People are full of concerns about artificial intelligence (AI), however, the combination of blockchain technology can be an excellent complement to human intelligence.
The cultural and regulatory dialogue around the world today indicates that people have many concerns about artificial intelligence. Artificial intelligence will take over the world, it will take away everyone’s jobs, it will destroy Hollywood: you can choose your own dystopian adventure. I don’t want these things to happen either, but deep down I am an optimist about artificial intelligence. Humans have done quite poorly in many aspects, and we should hope that artificial intelligence can help us solve these problems and work with us to solve them, especially when it comes to solving complex problems.
This is exactly what has been discussed in the Web3 field since the birth of Bitcoin: how to coordinate large-scale, decentralized, and complex populations under a common goal. The point I want to make is that in some areas, the combination of artificial intelligence and Web3 can truly help society solve its most complex problems. The following is a perspective on what this combination could look like, based on the current state of technology, and it is entirely feasible.
Some things that artificial intelligence is good at: collecting and integrating large amounts of information, even on a global scale. Evaluating results based on a set of parameters and conducting research and tasks based on explicit instructions from experts.
Some things that blockchain is good at: governance frameworks, deploying global pools of funds across multiple jurisdictions, helping expand networks of participants on a global scale around common protocols.
Some things that humans are good at: building deep holistic expertise based on organic experience, making wise and nuanced decisions, and sharing knowledge and passion on topics that matter to their communities.
What happens when we mix all these elements together to tackle a complex problem? I’m referring to a truly complex, global problem that has plagued generations or a “wicked problem” like curing cancer. This requires coordinating the actions and desires of thousands of people, making high-risk decisions on strategy and resource allocation, and managing across many industries and jurisdictions.
How does it work?
So let’s imagine a “Cure Cancer” DAO (decentralized autonomous organization). It is founded by a group of scientific research labs, academic departments, and disease communities, with an initial total of 1,000 people. They identify a common mission and designate a small group of experts as the governance team responsible for making strategic decisions. They launch a DAO that issues membership NFTs with different levels of governance responsibilities to each participant and allocate a pool of funds as startup capital. Then they establish an artificial intelligence agent to manage the project’s scaling process.
The governance committee has designated a series of key performance indicators (KPIs) to the artificial intelligence agent, requiring it to complete a series of community management tasks. Assuming these tasks are initially: managing donations to the funding pool, tracking new members, and paying for work completed by representatives of the DAO based on clear delivery criteria. This will save a significant amount of time and expenses, which are typically consumed by non-profit organizations or DAOs.
More importantly, the committee also requires the AI agent to assess the needs for advancing the cure for cancer and develop a proposal, including a work roadmap, sub-projects, potential participants, institutions suitable for global participation, and specific tasks to be completed. The agent formulates a long-term plan and proposes a series of execution steps, which are then submitted to the expert committee for review.
The committee adjusts and prioritizes the roadmap proposed by the AI in order to cover the work of the Cure Cancer DAO for the first six months. They authorize the AI agent to recruit personnel to complete these tasks, allocate work (regardless of size), and evaluate the completion of the work, paying compensation from the funding pool.
The AI agent will regularly update the roadmap and report progress to all stakeholders in the DAO, in a way that manages the overall view, enabling local contributions to be more effectively carried out in real time. Over time, it can expand the scope of the project by proposing sub-communities, managing experiments, and assisting in coordinating collaboration among growing members, even interacting with multiple committees managing different professional fields.
The DAO committee can veto any proposal put forward by the agent or make improvements to make things more efficient as progress is made. Over time, if the governance committee observes that the AI agent is underperforming in a certain aspect, they can commission the collection of new training data in that specific area to improve the model and fine-tune it to their needs. This can even be crowdsourced from the expert community on the blockchain, with these experts reviewing the work and evaluating the improvement of the AI agent.
The Role of AI and Web3
In fact, this vision requires the dual participation of AI and Web3 to be realized. We need Web3 for governance, financial support, and coordination tools. All AI behaviors are carried out on the chain, team members and donations are managed through blockchain tools, and it can interact directly with the DAO’s funding pool, enabling fully transparent transactions. As long as it collaborates with professionals and operates under the supervision and transparency of the blockchain, AI can optimize every aspect of operating the Cure Cancer DAO. If all processes are completed on the blockchain, we can even monitor risks and manage trust better than the current major social systems.
This is just a very high-level example, but I hope it can guide us to think in an optimistic direction, that is, how we can more effectively solve problems by creatively applying AI and Web3. We will be able to expand many things that were previously too complex to be managed solely through social means, or solely through top-down command and control, or solely through blockchain. This decentralized scientific community building example is also applicable to any global coordination problem or research effort.
These technologies are far less interesting in isolation than when they are combined together: it’s not about artificial intelligence doing the whole job alone, but about it playing a role in areas where we are not good at, helping us coordinate better and complete the work faster. If we focus on efficient construction and proactive risk management, establish checks and balances mechanisms that maximize the advantages of human and technological participants, and work together towards a shared mission, we will see some powerful experiments gradually emerge in the coming years.