced approach will pave the way for a more robust and trustworthy digital ecosystem, enabling users to navigate Web3 with conﬁdence and ease. 2.9.2 The Role of Identity , Data, and Incentives in Creating a T rustful Interaction Layer Figure 4: The DIKW Pyramid, https://en.wikipedia.org/wiki/DIKW_pyramid In exploring our solutions to the Trust Paradox, our solution must fundamentally revolve around the intricate relationship between identity and data. In earlier sections, we explored how trust is established through data and its interpretation, and how identities serve as conceptual anchors for accumulating and correlating this data. To create a truly trustful interaction layer, we must bring these concepts full circle, recognizing that many of the challenges we face in the digital realm are essentially problems of identity and data management. Trust, both in the physical and digital worlds, is built upon familiarity, credibility, and reliability. In the digital realm, where direct interactions are replaced by data ﬂows and digital signals, the need for reliable identity models and comprehensive data becomes even more critical. These identity models, though imperfect, help us navigate the complexities of the digital ecosystem by providing a framework for understanding the entities we interact with. In this framework, identities must extend beyond personal identiﬁcation to encompass organizations, smart contracts, products, and even concepts. Each of these requires a robust identity model that can be anchored in veriﬁable data. This data, whether it comes from user-generated content, transactional records, or behavioral analytics, forms the backbone of trust in the digital landscape. The more data we have about an entity, the clearer our understanding and the higher our trust in that entity. Therefore, to create a ‘trustful interaction layer’, the focus must be on building technologies and systems that can continuously gather, validate, and present relevant data in a transparent and accessible manner. Intuition aims to address these challenges by providing a robust system for identity and data reﬁnement, expression, and management - giving entities better ‘intuition’ in all of their interactions. 3 Current Solutions In pursuit of a trustful interaction layer, leveraging and building upon the foundational work of numerous in- novators and technologists is essential. Intuition is constructed on these existing solutions, and by examining them, we can better appreciate the landscape of tools and protocols that Intuition leverages and enhances. 20 Here, we explore key concepts, oﬀerings, and advancements that can be leveraged in the development of a holistic trust stack, from identity veriﬁcation to data validation mechanisms. 3.1 The W eb of T rust When examining the intersection of identity and data, the ‘Web of Trust’ emerges as a pivotal concept, encompassing a range of ideas that remain relevant across various contexts. The core principles of a Web of Trust provide a framework for understanding how trust can be established and maintained in decentralized systems. The Web of Trust concept originated in the early 1990s as a decentralized model for public key authentication, primarily used in PGP (Pretty Good Privacy) encryption. Unlike traditional hierarchical systems where a central authority validates identities, the Web of Trust allows individuals to vouch for each other’s public keys. This decentralized approach to trust management ensures that no single entity has control, promoting a more resilient and user-empowered network. Expanding this concept to a broader range of interactions, in a Web of Trust, indivi