This blog post discusses the intersection of AI and blockchain, and how decentralized solutions can align better with user values and privacy. It also provides an example of a blockchain-based solution in the health insurance industry that utilizes AI to provide a better user experience while ensuring user privacy and data ownership. The post encourages businesses to adopt decentralized solutions and prioritize user sovereignty over data to deliver better value and solutions. Keywords: AI, blockchain, decentralization, user privacy, health insurance, user data, user sovereignty, blockchain-based solutions, decentralized platforms.
Peter Thiel famously said, "Crypto is libertarian. AI is communist." If this is the case, communism is winning. A few months after its public release, ChatGPT has over 100M active users while the most popular blockchain protocol, Ethereum, has just under 7M.
Every day, the technology press announces a startup working on a new AI use case. And tech giants Microsoft and Google are engaged in an AI spending war that would be cheaper to fight if instead of learning models they were building their own F-22 programs and fighting in the sky. Meanwhile, the Web3 and blockchain press celebrate the announcement of a new NFT collaboration or an undecipherable description of the latest DeFi tool that will, more than likely, bring zero new participants into Web3. An amazing contrast between the former reporting on a potential existential event and the latter cheering on a meaningless, jpeg-driven transfer of wealth.
For those of us working in Web3, we need to look at AI through the lens of what it means for our core values. Why does decentralization matter? Why is AI communist? What are the implications for society when power is in the hands of the few, whether big government or big tech? Thiel's warning references the potential of an established centralized entity that already holds a lot of data, increasing its power by leveraging the predictive power that AI can glean from this data. In a world where data is gold, arguing over who crypto OGs are or over jpegs seems… pedestrian.
Thiel's warning came well before ChatGPT was released. Since then, other prominent voices have warned us about the power of AI. Brian Chau demonstrated how easily AI could be taught to take on a specific political viewpoint, even when presented with objective scientific evidence to the contrary. Meanwhile, on a recent Bankless podcast entitled "We're All Gonna Die," Eliezer Yudkowsky warned that we are already past the tipping point where AI's destruction of humanity is inevitable. While we like Brian’s bleak vision of the future over death, a super woke HAL 9000 punishing me for a misplaced pronoun while I shop online seems too similar to a r/AboringDystopia post to not come true.
Centralization powered by AI could lead to multiple negative scenarios of which there are two very likely paths. The first path is a winner-takes-all scenario where centralized entities, MATANA or some newcomers, become even more dominant. This leads to a pornographic multiplier effect of Chris Dixon’s S-Curve model. Value extraction of the user isn’t limited to whether a company like Apple can sustain a 30% tax on in-app purchases, but how much they can take from Joe Smith today so that Joe Smith has enough gas left in the tank to transact tomorrow. A sort of authoritarian perversion of Pareto optimization that might keep Joe at the poverty level if this results in the highest present value that Joe represents to Apple.
The second scenario is a continuation of today's centralized balance of power, but with a constant state of conflict over which AI models are least bad. This is the type of conflict we see playing out today at Twitter. Multiple alternatives have come and gone and done nothing to chip away at Twitter’s dominance. Meanwhile, we either fall into a pre-Elon or post-Elon camp based on our perspective of which leadership team yielded the algorithms in the “fairest” way. Think of how this would work at other centralized entities like the IRS as an example. In the future, we all get screwed by the IRS’ AI tax tool and each new presidential administration appoints a new commissioner who tweaks the AI to favor a different group of voters.
Web3 cannot eliminate the bias that Brian Chau identified. However, what we can do is provide a means for the AI models that compete on information asymmetry to lose. In both scenarios, AI is used as a tool to develop a hyper-personal understanding of the individual. Google’s Hal Varian outlined the benefits of data extraction and processing employed to deliver a more personal experience. This may have been the intent of Google, but somewhere along the way, this data extraction changed its focus to supporting surveillance capitalism. The advanced understanding of the individual was not used to deliver the best result for the user, but the result that yields the highest economic value.
The tools of blockchain can align the best solution for the user with businesses that want to compete to give the best possible solution. Infrastructure that ensures that the data owner is also the data holder and destroys surveillance by delinking activities is essential. Most importantly, blockchain technology makes it unnecessary for businesses to compete in user data extraction. With blockchain, the user can represent themselves. These are the principles we should all be fighting for (and are a core part of what’s being built at Seneca Blockchain).
At Seneca, we are talking more about data privacy and control than about nebulous ideas of ‘privacy’ that exist in a vacuum. How do we change our assumptions? We all assume data must be mono-directional, from the user to the big [company… government… central body…] But what if business (and government and life) can be conducted while starting with completely different assumptions? Can companies deliver hyper-personal solutions without requiring the application to access the user's data?
This means that applications can compete on delivering the best possible solutions and not on having better methods of data extraction and processing. Furthermore, if a user has the agency to bring their data to a transaction, the application would be able to deliver a solution based on every relevant data point required. No more requirement for a company running an application to algorithmically fill in the blanks on missing data. This approach ensures that solutions are based on individuals, rather than personas.
To understand how this works, look at an application being built on Seneca, LifeJOY. LifeJOY, provides users with life insurance quotes using generative AI as an interface. A request as simple as "please provide me with quotes for life insurance" reveals specifically priced quotes in seconds based on unique user attributes such as health, fitness, age, etc. Every personal and unique data point that is required for a life insurance quote is utilized, but the user doesn’t share any personal data with the insurance provider, with brokers, or with anyone. This sounds simple but it is a jarring experience. We are so used to multi-step processes and manual data entry that the instant quote seems unreal. We are so used to sharing as default that it seems almost strange to reverse this process.
Could some carriers decide that they don’t want to sell through LifeJOY and instead use their own AI model that ingests and holds user data? Sure. But the carriers that use LifeJOY will know that their quotes and bound policies are based on verified data and that if the customer doesn’t end up going with them, they have no privacy or regulatory challenges with the customer data, as they never collected it in the first place. Insurance companies spend a lot of money trying to fill in the blanks on risk data to achieve certainty. Filling in the blanks is probabilistic while verified data is certain.
Many supporters of Web3 and blockchain favor decentralization based on principle. So do we. The quickest and best way to a decentralized future is to deliver a better experience and functionality so companies adopt it, governments find use, and communities find value. AI is a game-changer for business, and building AI alongside blockchain provides an opportunity to ensure that this change is for the betterment of individuals. Seneca's use case in LifeJOY is a perfect example of how AI and blockchain can be used to improve the user experience, and it sets the tone for other businesses to follow.
Is AI without blockchain going to lead us to a fiery apocalypse? First, we aren’t sure if AI by itself will end humanity as Yudkowsy believes. But even before ChatGPT, centralization was showing no signs of slowing down. Another centralized, big tech company or OpenAI will only contribute to that centralization, certainly as they are no longer a nonprofit. We need to make AI a tool that serves our values. We must promote user experience and, as they say, provide real business benefits for decentralized platforms. Fortunately, we have the most valuable weapon in the technology adoption arsenal, which is a 10X better solution. Decentralization and user sovereignty over data can create more value and deliver better solutions than the centralized path. And this value is where we win.