Imagine your favorite social media platform uses a new AI bot detection tool, and for some reason your account keeps getting flagged as fraudulent even though you are a real, human user.
You and anyone else who is falsely reported would have little recourse today.
With millions or even billions of users, it is almost impossible to get noticed by customer service representatives on some larger platforms. And if you want the platform’s algorithm to consider additional data points, such as metrics that would prove the humanity of you and others in your situation? Yes, good luck.
But what if the platform’s artificial intelligence model was integrated into the blockchain?
The factors driving the model’s bot determinations would be publicly available on-chain and visible to anyone with an internet connection. The AI model’s decision-making framework would be transparent, and if it were tied to a blockchain-based Decentralized Autonomous Organization (DAO), members of the platform could make a suggestion on how to change the model so that it does not incorrectly label people as bots .
There are, of course, countless other things that could be voted on, from content moderation standards to user experience decisions. The broader point? Full integration of AI models with Web3 technology can lead to greater transparency, greater value exchange, greater decentralization, better education, learning and communication.
This promise has people across the Web3 ecosystem buzzing, so much so that their shared enthusiasm for AI and Web3 is easily remembered. And while this excitement is warranted, let’s pour some cold water on the whole thing: we’re probably still a decade away from true AI-Web3 integration becoming a reality.
The current blockchain AI market, worth $230 million in 2021, is expected to become a billion-dollar industry within the next decade. It could potentially get to that assessment much sooner – but it must first overcome the fact that decentralizing AI is a difficult and costly proposition.
Executing the millions or even billions of transactions required to run an AI model is already an extremely expensive proposition, and doing so on the blockchain is even more expensive. This performance will require smart chips to do much more than is currently possible, which is in many ways similar to the massive advances that will be required to power another high-transaction Web3 innovation: the Metaverse.
AI-powered blockchains and protocols could combine the benefits of machine learning with the decentralization and aligned incentives of Web3. This stacking can lead to exponential gains, optimizing not only the work done by AI, but also the way the value of that work is distributed through the incentive, ownership and transparency models enabled by Web3 technology.
Based on AI, here are five Web3 use cases we are likely to see in the future:
- DeFi with AI-powered risk assessment: AI can significantly improve decentralized finance applications by providing advanced risk assessment models that assess the creditworthiness of a user applying for a loan or determine the risk of an investment product. Because blockchain ensures a transparent and immutable record, AI models can use this data to make more accurate predictions.
- AI-driven NFTs: As NFTs evolve from static to dynamic entities, AI can play an important role. For example, AI could enable the creation of “smart” NFTs that change over time based on certain conditions or inputs. This could lead to a variety of innovative applications, such as NFTs that change their appearance based on the time of day or an artist’s mood, or NFT-powered virtual characters that evolve based on user interactions.
- AI-managed DAOs: Decentralized autonomous organizations can use AI to automate decision-making processes and improve operational efficiency. For example, AI could help optimize resource allocation, make predictions about future trends, or even vote on proposals based on predefined criteria. The parameters that control these AI models could be set and adjusted by the community to ensure a balance between autonomy and human control.
- Monetization of personal data: Web3 gives individuals greater control over their personal information. Combined with AI, users could not only control who has access to their data, but also monetize it when necessary. For example, users could allow AI algorithms to use their personal data to improve their models, and in return they could receive compensation in the form of cryptocurrency.
- AI-Powered Metaverses: Artificial intelligence can be integrated into virtual worlds to create more realistic and dynamic experiences. For example, AI could be used to generate unique real-time content in the metaverse, such as creating personalized quests in a game or simulating realistic weather patterns in a virtual world.
Next-generation blockchain layers will integrate AI into the core components of their network, increasing efficiency in storage and other essential functions. One can imagine a world where the validator market consists of not only human validators but also AI validators, which also increases the security of the protocols.
Ultimately, AI will be integrated to essentially “control” Web3 blockchains and networks. Instead of a DAO voting on every small tweak or adjustment to the protocol, the AI model could be given broad influence to make decisions that ensure the DAO operates efficiently.
The community could adapt this area of responsibility based on its own values and interests. Importantly, it could also adjust the parameters by which the AI model makes decisions about the network – and because of the blockchain’s transparency, these parameters could be public and easily accessible to everyone.
At the moment, it is difficult for ordinary users – even large communities that come together – to compete with giant platforms that have huge amounts of technical and financial capital. AI’s ability to augment human capabilities could help level the playing field for these ordinary users by combining with DAOs and other Web3 organizations built on the blockchain to better distribute ownership and governance .
This final stage of AI and Web3 integration will be difficult and costly to achieve, which is why it will not happen overnight. In fact, it will take much longer than many of the hyped articles shared on the internet today.
But once this integration comes to pass, it will open up a whole new galaxy of apps and services that give people more ownership and control. And the level of innovation that will result could be orders of magnitude greater than what we can imagine today – comparable to humanity using flip phones in 2005 without realizing that in a decade they would be able to access a few buttons click and instantly call drivers to their location, order groceries, program applications and do countless other previously unimaginable things.