The transition from Web2 to Web3 represents a significant shift in how we manage and control information online. Web3 offers a potential solution to issues like privacy, surveillance, and misinformation by utilizing blockchain technology to give users more control over their data.

However, Web3’s adoption has been slowed by user friction. The integration of AGI and blockchain technology can help accelerate the adoption of Web3 by improving the user experience and reducing user friction. For example, decentralized AI built on blockchain can offer users personalized online experiences while protecting their privacy and control over their data.

Blockchain and AI are complementary technologies that address each other’s limitations. Blockchain’s built-in consensus protocol can help ensure the accuracy and integrity of data, while AI trained on flawed data will inevitably produce flawed results. Additionally, blockchain platforms can be designed to distribute power more evenly, reducing the risk of a few AI companies or models making opaque but consequential decisions. However, leveraging the power of AI and blockchain cohesively is a complex task that requires overcoming technical challenges. One way to track the co-development of these two technologies is to examine their progression in three phases:

• Data,
• Information, and
• Knowledge.

AI can accelerate Web3 adoption by offering personalized experiences based on user prompts. For Web3 to go mainstream, the next generation of consumer-facing applications using blockchain must at least match the user experiences of Web2. Personalization will be essential for these applications to effectively engage their audience and attract new users, thereby optimizing marketing spend. Decentralized knowledge graphs – as they are developed in the Artificial Superintelligence Alliance ASI – may be the key to bringing personalized experiences from Web2 into Web3. Knowledge graphs are data science tools that map relationships between objects, facts, events, situations, and other data. By leveraging open, permissionless blockchain networks, decentralized knowledge graphs can make knowledge graphs more accessible and verifiable. By utilizing cutting-edge tools like knowledge graphs, integrating AI and blockchain can serve as the foundation for Web3 built on trustworthy data. This new decentralized internet can help address issues prevalent in our current centralized internet, such as disinformation, surveillance, risks to privacy and security, and loss of agency over personal data.

AI and Web3 belong together and can improve internet governance:

1. Decentralization: Web3 is built on blockchain technology, which is decentralized and transparent. AI can leverage this decentralized architecture to ensure that data is stored and processed in a secure, transparent, and tamper-evident manner. This reduces the risk of a single entity controlling or manipulating data, promoting a more democratic and equitable Internet governance.
2. Trust and Transparency: AI can help verify the authenticity and accuracy of data on the blockchain, ensuring that information is trustworthy and transparent. This is particularly important for internet governance, as it enables users to make informed decisions and reduces the spread of misinformation.
3. Autonomy and Agency: Web3’s decentralized architecture and AI’s ability to automate decision-making processes can empower users to take control of their personal data and online experiences. This promotes autonomy and agency, allowing users to make choices that align with their values and preferences.
4. Security and Privacy: AI can help detect and prevent cyber threats, ensuring that Web3 applications are more secure and private. This is crucial for internet governance, as it protects users’ sensitive information and prevents unauthorized access or manipulation.
5. Scalability and Efficiency: AI can optimize Web3 applications, enabling them to scale more efficiently and process vast amounts of data in real time. This improves the overall performance and responsiveness of the internet, making it more suitable for a wide range of use cases.
6. Incentivization and Tokenomics: AI can help design and optimize token-based incentive systems, which are essential for Web3’s decentralized architecture. These systems encourage desired behavior, such as data sharing or content creation, and promote a healthier internet ecosystem.
7. Data-Driven Decision-Making: AI can analyze vast amounts of data generated by Web3 applications, providing insights that inform data-driven decision-making. This enables more effective Internet governance, as decisions are based on objective data rather than personal biases or assumptions.
8. Accountability and Governance: AI can help ensure accountability and transparency in Web3’s decentralized governance models. By monitoring and analyzing network activity, AI can detect and prevent malicious behavior, ensuring that the internet remains a safe and trustworthy environment.

By combining AI and Web3, we can create a more decentralized, transparent, and secure internet that prioritizes user autonomy, privacy, and agency. This can lead to better internet governance, as decisions are made based on objective data and are more responsive to the needs of users.