Thesis of Data Economy 3.0

This is probably my most exciting and most important innovation article so far. Driven by the Fourth Industrial Revolution (4IR), we are witnessing the dawn of a new Data Economy, one that I would like to call the Data Economy 3.0. As this new data economy keeps evolving over time, it is my hope that we will find many contributors to this topic so we can design this together. We need the innovators and the scientists, the passionate daily users and the sceptics, we need the businesspeople and the bureaucrats.

We need you, to join in this wonderful journey towards a better data economy.

The Fourth Industrial Revolution

One could say that the 4IR is a next phase in the digitization of everything, driven by technologies that enable us to do things we could have never thought of before. These technologies enable us to redefine human-machine interaction, improvements in robotics, enhancements of Artificial Intelligence as well as (of course) data and connectivity.

We are currently (2024) at the very center in the innovation stage of the 4IR, the rise of GPT (such as the one from open AI) and AI image generation (such as the ones used in this article) are just a few examples of where the 4IR becomes tangible. The launch of Apple's Vision Pro is another example of early human-machine interaction and it clears the path for a better way of human-human interaction.

An (old) McKinsey report about the 4IR mentions that there are four foundational types of technologies that are driving the 4IR, the two that stand out and clear the path for the Data Economy 3.0 are:

1. Connectivity and computational power: Distributed cloud computing, blockchain, centralised & decentralised storage.
2. Data, analytics and intelligence: Artificial Intelligence & Autonomous AI, community (shared) data, data-control, advanced analytics, data monetization, standardisation & federated learning.

Note that behind the colon, is my take on technologies that are relevant to the Data Economy 3.0. Please let me know which ones I missed!

There is much to say about the 4IR and the benefits as well as the dangers it brings. Without a doubt it will change the way we work and connect with each other, it will make some jobs obsolete and new ones will be created. These technologies can, and will be, used for the greater good as wel as for the dark side of human nature.

Above all, the 4IR is driven by data and rapid learning. This inevitably leads to a new way of looking at 'the data economy'. The 4IR gives a logical and natural rise of the Data Economy 3.0!

Example of a more known 'Economy 3.0'

As it might be hard, at this point, to visualise the Data Economy 3.0. I would first like to introduce you to another 4IR powered new economy, which is known as the Creator Economy 3.0. This is a creator economy where creators and their fans/communities are put at the heart of everything. Every participant in the Creator Economy 3.0 benefits from their active participation and every actor has a voice/vote on what direction should be taken. This is very different from the current Creator Economy 2.0, which is platform centric (always, without exception) and mostly driven by influencers.

Imagine a platform where the creator (influencer, digital artist, choreographer or writer for example) release their content, knowledge and creations as digital assets. Whoever holds an asset/original that was once created by the artist receives certain rights. These rights could mean special access to otherwise closed off spaces, voting rights, the right to receive advertising-income, the right to hold copyright and receive royalties and much more. The distribution of rights is what makes the new Creator Economy so appealing to artists and their communities as rights that were commonly held centrally (often by the platform and their shareholders) are now distributed to those who add the actual value.

We talk about economies, especially when tokenization is introduced. There are many design principles for good tokenomics, and a main principle of good tokenomics include that those who add value can 'earn' tokens which then can be used in the ecosystem. This 'adding value' can be anything from contributing technical expertise, doing marketing activities and creating amazing work that people love. This also means that it is not only the creator who adds value, also their communities, developers, businesses and many more.

A key difference made by the new (3.0) economies lies in its purest form of ecosystem thinking and value creation, so that new micro-economies can be formed. Every actor in an economy benefits from its success, which is extremely powerful.

The Data Economy 3.0

The Data Economy 1.0 was driven by very flat 'simple' data, digital but often not connected to the web. The Data Economy 2.0 was platform centric and platform driven. The platforms, the games, the weather-apps, the business siloes, the giant tech, the siren servers.

Wonder why almost every single company in the top 100 most valuable companies are tech companies? Well, these are all innovation driven, which means they are data driven, which often mean they are driven on other people's (your) or businesses (also your) data.

Similar to the Creator Economy 3.0, the Data Economy 3.0 is ecosystem driven, it exist by virtue of those who share data, add data, improve data, manage data, control data, analyse data, train AI based on that data and so on. Consequently new data economies (yes with an 's') appear, welcome to the Data Economy 3.0.

Some of my favourite principles behind the new data economies include the following, and please let me know which ones I missed so far!

1. A good economy is democratised: When multiple people and/or businesses contribute to data, they should have a say in what happens with their data.
2. There is a clear distribution (or rather separation) of power: When companies are required to share data, even when they are competing, the infrastructure must be owned by all. Not one party may have full control.
3. An economy works when contributions and work is valued: Value add, such as new data and enhancing data, must lead to new income which in turn is good for the economy.
4. Trustful accounting: A data economy works when everyone can trust that they receive their fair share of rewards. From a business perspective, entering the data economy 3.0 should make accounting easier, not more complex.
5. Data Control: Businesses and people should be able to decide where the data resides, on their own servers, fully distributed or perhaps even mixed. They should also be able to say who gets access to data, and who does not, control is in the hands of the data owners.
6. Facilitating 4IR technologies: As virtually each 4IR tech is data driven, the Data Economy 3.0 enables anyone to provide data securely and fairly to this new technology. 4IR tech depends on the data that is coming out of the Data Economy 3.0.
7. Participative even at a small scale: Distributed Cloud Computing for example enables anyone to provide a little bit of compute power to train an AI. This opens the doors to many new AI businesses that would otherwise depend on the mercy of centralised entities.
8. Accessible to anyone: The true value of data can be seen when even people with limited coding skills can gain new insights from access to data. This will lead to better research, new businesses and many unexpected benefits to anyone anywhere.
9. Economies are powerful competitors: Perhaps the most important insight is that an economy of data publishers, experts, companies etcetera can become so powerful that they become a better alternative to current centralised systems. Competing with an economy where every participant benefit from its success is extremely hard.

So one first conclusion is that we are moving from data that is platform centric to data that empowers democratic and trustful micro economies. A data economy can be formed around a specific industry (say mobility), a specific topic (say CSR reporting) and even a specific cause (say fighting extinction of animal species).

Data economies can be permissioned, when companies in data consortiums need to share data only amongst each other, or permissionless where anyone can get access to the data.

A data economy can even form when one giant dataset is managed by the contributors, who can be businesses, individuals, data professionals etcetera.

Community data

The above example is what we call a 'community dataset', imagine what happens when thousands of businesses move away from using Google, and start using Matomo. Now suddenly all that data is no longer accessible to Google, as businesses respect their visitor's privacy. And what happens when these businesses (with consent of the visitors) share their data into one Matomo community dataset? The outcome is that now these businesses and their users can monetize this data, which has not been possible before. The dataset can be managed by a DAO (democratically) and the DAO can decide for what purposes, businesses, regions the data can be used AND how to monetize the data. Each of these community data-sets then has the power to become a micro-data-economy in it's own right.

The wonders of the Data Economy 3.0!

Role of autonomous federated AI

Since we are in the midst of the 'AI wars', it is worth explaining the role and potential of AI in the context of the Data Economy 3.0 as well. Though this might seem like a dream (or nightmare?) from your future self, it is actually much closer than you might think.

Federated AI (collaborative learning) is a groundbreaking technique as it allows AI to be trained on data, without having actual 'access' to that data. An AI can be trained on a dataset and then take the 'learnings' back without taking the data back. This ensures data privacy in a much better way, as the alternative is to upload all data so that the AI can be trained on that dataset. This is perfect for the Data Economy 3.0.

Autonomous AI takes this even a step further. Imagine an AI that belongs to everyone in a data economy. It lives as an autonomous 'person' in a data economy. This AI is trained on data from a specific data economy and becomes an 'expert' in that field. Anyone who needs access to that AI, for business or research purposes, needs to pay for it. And the payment then goes directly to those who provided the training data.

An example of this could come from the farming industry (which is often highly tech driven, as this industry too is influenced by the 4IR). Hundreds of farms provide their IoT (DePin) data, pooled into one community dataset. Other businesses provide data around other measurements like soil quality, weather data, product sales, satellite data you name it. We already know that these data publishers can be formed as a consortium or as individual entities.

These data providers (a business or a person) decide to use the data from their Data Economy 3.0 to train a new dedicated autonomous AI. It is autonomous because it lives in the economy and everyone can share computational resources to train it. Once trained on all the datasets, it becomes useful for commercial purposes. Access to this AI can now be sold, and the revenue goes directly to each data provider and provider of computational power. This AI now contributes value to the economy, and this can be done autonomously.

Autonomous AI become valuable citizens of the Data Economy 3.0!

How we do it at Nuklai

At Nuklai we are building the infrastructure underpinning the Data Economy 3.0. Remember the two foundational types of technologies that I mentioned before? Well we are building them, some in-house and other technologies with other experts.

As data economies should be open, we would like you to know that we are always looking to connect with those who can add value. After all, we are playing the 'ecosystem' and 'economy' game, you are welcome to join the powerful movement. Whether you are a data scientist, Chief Information Officer, an intern on your first day on the job, academic researcher, AI builder or sceptic. When you think you can add value, then you can!

Final word; connect with me!

As 'Head of Ecosystem' it is my deep desire to keep growing the Nuklai ecosystem, and with that lay a foundation for not one, but many new data economies. Last year alone there were 6000 new AI start-ups, all using LLMs from the select few big players in the market. What they all need though is structured data, as that is needed to get the AI to make proper predictions that go beyond simple content creation. This data needs to come out of the Data Economy 3.0, so that everyone benefits.

What other 4IR technologies will we see pop up in the upcoming years? Please help me find out, I do not have all the answers! All I know is that they will be data-driven, and if you join the movement today then together we can make moves and make big differences.