Data Marketplaces: Value Capture in Web 3.0

Marketplaces are critical elements of the entire Convergence ecosystem; the element that incentivises data to be collected, shared and utilised. We now have the ability to open up the machine economy and need to think of ‘trading’ beyond the scope of human interaction. The sorts of marketplaces that are being developed in the crypto community are decentralised, automated and tokenized. These marketplaces are made possible because of the distributed ledgers, consensus mechanisms and interoperability protocols at the lower levels.

We will see the emergence of a whole host of new types of marketplaces beyond just today’s cryptocurrency exchanges like Binance or Coinbase. We are seeing the emergence of data exchanges that work with specific types of data; machine data from IoT networks, artificial intelligence data, personal data, and complex digital assets like crypto-collectables (pioneered by ERC 721 non-fungible tokens like CryptoKitties) and bots. It’s likely that over time marketplaces will expand into enabling all types of data and if that does occur we could end up with a dominant data and digital asset marketplace for Web 3.0 like Amazon for the Web 2.0. It’s interesting to think where the points of leverage will be in the Web 3.0 especially if value and data are interoperable across blockchains. Anyway at least for now, we see four types of decentralised data marketplace.

IoT Data Marketplaces

IoT data is already being collected in vast quantities, but the sprawl of devices has created a fragmented ecosystem. On the consumer side, operating system providers like Apple, Google and Amazon are attempting to leverage their dominant positions in smartphones and retail to sell more devices to collect more data. The Apple Watch and CarPlay, Google Home and Next, Amazon Echo and Dot; these are all attempts to grow their walled gardens of data. Smaller consumer IoT device makers like Fitbit, Wink, or GreenIQ struggle to collect enough data to make do meaningful machine learning to improve their products as quickly as the tech giants.

On the enterprise side, the same dynamics are at work. The internet of things (IoT) and industrial internet in the United States, Industrie 4.0 in Germany, and 物联网 (wù lián wăng) in China all promise to use low-cost sensors and big data analytics to dramatically improve productivity and usher in a new age of data-driven manufacturing. But the promise has not been realized for a number of reasons. Core to the failure has been the lack of data sharing. This lack of data sharing has been the case across all industries that are trying to utilise IoT technologies including aviation, agriculture, and utilities. The problem, as we have already highlighted, is that there is no incentive to share data because it is seen as the competitive advantage to be protected. Current data infrastructure is coarse: data is either hoarded and valuable, or shared with limited commercial viability. IoT marketplaces begin to offer new business models for the monetisation of machine data. The IOTA data marketplace, Streamr, Datum and Databroker DAO are all examples of these marketplace emerging to enable the sharing of sensor and machine data.

AI Data Marketplaces

Just like IoT data, or any data for that matter, data for AI algorithms tend to be accumulated by the largest companies. Society is becoming reliant on data, and as it applied to AI algorithms, we are facing a situation in which a select group of organisations are amassing vast datasets and building unassailable AI capabilities. With the emergence of deep learning as the most useful machine learning technique for a range of AI applications like computer vision and natural language processing, data has become like digital oil. Digital monopolies like Facebook, Google and Amazon, today get data from users for free. Every like, search and purchase feeds the learning system to further improve the algorithms; in turn bringing more customers and engagement. In value chain terms, data is supply, and AI algorithms are demand. Digital monopolies are searching everywhere for more and more data to feed their algorithms: Facebook buying WhatsApp and Instagram, Google with self-driving cars and Google Home, and Amazon with Alexa Echos and Dots.

“Traditionally proprietary data and technology have been significant defensibility mechanisms for companies. In the blockchain industry this is all open source, leading to an incredibly rapid innovation cycle, but also shifting defensibility more towards the sheer size of the community and thus the distribution power. This is an industry where increasingly users decide what technologies they want to use.” — Teemu Paivinen, Founder, Equilibrium Labs & Author of Thin Protocols

Decentralised AI data marketplaces will reduce, and eventually remove, the competitive advantage of hoarding private data by enabling anybody to monetise data. Again in value chain terms, these marketplaces increase supply. An AI data marketplace will make it easy for people and increasingly agents and bots to recommend, price and therefore find value in different types of data. A market for data will lead to more efficient allocation of data, rather than giving it away for free or not using it at all. As more and more machines, individuals and organisations upload data to sell on a data marketplace, it becomes more attractive to data buyers. As this data commons grows with more datasets, it will attract more data buyers, creating powerful network effects. More than anything, decentralised AI data marketplaces are a bulwark to the rapacious AI data monopolies that have the potential to become the most powerful organisations ever built (if they aren’t already), controlling ever-increasing numbers of industries and markets with their superior AI capabilities. It is, for this reason, we invested in the Ocean Protocol, whose mission is “to unlock data, for more equitable outcomes for users of data, using a thoughtful application of both technology and governance.”

“The aim of Ocean Protocol is to to equalize the opportunity to access data, so that a much broader range of AI practitioners can create value from it, and in turn spread the power of data. To respect privacy needs, we must include privacy-preserving compute. Our practical goal is deploy a tokenised ecosystem that incentivizes for making AI data & services available. This network can be used as a foundational substrate to power a new ecosystem of data marketplaces, and more broadly, data sharing for the public good.” — 

Trent McConaghy, Co-Founder, BigChainDB & Ocean Protocol

We also expect to see these marketplaces become ever more automated and efficient. Another of our portfolio companies, Fetch, is building a solution that uses decentralised machine learning to enable marketplaces to self-evolve around popular or valuable datasets, improving discoverability. In some senses they are embedding marketplaces directly into the ledger to truly enable the machine economy.

Personal Data Marketplaces

After peer-to-peer payments, control of personal data has been one of the most talked about applications for blockchains. This is related to but separate from self-sovereign identity and SII networks like Sovrin, in the sense that once an individual controls their own identity, they can choose who can have access to it. The same principle can be applied to other personal data. This choice puts the individual in the position of the seller and the party who wants access to the data as the buyer. Personal data is an economic asset that we currently give up in return for services. Some data is handed over consciously, like entering an email address or a telephone number; other data is captured without us knowing about it: likes, tweets, our online behaviour and other forms of digital data exhaust. The value comes (albeit it is much less understood by individuals) when different datasets are aggregated, and an individual psycho-demographic profile is created and sold to all sorts of organisations like insurers, market researchers, and political organisations. A multi-billion dollar data industry exists just to trade personal data.

Individual pieces of personal data are not particularly valuable on their own. According to the Financial Times, general information such as age, gender or location is worth just 0.0005 dollars per person. Buyers will have to fork out 26 cents per person for lists of people with specific health conditions. Genomic data would likely fetch much more. The challenge is that at an individual level, there is very little economic value. Value comes in aggregate. This is where blockchains, self-sovereign identity, and personal data wallets combine.

In today’s Web 2.0 paradigm, Google, Facebook and other data monopolists capture the profit. In the future, blockchain infrastructure, self-sovereign identity and personal data marketplaces will empower individuals. They can choose to allow Google and Facebook to use their data, or they can auction it off to get the best price. They might decide to only sell general information, but not their genomic data. Others will rent access to genomic data to cancer research charities but not insurers. New business models will emerge as buyers give sellers discounts based on aggregating family data for instance and new startups will emerge differentiating on consumer trust. Metâme is a UK-based startup working on creating a universal unit of trade enabling bundles of personal data to be packaged and exchanged. A data marketplace is not necessarily about making the most money. It is about giving individuals choice and control of how they want to invest their most valuable economic asset.

“Self-sovereign personal data marketplaces need to address two key hurdles before they can take off: 1) the need for a universal unit of trade that transforms personal data into assets which people can tangibly trade and own, 2) ensuring anonymity and then incentivising consented identifiability as new legislation like GDPR effectively calls for anonymity by default. Without solutions to these problems personal data marketplaces cannot scale sustainably.”

Dele Atanda, CEO, Metâme Labs

Digital Assets Marketplaces

The final category of marketplace we expect to evolve are digital asset marketplaces. Unlike traditional physical assets or money, distributed ledger-based crypto-tokens can be programmable. This gives them more flexibility and variety than their physical counterparts. Cryptocurrencies, or tokens designed to be a medium of exchange, are already reasonably well-defined and projects are innovating around how to create the optimal token for this use in mind with rules around supply, distribution, privacy, and other attributes being tweaked. Cryptocurrencies confer the fact that the crypto-token is a medium of exchange. Most tokens are incorrectly referred to as cryptocurrencies. This is because Bitcoin began life as a cryptocurrency and has over the last ten years become more of a crypto-asset, predominantly because of the programmed deflationary economics (Layer 2 solutions like Lightning may change this classification however). However, currencies and assets require different economic designs. Currencies need to have a high velocity; assets need to retain and ideally increase value resulting in low velocity.

Broader than cryptocurrencies, digital assets will come to include all digitals assets that use distributed ledgers to create scarcity. Today there isn’t a clear distinction between cryptocurrencies and crypto-assets, but as the market matures, it will become more evident which tokens are designed to be a medium of exchange and which are designed to be a store of value. It is challenging to be both. Ether, for example, is intended to be used as a medium of exchange to redeem decentralised services from applications. But as its price rises, it becomes more of a store of value and less of a medium of exchange as holders refrain from redeeming Ether in anticipation of value appreciation. This non-fungible subclass of crypto-assets will be designed to be collectables and derive value through exclusivity and proof-of-ownership. Tooling for this is already emerging with the ERC 721 NFTs.

We expect to see a whole new ecosystem of digital assets like in-game weapons or costumes for gaming, AI bots and virtual avatar templates, such as those provided by SEED. Virtual reality land such as Decentraland; objects with real-world counterparts like digital twins from Spherity; and even digital to physical assets like 3D printed items, many of which will be collaboratively made and collectively owned. With digital scarcity comes the ability to artificially limit supply which has up until now been almost impossible with existing digital and Internet technologies.

The possibilities are endless and we are at the very beginning of a whole new age of digital assets created, bought, licensed, rented and sold in decentralised peer-to-peer marketplaces.

This excerpt is the latest in a series from Convergence Ecosystem vision paper. Go and read the full thing here which can be read here. Or take a look at the previous excerpts which have covered core themes from the paper:

The End of Scale: Blockchains, Community & Crypto Governance

We are excited to introduce the Outlier Ventures vision of the future and our investment thesis: The Convergence Ecosystem. The new data value ecosystem see data captured by the Internet of Things, managed by blockchains, automated by artificial intelligence, and all incentivised using crypto-tokens. For a summary of the thesis take a look at the introductory blog, today I want to take a deeper look at how important communities, governance and politics will play in this new era.

The industry is rapidly experimenting with new (and old) consensus mechanisms and decision-making techniques to coordinate and govern the emerging token economy. This experimentation began with Bitcoin and spawned thousands of tokens each with different rules to encourage or discourage behaviours within the network and allocate resources. Tokens and automated decision-making tools allow for the mass decentralisation of entire industries through a distributed coordination network. These networks are birthing new types of resource allocation structures such as decentralised and autonomous organisations, pushing forward our conception of what an organisation should be.

Crypto Tokens

Cryptographically secure and digitally scarce tokens are the key innovation that makes a group of technologies into a living, breathing ecosystem.

Tokens are a native digital coordination mechanism for the Convergence Ecosystem. Until now we have been retrofitting a financial infrastructure designed for cash and cheques to the digital, software-defined era. Ever since the emergence of Bitcoin, it has been clear that distributed ledgers with automated consensus held the potential for new forms of asset and value exchange. It was not until the ERC20 smart contract on Ethereum that experimentation around digital and programmable money began at significant scale. There is now a mechanism to fund open-source protocols that would have previously struggled to raise financing because open-source lacked a business model. As Albert Wenger has noted: “Now, however, we have a new way of providing incentives for the creation of protocols and for governing their evolution.” In early 2018, we are still at the very beginning of this evolution.

Over the next year or so, we expect to see a much clearer delineation between two types of tokens: crypto-assets and cryptocurrencies.

Cryptocurrencies will be designed to be a medium of exchange and crypto-assets will be designed to be a store of value and offer utility in a digital economy. Despite the fact dominant token ecosystems have a element of both; design challenges abound when attempting to incentivise usage with digital scarcity. It is unclear if single-token systems like Bitcoin and Ethereum can provide a sustainable balance; instead it is likely we will see multi-token systems as a more effective mechanism.

Experimentation is happening at a rapid pace on both the supply and demand side.

We have tokens with a deflationary economy, scheduled inflation and others that let the community vote on how and when new tokens are minted and/or burned. That is just programmable money supply; we are also experimenting with demand-side economics: variable transaction fees, demurrage charges, interoperability, and different consensus rules. Non-fungible tokens such as cryptokitties and the new Ethereum ERC 721 NFTs will also impact demand by incorporating historical ownership creating a subclass of crypto-assets called crypto-collectables. In addition, a currently underutilized token model is the crypto-consumable, a token that is programmed to reduce in value over time using a decay or burn function. This could be a continuous decline in value like a used car or a step decline like a ticket to a live event. This sort of token design would not be a store-of-value and would be be a powerful way to increase network token velocity. Our head of cryptoeconomics Eden Dhaliwal is working with Imperial College London and our portfolio companies to experiment and design sustainable token ecoomies.

Today the industry is focused on the initial distribution of these tokens in generation events. But the initial distribution is just one stage of building a sustainable ecosystem.

Token distribution schedules will become more sophisticated over time to include staged releases like traditional equity fundraises and mechanisms such as airdrops or token faucets. Continued network engagement will separate successful networks from unsuccessful ones. 2018 and beyond will show that the much of the ICO class of 2017 was prepared for initial distributions but underprepared for sustainable growth and utility. It must be remembered that prior to 2017, tokens were distributed to the network in exchange for utility; Bitcoin distributes Bitcoin as a reward for the secure clearing and settling of Bitcoin transactions. By giving away the majority of tokens upfront, many 2017 ICO projects are left with few tokens to reinvigorate demand later down the line. Most projects will fail, but the open-source nature of the ecosystem means learnings and code will be available to all. We can learn and build faster than ever. Unlike economic modelling or theory, the industry is testing economic theories in real-time with real money. It is the greatest experiment in socio-economics we have ever seen.

Tokens are the first native coordination mechanism for the digital and now machine economy.

We expect tokens to be issued at each layer of the stack to incentivise behaviours within each particular network and to connect with the broader ecosystem through a series of exchanges and interoperability protocols. The model would be similar to today’s global economy in which each nation issues and uses their own currency within their own borders and trades foreign currency with other countries for products and services that it needs. If Bitcoin is indeed the digital store-of-value in the same way gold is the physical store-of-value, it is likely we will see a digital hierarchy of money emerge with Bitcoin as an apex token, protocol tokens like ethereum, NEO and CARDANO Labo below Bitcoin, and utility or application tokens below the protocol tokens. As the Convergence economy develops and core infrastructure is developed, tokens will become increasingly liquid and frictionless leading to extraordinarily complex economic dynamics.

Communities & Governance

Tokens themselves are simply a type of value instrument, the rules under which these instruments are generated, distributed and managed are decided by community members through agreed governance rules.

These governance rules are set and decided by the community members using different forms of decision-making. For protocol tokens like Bitcoin, Ethereum et al., governance includes decision-making on changes to the network. The explosion of tokens and blockchain-based networks has led to a renaissance in thinking about governance, especially decentralised governance.

We have the Bitcoin network with a strong libertarian value-system valuing decentralisation above all else. And therefore there is a separation of ‘powers’ between developers, miners and users; no one stakeholder group can ‘force’ a decision on the others. This results in a very slow-moving but stable network. Ethereum, while still aiming to be a decentralised network, does not have quite as strong libertarian streak but does have more leadership with Vitalik Buterin who is often able to push through changes because the community follows his lead. See the 2016 summer fork to return funds lost through the DAO bug.

New projects are experimenting with automated governance in an attempt to avoid messy human decision-making.

Tezos is hoping to enable governance to be ‘upgraded’ through community voting. dfinity-network is doing something similar but allowing retroactive changes to the ledger. These types of ‘on-chain’ governance as they are known are still technically immature and open up a whole new attack vector. Other projects like Augur and Gnosis are testing futarchy, a type of voting model in which the community defines a set of values and then prediction markets are used to decide which decisions will maximise those values.

We are also seeing exciting experiments with curation markets and reputation staking from projects like Colony and @Ocean_protocol. This type of decentralised and automated model is extended further with decentralised autonomous organisations (DAOs). In these sorts of organisations, all decision-making is offloaded to smart contracts and decisions would be automated based on the rules encoded in the smart contracts. One of the first examples was of course TheDAO, a DAO for venture funding, that was never able to allocate capital after a bug was exploited. Other live examples include Dash, a privacy-focused cryptocurrency; Digix, a gold payment system project; and Aragon, a platform hoping to provide the entire governance service for other token projects.

The end-point of blockchain-based automation will come through AI DAOs as articulated by Trent McConaghy These theoretical organisations will be managed and owned by AI algorithms enabling AI to interact in the economy by earning and spending tokens. An AI could own a fleet of self-driving vehicles, charging fares which it then uses to pay for maintenance, tolls, insurance, and taxes.

Blockchains and tokens will be issued, distributed, governed and owned in increasingly diverse ways. Governing models will evolve and we are likely to see an industry with multi-types of governance each co-evolving around the belief-systems of the community they serve.

Bitcoin will remain staunchly libertarian; Ethereum has more of a central leadership which appeals to pragmatic developers; and self-sovereign identity underpins the value-system of the Sovrin Foundation blockchain. We will soon see more projects with social democratic values that prioritise wealth redistribution through ‘network’ (read: State) intervention or pre-agreed taxation rules. Others will prioritise ethical and environmental values with green-friendly policies that use non-consumption based consensus mechanisms (eg Chia) and focus on common-ownership and resource sharing.

“The Convergence Ecosystem should support a diverse range of different governing models that support different communities. There is no optimal model of governance; only a perpetual tension to maintain alignment amongst stakeholders.”

We have millenia of literature exploring politics and governance, everything from Plato’s five regimes to John Locke’s libertarianism to Jeremy Bentham’s utilitarianism. Philosophers and political scientists will never settle on an ‘optimal’ governance model because ‘optimal’ can only exist for individuals in limited contexts never for society at large.

As with almost all information and communications technologies that have come before, blockchain technology was born decentralised.

Bitcoin with the first blockchain implementation was a libertarian movement created as a direct reaction to a centralised financial system. Early adopters shared this value-system. As more and more blockchains and tokens are created, the industry attracts an audience with different belief-systems. As it continues to mature, different communities will have unique objectives and priorities that will require specific design trade-offs. The financial community requires more and faster transactions and will sacrifice decentralised consensus to achieve that, as can be seen with Ripple and it’s XRP token. The healthcare community must adhere to privacy regulations and so will require more privacy than public blockchains currently afford. The ecosystem will support a variety of communities using different governance models with differing levels of decentralisation and automation depending on the values of the community and the needs of the market.

We are in the very early stages of understanding how to design token economies and the governance models that support them.

As an industry, we must be more supportive of new ideas and implementations. It is not a zero-sum game in a growing market. Some tokens, communities and governance experiments will fail. Let’s learn quickly from their failures and compound learnings.

The biggest advantage the decentralisation community has is momentum and the brightest minds from around the world are working together to solve tough problems. Communities will co-exist and thrive. Let’s be inclusive and supportive.

For more on how crypto-communities and crypto-tokens will integrate with the Internet of Things and Artificial Intelligence, read the full paper here.