The role of AI in making Web 3 accessible to the masses

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The launch of Web3 ushers in a transformative era for the Internet, promising a secure and user-empowered online experience. However, blockchain’s technical complexities present a formidable barrier to mass adoption.

Not only that, but the complexity of crypto may be partially responsible for some of the major disruptions the ecosystem has faced in recent years, most notably the demise of FTX. A recent post by John Wang on X (formerly Twitter) described the gravity of the aftermath and the serious technical hurdles facing the judges in this case, By describing “Watching the jury made me realize how far we have to go in educating and onboarding the general public. Blockchain UX is still a joke.

Enter artificial intelligence (AI)—the technological linchpin poised to unseat the Web3 for the everyday user and bridge the gap between innovation and usability.

Complexity of the Web 3

Web3 represents a leap towards an Internet where users control their data, identity and transactions through blockchain technology. Despite its revolutionary potential, the inherent complexity of understanding and interacting with Web3 platforms has limited its appeal to a wider audience. When consumers themselves are not empowered to understand these technologies, it can also lead to situations where they trust institutions, which, in the example of FTX, can have disastrous consequences. The technical nuances of managing digital wallets, engaging with smart contracts, and navigating dApps can be daunting for the uninitiated, creating a chasm between Web3’s potential and its practical application.

Facilitating smart contracts with AI

Smart contracts are self-executing contracts with contract terms written directly in lines of code. Essential to blockchain technology, they automatically enforce and enforce contract terms when predetermined conditions are met, without the need for intermediaries. This makes transactions not only more efficient but also transparent and tamper-free, leveraging the permissionless and secure nature of blockchain. Smart contracts are the cornerstone of many blockchain applications, enabling trusted contracts and automated transactions that could redefine industries from finance to supply chain management.

AI, with its vast capabilities in natural language processing (NLP) and machine learning (ML), emerges as a ray of hope in this scenario. By integrating AI technologies into Web3 platforms, the user experience can be dramatically transformed to emphasize simplicity, insight, and accessibility.

An AI-powered natural language processing (NLP) model can interpret and implement complex smart contract protocols through a simple, conversational language, allowing users to engage with dApps without a deep understanding of the underlying code. is allowed.

“AI-powered NLP models may be able to make complex smart contracts readable to the public. However, as with any AI system, we must be mindful of the room for error and deception in the systems we build. If we Depend on AI. Interpret blockchain systems We will need to pay extra attention to adopting checks and balances that can keep our systems secure and fair in the long term,” commented Maika Isugawa, founder and CEO of Webisi. What did

A more usable interface

Many users struggle with the complexities of web3. Machine learning algorithms can analyze user behavior to personalize their experience, generate recommendations and automate transactions based on individual preferences and patterns.

Several companies are beginning to integrate machine learning algorithms to enhance the user experience in the Web3, with the goal of simplifying its complexities and providing services tailored to individual user preferences. These firms are tackling the dual challenge of leveraging smart contracts within blockchain platforms while making their interfaces more intuitive and user-friendly through AI-powered personalization.
is building machine learning platforms for applications in various sectors including finance, transportation and energy. uses autonomous agents on the blockchain to automate decision-making processes and transactions, making the Web3 experience more intuitive.

Building a marketplace for AI services, allowing anyone to create, share and monetize AI services at scale. The platform uses blockchain to facilitate transactions between users and AI service providers, tailoring the AI ​​services offered to its customers’ needs.

While Brave is primarily known for its privacy-focused browser, Brave has ventured into the Web3 space with features like Brave Rewards and Core Attention Tokens that integrate blockchain technology for advertisers, content creators, and consumers. she does. It uses machine learning to personalize the user experience without compromising privacy, providing an example of how Web3 applications can tailor experiences in a user-centric manner.

Brian Bondy, Brave’s CTO and co-founder told me, “Brave’s approach to every product we build is to put users in charge of their experience and integrate privacy by default. have been using machine learning for years. based advertising platforms to match ads to users while maintaining their privacy. Our goal is to protect user data across users’ devices and ultimately make those devices Connect to blockchain nodes and Web3 servers via cryptographic protocols that do not collect data.”

Fraud detection

Another key area where AI can significantly help Web3 achieve mass adoption is in enhanced security and fraud detection. As Web3 platforms grow in popularity, they become more attractive targets for malicious activity.

AI can help mitigate these risks by analyzing patterns, detecting anomalies that may indicate fraudulent activity, and enhancing the overall security infrastructure of blockchain networks. By leveraging AI’s predictive capabilities, Web3 platforms can identify and respond to security threats, ensuring a secure ecosystem for users and fostering greater trust in blockchain technology.

Quantstamp leverages AI in its mission to secure crypto applications. It provides security audits for smart contracts and blockchain networks, using AI algorithms to automatically scan and identify vulnerabilities. This proactive approach to security helps preserve the integrity of Web3 applications and protect them from exploitation and hacking.

Chainalysis is known for its comprehensive blockchain data analysis tools, used by governments, banks and businesses to detect fraudulent transactions and understand blockchain activity. By applying AI and machine learning to large amounts of blockchain data, Chainalysis helps identify and prevent illegal activities in the Web3 ecosystem. This not only enhances security but also promotes regulatory compliance, making blockchain technology more palatable for mainstream adoption.

Addressing security concerns with AI-powered solutions, these companies play a key role in driving the mass adoption of Web3 technologies, ensuring that trust and security are paramount in the crypto ecosystem. Stay ahead.

Take for example, POG Digital. POG Digital is an interoperable universal gaming ecosystem created by THE WORLD POG FEDERATION™, a beloved game and collectible brand from the 90s. They have more than 150 million people spread across 40 countries who are pogers, who are collectors. In June, 2022, POG moved to placing its collections online. Their CEO and founder, Kyler Frisbee, came from Google.
where he led AI projects as well as Unity Technologies.

As Kyler told me, “In 2017, I helped build a team at Unity that won an award from Forbes for the top 5 breakthroughs in AI for playing video games we built on Unity. This technology was provided as a service to game developers to better understand bottlenecks and pain points in gameplay. Places in games where players get stuck or too slow to move forward. There was a problem.”

He continued on how they are using it at POG, “We have expanded this technology at POG to better understand our games as well as identify cheating and fraudulent gameplay. AI game agents are excited to use agents in which bots try to mimic human behavior.

“This technology is critical to mass adoption because we want our games to be accessible, engaging and fair. And as we integrate web3 game assets and digital collections, for us in our gameplay The need to install the highest level of fraud detection is paramount.”

Impact on widespread adoption

The integration of AI into Web3 platforms is not just a technological addition. This is a paradigm shift towards making blockchain accessible to a wider audience. By simplifying the user experience and lowering the barrier to entry, AI has the potential for mass adoption of cryptocurrencies.

Despite the promise, integrating AI with Web3 is not without its challenges. Issues of scalability, data privacy, and the development of standard AI frameworks for blockchain applications must be addressed. Still, as soon as these challenges are overcome, the future of a user-friendly, AI-enhanced Web3 looks increasingly bright.


AI stands as a key force in realizing the promise of a user-centric Internet and the reality of today’s complex Web3 technologies. As AI continues to evolve and integrate with the Web3, the barriers that once stood in the way of mass adoption begin to break down, paving the way for a future where the full capabilities of the Web are fully realized. Everyone can understand. The journey to this future is just beginning, but the path is clear: AI and Web3 together are transforming the digital landscape into one that is more accessible, empowering and inclusive for all.

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