Intuition 백서 전문

eriﬁed by the community, enhancing its reliability. By leveraging the collective intelligence and vigilance of the decentralized ecosystem, Web3 wallets can provide a more secure and trustworthy environment for users. Beyond security, the integration of Intuition data can enrich the user experience by providing semantic context to transactions. Users could see labels and descriptions for tokens, contracts, and addresses based on community-generated data. For example, a token address could be accompanied by a description of the token’s purpose, the project behind it, and user reviews or ratings, without reliance on an intermediary such as Coingecko. This semantic enrichment makes the data more accessible and understandable, even for users who may not have deep technical knowledge. Furthermore, this enriched context can be personalized based on the user’s trust graph. By leveraging the trust relationships established within Intuition, wallets can prioritize information and recommendations from sources that the user personally trusts, creating a more tailored and relevant experience. 9.1.2 Developer T ooling Discoverability The rapid pace of innovation in the Web3 and blockchain space has led to a proliferation of developer tools, frameworks, and libraries. While this wealth of resources is a boon for developers, it also presents a signiﬁcant challenge: keeping track of the latest and most eﬀective tools is increasingly diﬃcult. The current ecosystem suﬀers from fragmentation, with many valuable tools going unnoticed or underutilized, leading to duplicated eﬀorts and ineﬃciencies. Intuition oﬀers a solution by leveraging the power of crowdsourced knowledge to create comprehensive, dynamic, and easily navigable lists of developer tools. With new tools and frameworks being released frequently, developers face the daunting task of staying updated and identifying the best resources for their needs. The decentralized nature of the Web3 space further complicates this, as information is scattered across various platforms and repositories. This fragmentation not only hampers productivity but also leads to the unintentional duplication of work, as developers may unknowingly create tools that already exist. Intuition tackles this problem by providing a platform for the community to collectively categorize, review, and endorse developer tools. By aggregating and organizing data through user contributions, Intuition en- 80 sures that valuable resources are easily discoverable, reducing the time and eﬀort developers spend searching for the right tools. Intuition enables users to tag and categorize developer tools based on their functionality, use cases, and other relevant criteria. When a developer organizes their own toolkit—by tagging a new library or framework as “smart contract development” or “Ethereum scaling solution”—this information is shared with the entire Intuition ecosystem. This crowdsourced approach ensures that the collective knowledge and experience of the developer community are harnessed to create a comprehensive and up-to-date repository of tools. For instance, a developer might discover a new tool that simpliﬁes the process of deploying smart contracts. By tagging and categorizing this tool within Intuition, they not only organize their own resources but also make this tool discoverable to others who might beneﬁt from it. This collaborative eﬀort helps prevent the duplication of work and encourages the adoption of the best available tools. Intuition’s decentralized and permissionless data lake allows for the creation of a dynamic and interconnected knowledge base. As more developers contribute to the platform, the repository of developer tools grows richer and more nuanced. Each tool’s entry can include detailed descriptions, user reviews, and endorsements from trusted community members, providing a holistic view of its capabilities and reliability. This interconnected knowledge base enables developers to quickly ﬁnd the tools they need, understand their use cases, and assess their quality based on community feedback. The ability to access this wealth of information in one place signiﬁcantly enhances the eﬃciency of the development process. Leveraging Intuition’s personalized trust graphs, developers can receive tailored recommendations based on their speciﬁc needs and preferences. By overlaying their trust graph onto the list of developer tools, they can prioritize recommendations and endorsements from individuals and organizations they trust. This personalized approach helps developers navigate the vast array of tools and focus on those most relevant to their projects. For example, if a developer trusts the recommendations of a well-known blockchain development team, they can see which tools this team endorses and uses. This not only streamlines the discovery process but also provides an additional layer of conﬁdence in the quality and reliability of the tools selected. 9.1.3 Delegate Reputation In the Web3 ecosystem, decentralized governance is highly prized, and the decision to delegate tokens or voting power plays a critical role in the success of decentralized projects. However, the current processes for vetting and selecting DAO (Decentralized Autonomous Organization) delegates are deeply ﬂawed. Despite the value placed on pseudonymity, control over multi-billion-dollar protocols is often handed to individuals who haven’t undergone proper vetting and may lack the necessary expertise. The typical vetting process is superﬁcial, relying on factors like usernames, proﬁle pictures, or brief bios, which fall far short of what’s needed. Users are expected to conduct their own thorough due diligence, which is impractical in a decentral- ized environment where individual stakes are usually too small to justify the eﬀort. Even when due diligence is performed, the data available is often unreliable, with falsiﬁed credentials being a common issue. Intuition oﬀers a solution by providing tools that enable the veriﬁcation of key information, such as who made speciﬁc claims about what, and at what time—for example, a university verifying that an individual graduated with a speciﬁc degree, or an employer conﬁrming that someone worked for them. Additionally, Intuition incentivizes community members to share more data points, helping to build a more comprehensive picture of an individual’s reputation within the ecosystem. The semantic structuring of this data allows users to easily navigate and ﬁlter through trust networks, or “trust circles,” within speciﬁc contexts. This means that users can view data, sentiment, and opinions ﬁltered through people they trust within relevant ﬁelds. For instance, users could identify which experts in a particular area endorse a speciﬁc delegate or staking operator. Contextual reputation is key here—knowing that an entity has a high general reputation is less valuable than understanding their reputation within the speciﬁc context of their role. For example, a delegate’s expertise in managing hardware and software operations is far more relevant to their role in a DAO than their reputation in unrelated areas like sports or entertainment. Furthermore, this system incentivizes delegates to act in the best interests of the protocol, as their actions directly impact their reputation within the Intuition system. A transparent, aggregated trust score, derived from the collective input of the Web3 community, provides a more accurate and holistic view of their capabil- 81 ities and track record. This reputation score can then be used as a credential, unlocking new opportunities and oﬀering tangible beneﬁts that may have previously been out of reach. 9.1.4 Credit Scores In the traditional ﬁnancial system, credit scores are pivotal for accessing ﬁnancial services, yet they often rely on limited, centralized data that doesn’t fully capture an individual’s ﬁnancial behavior or potential. This approach can exclude those without established credit histories, such as young adults or individuals in underserved regions, limiting their access to ﬁnancial opportunities. Intuition can revolutionize credit scoring by leveraging decentralized attestations and community-driven reputation systems. Here, creditworthiness is determined not just by traditional ﬁnancial data but also by a comprehensive array of attestations—both objective and subjective. These attestations provide deeper insights into an individual’s ﬁnancial behavior. For example, when someone borrows money, the lender can attest to their reliability, timeliness in repayment, and overall trustworthiness. These attestations, whether formal statements or subjective opinions, are recorded, timestamped, and integrated into the borrower’s decentralized credit proﬁle, creating a nuanced and dynamic credit score. One of the key innovations of Intuition is the ability to leverage this reputation as collateral. If Intuition is widely adopted and people invest signiﬁcant time and resources into building their reputations, these reputations themselves acquire tangible value. A strong reputation within the Intuition system could become a valuable asset that can be used to secure loans. Since the reputation is built on a foundation of community- validated attestations, any attempt to undermine it would need to outweigh the value of that reputation. This makes malicious attacks costly and impractical, further reinforcing the trust and reliability of the system. Imagine a scenario where, based on your Intuition reputation, you could borrow money with the assurance that the loan amount is less than the value of your reputation. The system inherently discourages default- ing, as the cost to one’s reputation—and the associated loss of future opportunities—would far exceed the beneﬁt of a short-term gain. This creates a powerful incentive for individuals to maintain and protect their reputations, knowing that their standing within the community holds real, tangible value. By focusing on decentralized attestations, subjective claims, and the intrinsic value of reputation, Intuition not only democratizes access to credit but also fosters a more secure and fair ﬁnancial ecosystem. This system empowers individuals to build, leverage, and protect their ﬁnancial identity, oﬀering a credit score that truly reﬂects their behavior, trustworthiness, and the conﬁdence others have in them. 9.2 Web2 Use Cases & Examples 9.2.1 Media & News In the current landscape of media, manipulation and misinformation are pervasive issues that undermine the integrity of public discourse. The rapid spread of misinformation and disinformation and the strategic use of propaganda tactics can signiﬁcantly distort public perception and decision-making. Intuition provides a framework to mitigate these challenges by enhancing transparency, accountability, and trustworthiness in information dissemination. One of the key features of Intuition is its ability to trace the provenance of data. Intuition ensures that the origin and history of information are transparent and veriﬁable. This transparency allows users to trace the source of information to its origin, determining its credibility and authenticity. By examining the history of data and users, individuals can evaluate the consistency and reliability of the sources over time. Transparency in data provenance helps identify alterations or misrepresentations, making it more diﬃcult for malicious actors to manipulate information without detection. Additionally, Intuition’s opt-in state interpretation mechanisms, such as the ability to toggle between Reality Tunnels, ensure that no one is locked into a single, manipulative echo chamber. This feature helps users discern trustworthy information from manipulative or false narratives, providing a more balanced perspective on the information they encounter. Intuition also enables a community-driven approach to fact-checking. Similar to ‘community notes’ on platforms like Twitter, but applicable to the entire internet, Intuition leverages the collective intelligence and expertise of its users. This community-driven model allows for real-time policing to ensure higher data quality and accuracy. 82 Consider the context of a major political election. In such a scenario, misinformation and propaganda can signiﬁcantly inﬂuence voter behavior. Intuition can help mitigate these eﬀects by providing a transparent and accountable information ecosystem. In Intuition, people can express their thoughts and opinions freely, without risk of censorship, bias, or manipulation. Political statements and campaign promises can be recorded on Intuition, with their origins and subsequent modiﬁcations transparently documented. Voters can verify the authenticity and consistency of these statements. News articles and reports can be evaluated based on their source reputation and content quality, allowing voters to access information from high-reputation sources and reducing the risk of being misled by biased or false reporting. By providing tools for verifying the authenticity of information, Intuition empowers individuals to make more informed decisions. Ensuring that voters have access to accurate and reliable information strengthens the democratic process and protects it from manipulation. Transparent and accountable information dissem- ination fosters a healthier public discourse, where ideas can be debated based on their merits rather than misinformation. By reducing the prevalence of manipulation, Intuition can help restore trust in our media, building a more informed and engaged society. 9.2.2 Reviews The landscape of reviews in Web2 is fundamentally broken. Identity fragmentation makes it diﬃcult to reconcile reviews across platforms. As new platforms emerge, they compete for data, leading to further fragmentation. Although building aggregators is possible, Web2 companies often restrict access to their data, charge exorbitant fees for API usage, or eliminate access entirely, as their data is their moat. Data fragmentation exacerbates the problem. Users frequently express themselves through unstructured text in closed environments, such as group chats and verbal conversations. Without a suitable platform that ensures this data reaches the intended recipients, data remains fragmented and disconnected. A signiﬁcant issue is the lack of incentives for users to leave reviews on these platforms meant to aggregate communal sentiment. These incentives can be categorized into four main areas: • Economic Incentives : Currently, platforms like Amazon typically do not oﬀer ﬁnancial rewards for consumers to leave reviews. • Reputational Incentives: There is no mechanism for users to build and beneﬁt from a reputation as reviewers within or outside most platforms. • Educational Incentives : Users have no certainty that their reviews will be seen by people they care about, discouraging them from investing time and eﬀort. • F unctional Incentives: Reviewing products does not provide any practical utility to the user, aside from maybe occasionally serving as an outlet for frustrations. Due to these limitations, most users do not contribute reviews, even though most people relies on these reviews to make daily decisions. The absence of a better alternative forces reliance on fragmented and unreliable data to discern who or what to trust online. Intuition introduces a paradigm where every thing - including you, your network, and the things you are reviewing - has a canonical decentralized identiﬁer, making it universally referenceable across the web. Imagine leaving a review on a product in an Intuition-enabled app, and having it seamlessly propagate across all platforms that display reviews. Furthermore, imagine carrying your social and trust graphs, along with all your data, wherever you go. There would be no need to rejoin communities, rebuild follower lists, or repeatedly create proﬁles and set preferences. For instance, when shopping for supplements on Amazon, you could see recommendations from experts in your global ‘supplements trust graph’ . When searching for AI podcasts on Spotify, you would see recommendations from trusted individuals in the AI ﬁeld. Envision being compensated for sharing useful information. Liking a YouTube video could earn you money for each subsequent like it receives. You could build a reputation as a trusted reviewer of content or products. Your social graph or followers could always see your opinions if they wished—whether you liked a YouTube video, which supplements your trusted expert recommends, or which inﬂuencers in Web3 to follow. Furthermore, if users could take their reputation as a reviewer and use it elsewhere, such as in the process of securing an undercollateralized loan in decentralized ﬁnance (DeFi), the incentive to build and maintain a 83 good reputation would be much stronger. The ability to leverage their reviewer reputation in other contexts would enhance the value of leaving reviews, fostering a more interactive and community-driven environment. By allowing for the capture of many-to-one, non-deterministic attestations and incentivizing people econom- ically to participate in this process, Intuition provides a powerful tool for enhancing the value and impact of reviews across all platforms. This system not only improves the reliability and trustworthiness of reviews but also creates a more interconnected and motivated community of reviewers, ultimately leading to richer and more valuable user experiences. 9.2.3 Recommendations and Advertisements Advertising, when executed eﬀectively, has the potential to signiﬁcantly enhance the user experience by delivering relevant and desired content. Eﬀective advertising is beneﬁcial because it connects users with products and services they genuinely want or need. Rather than being perceived as a nuisance, relevant advertisements can enrich users’ lives by providing information about useful products, new music, upcoming events, or services they might not have discovered otherwise. When advertisements are tailored to individual preferences, they add value to the user experience. This is especially important in a world where there is inﬁnite content to consume and our options are nearly limitless. Spotify’s Discover Weekly playlist is a prime example of how personalized recommendations can lead to positive outcomes. Every week, Spotify curates a playlist of songs speciﬁcally tailored to each user’s music tastes, based on their listening history and preferences. This feature leverages sophisticated algorithms to predict which songs the user will enjoy, resulting in a highly personalized music discovery experience. For many users, Discover Weekly has become an anticipated event, oﬀering a curated selection of new and lesser-known tracks that align perfectly with their tastes. This not only enhances the user’s enjoyment but also supports artists by introducing their music to new audiences. In this case, the recommendation system acts as a form of advertising that users actively seek out and appreciate. However, current platforms often rely on interpreting implicit signaling of user preferences, which can lead to less-than-ideal recommendations. For example, Spotify’s Discover Weekly is based on the user’s listening activity over the past week. While this method often provides good recommendations, it does not always capture the user’s true preferences. Imagine a scenario where users could explicitly express their preferences in a universally semantic format that all platforms could ingest. This would eliminate irrelevant ads and recommendations. For instance, users who do not speak Spanish would no longer receive ads in Spanish, and those who prefer House music over Techno would receive recommendations that better match their tastes. By allowing users to explicitly communicate their preferences, platforms would be able to deliver more accurate and satisfying co