Please describe your proposed solution.
Executive Summary:
TrustLevel builds an online reputation system that addresses the challenges posed by misinformation, confirmation bias, and lack of accountability in today's digital world. Our solution combines blockchain technology and artificial intelligence (AI) to evaluate the trustworthiness, objectivity, and origin of online information and sources. Our system consists of a browser extension that uses AI to analyze website content, a reputation scoring algorithm that evaluates content and source quality, and the storage of reputation scores on the Cardano blockchain.
With this proposal, we are asking the Cardano community for funding to integrate the Cardano blockchain into the TrustLevel application.
Extended Problem Statement:
In today's interconnected world, it is nearly impossible for individuals to make judgments about the trustworthiness of online sources in a reasonable amount of time. The massive improvement in AI in recent months and the resulting rapid growth in the use of AI for content creation is further intensifying this issue.In the following are presented some main challenges with which our society is confronted today:
- Information Overload: The internet provides an overwhelming amount of information, making it difficult to differentiate between reliable and unreliable sources. Misinformation, disinformation, and fake news can easily spread, leading to confusion and skepticism.
- Ease of Publication: Anyone can create and publish content online without rigorous fact-checking or editorial oversight. This means that inaccurate or biased information can be readily available, making it crucial to critically evaluate the credibility of online sources.
- Confirmation Bias: Online platforms often use algorithms that personalize content based on users' preferences and browsing history. This can lead to the formation of echo chambers, where individuals are exposed primarily to information that aligns with their existing beliefs, reinforcing confirmation bias and limiting exposure to diverse perspectives.
- Malicious Actors: There are individuals or groups with the intent to deceive or manipulate others by disseminating false or misleading information. They may have political, financial, or social motivations that compromise the trustworthiness of online sources.
- Lack of Accountability: The anonymity and pseudonymity allowed by the internet can make it difficult to hold individuals or organizations accountable for the information they publish. Without clear attribution or transparency, it becomes harder to verify the credibility of the source.
- Rapid Spread of Information: Information can spread rapidly on the internet, often outpacing the ability to fact-check or verify its accuracy. This can result in false or misleading information gaining traction before corrections or clarifications can be made.
- Limited Media Literacy: Many individuals lack sufficient media literacy skills to critically evaluate online sources and distinguish between credible and unreliable information. This lack of awareness can contribute to the widespread dissemination and acceptance of misinformation.
For these reasons, we see an online reputation system that combines blockchain and AI as a necessary answer to these challenges.
Overview of our solution:
TrustLevel offers a reputation scoring system that evaluates the trustworthiness, objectivity and origin of online information. Our solution consists of three main components:
- Browser Extension: TrustLevel provides a browser extension that utilizes AI to analyze the content of websites and social media platforms (release around October 2023). It examines various aspects such as factual information, citations, references, and the presence of subjective evaluations or promotional elements.
- Reputation Scoring Algorithm: TrustLevel's reputation scoring algorithm evaluates both the content quality and source quality of online information (method is explained further below).
- Integration with Cardano Blockchain: To ensure transparency, immutability, and user control over reputation data, TrustLevel stores the reputation scores on the Cardano blockchain. This integration enables individuals to have ownership and control over their reputation data while allowing selective access to authorized entities and platforms.
TrustLevel scoring method:
The TrustLevel Score measures the trustworthiness of online articles and helps our user to verify online information and enable websites and authors to build reputation about their publications. We use different open source APIs and our own AI method to extract and analyze a webpage's content, sources, and other relevant parameters in real time providing immediate feedback to users about the website's reputation.
The TrustLevel reputation scoring algorithm consists of 3 main parameter:
- <u>Content quality score:</u>
The metric includes three aspects:
(1) Context Setting: the AI performs a text analysis to understand the content of the Internet source and find clues to possible subjective or objective elements (including the amount of factual information contained in the article, including citations and references).
(2) Sentiment polarity (negative, neutral, positive): Using sentiment analysis algorithms, the AI detects the subjective tone or emotional charge of the text. A higher objectivity score indicates that the text is more factual and free of subjective evaluations.
(3) The probability that the article is "clickbait” and or of promotional nature.
- <u>Source quality score</u>
The metric includes two aspects:
(1) assessing the quality of available sources by extracting hyperlinks, references, and references, and cross-referencing with previously published similar articles.
(2) Author assessment: credibility, expertise, and possible bias of the author or organization behind the source.
- <u>Controversy Score</u>
The controversy score is a metric used to assess the consistency of information across trusted sources. It aims to provide an indication of whether sources with high reputations have published comparable or different information on a given topic. The controversy score takes into account the representation of the topic from various trusted sources and evaluates the consistency or divergence of information. If multiple reputable sources present similar information without obvious bias or distortion, it suggests a higher level of objectivity and trustworthiness.
In other words, the controversy score analyzes how widely accepted or disputed a piece of information is among reputable sources. If there is a consensus among reliable sources, it increases the confidence in the information's reliability. On the other hand, if there are significant discrepancies or conflicting information from trusted sources, it may raise doubts about the accuracy or objectivity of the information.
By considering the consistency of information across multiple trusted sources, the controversy score provides users with an additional measure to assess the trustworthiness and reliability of online information. It helps users navigate through potential biases and discrepancies, enabling them to make more informed judgments about the credibility of the content they encounter.
Integration and use of blockchain:
The integration of a blockchain in TrustLevel's solution offers several advantages that position it as a leading application in its industry:
- User Ownership and Control: Blockchain allows individuals to have ownership and control over their reputation data. Users can selectively grant access to their reputation scores and choose which entities or platforms can access their information, giving individuals greater control over their online reputation.
- Transparency: Blockchain provides a transparent and immutable ledger where all reputation-related transactions and data will be recorded and can be verified by anyone, increasing trust in the system.
- Decentralization: With blockchain, reputation data can be stored and maintained across a distributed network of nodes, eliminating the need for a central authority or single point of control. Decentralization reduces the risk of manipulation or censorship, making the reputation score system more reliable.
- Interoperability: Blockchain can facilitate interoperability among different platforms and systems that utilize reputation scores. Reputation data stored on the blockchain can be accessed and utilized by various applications and services, enabling a unified reputation ecosystem.
By leveraging these features, a reputation score system built on blockchain can provide a transparent, decentralized, and secure framework for assessing and evaluating individuals' reputations in online environments. It offers increased trust, accountability, and control over reputation data, fostering a more reliable and equitable online reputation ecosystem.
Smart Contract Design:
- Reputation Score Storage: The smart contracts have a mechanism to store reputation scores associated with users or entities. This can be achieved by defining data structures within the smart contract that can store the reputation scores and their corresponding identifiers.
- Updatable Reputation Scores: The smart contracts allow for the updating of reputation scores.
- Integration with TrustLevel Web Application: API between the smart contracts and the TrustLevel browser extension. This integration enables the browser extension to interact with the smart contracts, retrieve reputation scores, and display them to users. It also allows users to submit feedback or other relevant data that can influence the reputation scores.
- Event Logging and Transparency: The smart contracts log relevant events, such as reputation score updates or user interactions. This provides transparency and auditability of reputation-related activities on the blockchain. Users can have confidence in the integrity of the reputation scoring system, knowing that all changes are transparently recorded on the Cardano blockchain.
What does the TrustLevel Score storage will look like?
- ReputationScore Struct:
- Address: The address or identifier of the user or entity associated with the reputation score.
- Score: The numerical value representing the reputation score.
- LastUpdated: The timestamp indicating when the reputation score was last updated.
- ReputationScores Mapping: Mapping user or entity address with their respective reputation score struct. This mapping allows for efficient retrieval and storage of reputation scores. Each address serves as the key, and the associated reputation score struct represents the value.
- Update Reputation Score Function: This function takes parameters such as the address of the user or entity and the new reputation score. It updates the reputation score struct associated with the given address in the reputation scores mapping.
- Get Reputation Score Function: This function takes the address as input and returns the associated reputation score struct from the reputation scores mapping.
How does your proposed solution address the challenge and what benefits will this bring to the Cardano ecosystem?
The challenge asks for products and integrations that will offer more high impact use cases to the Cardano ecosystem and that drive more adoption.
TrustLevel offers a unique innovation for the verification of online information. By integrating the Cardano Blockchain into our solution, we are able to deliver a number of new features to our users and at the same time the Cardano ecosystem benefits from increasing usage and adoption.
Our proposed solution brings several benefits to the Cardano ecosystem:
- Increased Adoption: By integrating TrustLevel's reputation scoring system with the Cardano blockchain, it can attract more users and applications to the Cardano ecosystem. The reputation system addresses the challenges of misinformation and unreliable online sources, which are prevalent in today's digital landscape. This can position Cardano as a trusted platform for accessing reliable information, encouraging adoption and usage of the Cardano network.
- Interoperability and Synergy: The integration of TrustLevel with Cardano creates opportunities for interoperability and synergy within the ecosystem. Reputation data stored on the Cardano blockchain can be accessed and utilized by various applications and services within the Cardano network. This allows reputation scores to be used across different platforms, contributing to a unified reputation ecosystem within Cardano.
- Trustworthy DApp Development: TrustLevel's reputation scoring system can benefit decentralized application (DApp) developers on the Cardano platform. By utilizing TrustLevel's reputation scores, DApps can assess the trustworthiness and reliability of data sources, enabling them to provide more accurate and reliable services to users. This can foster the development of high-quality DApps within the Cardano ecosystem.
How do you intend to measure the success of your project?
The successful completion of the proposal means that we will have a functional integration of the Cardano blockchain into the TrustLevel application within the specified timeframe.
To measure the success of our project we propose several KPIs:
- User Adoption: We measure the number of users who have installed and actively use the TrustLevel browser extension or application. This KPI reflects the level of acceptance and adoption of TrustLevel's reputation scoring system. Our goal is to reach 1000 installations within the first month after the product launch.
- Reputation Score Usage: We track the frequency and extent to which reputation scores stored on the Cardano blockchain are utilized by websites, social media accounts, or information providers. This indicates the integration and adoption of TrustLevel's reputation scores within the online ecosystem. Our goal is to reach 10.000 requests of our TrustLevel API within the first month after the product launch.
- Accuracy and Reliability: We conduct periodic assessments to evaluate the accuracy and reliability of TrustLevel's reputation scores. This involves comparing the reputation scores assigned by TrustLevel with independent assessments of the same content or sources. The higher the accuracy and reliability, the more successful the project. We aim for an accuracy of higher than 75% within the first month after the product launch.
- User Satisfaction: We gather feedback from users regarding their satisfaction with TrustLevel's reputation scoring system. Surveys, ratings, and user testimonials can provide insights into user satisfaction levels, user experience, and perceived value of the solution. We aim for a user rating of 4 out of 5 or higher within the first month after the product launch.
- Partnerships and Integration: We monitor the number of partnerships and integrations with other platforms, organizations, or content providers. This demonstrates the willingness of external entities to collaborate with TrustLevel and integrate its reputation scoring system, indicating the project's market relevance and potential impact. We aim for at least three substantial partnerships within the first month of the product launch.
- Community Engagement: We measure the level of engagement within the Cardano community related to TrustLevel's project. This includes metrics such as the number of active community members involved in discussions, contributions, or development efforts related to TrustLevel. We aim for at least 20 active community members of the Cardano and Catalyst ecosystem engaging in the development of TrustLevel. These can include tasks as beta testing.
Please describe your plans to share the outputs and results of your project?
Our approach is to operate as transparently as possible, so that the community has the maximum possible insight into the project on the one hand and can also participate in the project on the other. Therefore we provide different sources for the documentation:
Our Website: We will create a sub page on our website to give the community easy access to all relevant documents, links and reports that we will publish.
GitHub: To measure and track the process of the proposal, we will document any step and output in our dedicated GitHub repository.
Furthermore, we will offer monthly feedback session for the community (communicated via GitHub and on Catalyst Telegram Channels).
Official monthly Catalyst reporting:
- During monthly reporting we share our activity board for the project as well as the developer sprint velocity for development tickets
- During monthly reporting we share estimated parts of work in our detailed budget/timeline that need more or less time than expected to get an estimate on the forecasted completion date.