Web3 promises to usher in a new Internet owned by builders and users rather than corporate giants. Leveraging blockchain technologies and tokenomics, its proponents envision decentralized social networks, play-to-earn games, and an intermediary-free digital economy.
At the same time, artificial intelligence capabilities have grown by leaps and bounds over the past few years. While a chess-beating bot was impressive, today’s algorithms can write a compelling novel, generate a gallery-worthy painting, or create a new app in minutes.
In this article, we’ll look at how the combination of these technologies could pave the way for an exciting new generation of AI-powered Web3 applications.
A Quick Web3 Primer
Web3 represents a natural evolution from Web1 and Web2. Web1 refers to the internet of the 1990s and early 2000s, powered by open protocols like HTTP, SMTP, and FTP. There were no massive single owners of web infrastructure, and most builders and creators published content on servers they set up or rented from server farms.
Then, social media giants ushered in the Web2 era, characterized by content creation on social media platforms. Rather than owning their content, Facebook, Twitter, and other social media took over distribution and monetization. As a result, perverse incentives led to the promotion of disinformation and many other challenges.
Web3 aims to replace these social media giants with open protocols and decentralization, putting the power back into the hands of users and creators rather than social media giants. In essence, it would combine the open infrastructure of Web1 with the public participation of Web2 and set the stage for a more vibrant global community.
A great example of these principles in action is IPFS, a peer-to-peer hypermedia protocol. Rather than storing data on centralized servers, IPFS stores data across multiple nodes, creating a more resilient network. Consumers can retrieve data from multiple nodes at the same time for a faster experience, while creators can store data that’s always available forever.
The AI Revolution
Artificial intelligence (AI) has also come a long way over the past couple of years. After deep learning algorithms beat humans at chess and go, large language models (LLMs) became proficient at everything from holding conversations to writing code. And, there’s no sign that these trends will slow over the coming months as algorithms continue to evolve.
These technologies could play an enormous role in the Web3 ecosystem, from optimizing smart contracts for better performance to detecting fraudulent transactions
Data Management
Smart Contracts
Web3 applications are built on smart contracts. By encoding the terms of an agreement, they automatically execute when pre-set conditions are met, eliminating the need to trust an intermediary. As a result, they’ve become an integral part of everything from decentralized finance (DeFi) transactions to non-fungible token-based (NFT) collectibles.
AI could improve Web3 smart contracts by analyzing patterns and suggesting optimal terms for these agreements. In addition, they could help automatically resolve disputes by analyzing contract terms, the behavior of each party, and any related transactions to make impartial decisions. Or, they could help on a more fundamental level to improve contract performance.
Governance & Consensus
Many crypto projects rely on governance and consensus mechanisms to make decisions. By distributing voting power among members, decentralized autonomous organizations (DAOs) and similar mechanisms can democratize decision-making and ensure that Web3 projects move in the best interests of the stakeholders rather than a group of minority owners.
AI could improve these governance and consensus mechanisms. For instance, they could analyze voting data to identify potentially fraudulent patterns. Or, they could analyze historical voting data to assess the likelihood of certain proposals to pass. They could even suggest new proposals based on issues that users experience and the state of the code base.
Creator Economy
NFTs have helped spark a revolution in the creator economy, enabling digital-native artists to monetize their work. Meanwhile, play-to-earn games have introduced new dynamics into the multi-billion dollar gaming industry. As a result, massive creator ecosystems have emerged alongside new virtual reality and augmented reality technologies.
In the future, play-to-earn game developers could leverage AI to generate unique in-game items with varying rarity levels, endless maps with unique topologies, or virtual characters modeled after real users. These capabilities make it possible to create innovative gaming experiences that aren’t possible without AI capabilities.
Finance and Tokenomics
Financial services and tokenomics are an integral part of the Web3 ecosystem, helping incentive creators and democratize services. For example, DeFi has the potential to revolutionize everything from lending to market making, while other crypto projects aim to reduce the friction of cross-border transactions and tackle other problems.
Of course, AI could play a heavy role in these efforts. AI-based risk assessment tools could help price everything from loans to securities, while predictive analytics could forecast token prices, market volatility, and investor behavior. AI could also help mitigate crypto market risks through the use of derivatives or other financial engineering tools and techniques
Potential Challenges
Artificial intelligence could add tremendous value to the Web3 ecosystem, but it also introduces a unique set of challenges.
AI can be opaque and difficult to understand (e.g., its outputs can’t be traced back to specific inputs), which could lead to decisions that users find unfair or discriminatory. For example, a ProPublica investigation of the AI-powered COMPAS program found a significant racial bias. Web3 developers should ensure the data they use to train AI models is representative and unbiased while testing the algorithms to ensure they promote fair decisions.
Privacy rules and regulations could also influence the availability of training data. For instance, some countries have strict regulations surrounding data privacy, limiting the amount of information an AI can access to make decisions. Web3 developers must navigate these rules and regulations to ensure they comply with these regulations, avoid any potential legal problems, and build trust with their user base.
Finally, AI models are expensive to develop and train, meaning proprietary models often have the best results. However, the opaqueness of these models could deter crypto developers that prefer open-source code and open standards. These proprietary models could also involve significantly higher costs that may not be acceptable to Web3 developers or their users, while opening up Web3 apps to issues if these services go down.
The Bottom Line
Web3 promises to reshape today’s internet, making it more equitable for builders, creators, and users. While blockchain technologies help decentralize and tokenize Web3, artificial intelligence is crucial in empowering creators and accelerating technological progress. And many of these AI technologies are just now gaining traction.
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