Exploring the Relationship between AI and Web3

The short answer is technically, no, AI is not considered part of "web3". But as with most technologies, it depends.

The recent surge in web- and mobile applications developed over the past year has ushered in a new era of technological integration. In particular, the convergence of Artificial Intelligence (AI) and Web3 presents a unique technological synergy that seems like a match made in heaven. This intersection has given rise to an array of opportunities, fostering innovation, and expanding the horizons of what can be achieved in the digital realm. The amalgamation of AI's ability to learn, predict, and automate with the decentralization, security, and user-centric ethos of Web3 is opening up exciting new possibilities. From decentralized finance and autonomous organizations to personalized, privacy-preserving services, the fusion of AI and Web3 is poised to redefine the future of technology.

What is web3?

Computer scientist Gavin Wood coined the term “Web 3.0” in 2014, which refers to a vision for the future of the internet that is “decentralized”, and where content and data is “democratized”. This version of the internet is one not dominated by a handful of “tech giants” like Amazon, Microsoft, and Google. Instead, these online platforms, services, web apps and even mobile apps that we utilize are not tied to a single provider or company. They are primarily hosted in a collective manner, resembling a peer-to-peer network. The principle behind the web3 approach is that all participants contribute a tiny part to the overall service.

One of the technologies dominantly associated with web3 are blockchain technologies, where users have full control over their data and digital identities. Commonly understood use-cases of blockchains include decentralized finance (DeFi), decentralized autonomous organizations (DAOs), non-fungible tokens (NFTs). This paradigm of the internet emphasizes the decentralization of control, autonomy over one’s data and empowering community and creators.

So what about AI?

Artificial Intelligence (AI) is a broad field encompassing various sub-disciplines such as machine learning, natural language processing, computer vision, robotics, etc. AI functions by simulating human “intelligence processes” in machines. This typically involves feeding datasets of information that deals with learning, reasoning, problem-solving, perception, and language understanding. The data is processed using predefined algorithms, which allow the AI to learn patterns and gain insights from the data.

One key feature of AI is its adaptability. The more data the AI processes, the more accurate its outputs become. In theory, it is a self-improving system: as it gets more data and feedback, it continuously updates its understanding, making better and more precise predictions or decisions. This characteristic is what allows AI to handle a broad array of tasks, from playing chess to driving autonomous vehicles, and to constantly improve in performing these tasks.

So do elements of AI fall under the web3 category of technologies?

AI in itself isn’t intrinsically linked to the principles of web3, as its primary function lies in making machines and systems perform tasks that normally require some basic human intelligence. This includes tasks such as recognizing patterns, understanding languages, making decisions, and so forth.

Machine Learning (ML), a subset of AI, as a technology function also doesn’t inherently align with the vision of web3. ML involves algorithms that enable systems to learn from data, improve over time, and make predictions or decisions without being explicitly programmed to do so.

AI and ML are technologies that can function in any context, and can augment the functionalities of systems, be it centralized ones (like those of the tech giants) or decentralized ones (like envisioned in web3). Their function is not dependent on the structure of data ownership or the network they operate on. Instead, they work towards enhancing the capabilities of these systems.

One could definitely argue that AI and ML could have a big role to play in the context of web3. For instance, they could be used to enhance the functionality and efficiency of decentralized systems, provide personalization while maintaining data privacy, or facilitate complex decision-making processes in DAOs. By technical distinctions, they are not part of web3’s core infrastructure but rather auxiliary tools that can be applied in a web3 context to optimize processes and deliver value to users. Although, they are not inherently part of web3, but they can definitely play a significant role in shaping the future of a decentralized internet.