Disrupting the Disruptors

Using Decentralized Technologies to Build a Global Data Commons

First published on Internet of Business — Link

We have a massive data problem. We’re creating and collecting more personal data than ever, but it’s stored in insecure and private databases. Despite the original decentralised design of the Internet and the hope of peer-to-peer communication; digital information is anything but peer-to-peer. Data is most useful when it is close to hand and in one place. As the Internet and corporate IT networks evolved, it made sense to find as much data as possible and secure it in one place. This led to the silo effect where companies and even departments inside companies found it technically challenging to share data. Expensive consulting fixes for corporate networks and application programming interfaces (APIs) for Internet services have created a more collaborative environment but in many cases, but the fact is, data hoarding is easier than data sharing.

Privacy laws and data protection legislation also have a chilling effect on data sharing. The Health Insurance Portability and Accountability Act (HIPAA) in the US or the Data Protection Act in the UK are designed to protect consumer rights, but the trade-off is in sharing of data. These regulations are complicated, and it is better to be safe than sorry from a regulatory perspective. So people err on the side of caution and don’t want to go through the hassle of opening up data to other parts of the organisation or the public. The downside is too high for the relatively intangible upside of collaboration.

Even when sharing is culturally encouraged, technically possible, and legislation is favourable, today’s infrastructure makes it almost impossible to earn money from sharing data. The best that happens is that developers or citizens get free access to data. There is no market for data; price isn’t used as a coordination mechanism to incentivise data buying and selling. There is no easy way to get paid for published data and licensing of personal data is almost non-existent. Some content can be distributed using open-source or dual-licensing arrangements, but in most cases licensing is costly, difficult to enforce and inefficient.

New Data Infrastructure

Public blockchains are in many ways worse than existing databases. They are slower, have less storage, use more energy, and are less private. But these are design choices made to improve one feature: censorship resistance. Public blockchains aren’t owned or managed by one Government or company that can choose who views or uses it. This is what crypto people mean when they say blockchains cut out the middleman. Governments have traditionally had the ability to censor information and communication; but today Silicon Valley tech monopolies do on a global scale. Twitter, Facebook and Google have all come under fire recently because of their decisions to limit freedom of speech. If you control a network you pick and choose who uses it. This is too much power for a single entity.

But public blockchains are the ideal solution for a public data utility. We now have the tools to ensure no single entity controls data. With all communications, money, and health becoming digital; data infrastructure will be too valuable to be controlled by one nation or company. In fact, for individuals and society more broadly, global data infrastructure, just like the Internet, should be a public good. Never has so much data been available for collection and analysis. And everyone wants it. As sensors are embedded in everyday objects, and we move to a world of ubiquitous computing, everybody is fighting for who ‘owns’ the data. This is yesterday’s war. Public blockchains offer an open-source, decentralised, shared database that anyone can view and interact with based on programmable rules.

As we start 2018, we are seeing the emergence of this new data infrastructure. We aren’t there yet, we still need to process more transactions, at faster speeds and use less energy in doing so. Data needs to be private, stored in an accessible way, and shared across different blockchain flavours. We also need a way for individuals, organisations and machines to buy and sell data in a marketplace. The storage and access to data is important, but it will be the data marketplaces that finally provide a business model for data creators. There will finally be a way for people and machines to make the most of the data they collect. A marketplace provides an economic incentive for the more efficient allocation of data. Individuals can sell it instead of giving it away for free; organisations can monetize it instead of letting it sit idle on databases; and machines can buy and sell data automatically to increase their utility. In my view, a peer-to-peer marketplace for data is the second most important idea to come from the blockchain industry after peer-to-peer electronic cash.

“The seed of disruption has been planted. Why allow yourself to be sold for nothing when you can get paid?”

The End for Data Monopolies

2018 will see the beginnings of this global data sharing and monetisation network. Data creators will begin to earn money from uploads, likes and retweets. This is a far more profound change than it may seem. Disruption has typically come from startups offering seemingly inferior products that serve a niche which is underserved by the incumbent. Blockchain-based networks won’t just disrupt particular companies; they go much further, they disrupt a digital norm: the existing assumption that we should be giving away personal data for free. Digital monopolies including Facebook, Google and Amazon, 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.

Blockchains and decentralised public infrastructure change the game. Blockchains reduce the value of hoards of private data. It makes proprietary datasets much less valuable because as more and more machines, individuals and organisations use a public data infrastructure, a global data commons becomes more attractive to data sellers. As this data commons grows with more datasets, it will attract more data buyers, creating powerful network effects. In other words, data becomes more of a commodity; and it is no longer the source of value in and of itself. Firms that control supply — data — no longer dominate markets.

The point of value capture in the value chain will change from data to brand and trust.

As data becomes less valuable, the customer relationship becomes ever more important. Startups and incumbents alike will compete for customers’ data based on trust. The global data commons will mean individuals will choose where their data is sold or rented. This global data commons will at first attract individuals that care about privacy and self-sovereign data. Machines will soon follow as machine operators and owners look for new revenue streams. Some organisations, especially the public sector, will be attracted by the non-corporate controlled nature of the decentralised infrastructure as well as the cost and liability reductions in not storing consumer data. Smaller organisations and startups will sign-up to access standardised data that would otherwise take too long or cost too much to acquire.

Today, data is siloed with no business model for creators to monetise it. Blockchain technology and other decentralised infrastructure are emerging as a new data infrastructure to support machines, individuals and organisations to get paid for the data they generate.

This will lead to the downfall of digital monopolies whose power rests on the collection and control of more data than anyone else.

Blockchain-based data infrastructure, including data exchanges, will commoditise data and help realise the vision of a global data commons.

“Disruption comes in many guises, for Google and Facebook, disruption isn’t from some upstart they can acquire: it is from a centralised model of data ownership to a decentralised collective model of data sharing.”

Disrupting Tech Monopolies & AI Tycoons — Part 2

Blockchains combined with artificial intelligence is more than just a technical innovation: it’s an economic paradigm shift 💰💰💰

This is Part 2 of Disrupting Tech Monopolies & AI Tycoons — Part 1 outlines how we will get here.

>>Blockchains combined with AI will create the conditions for disruption of platform monopolies>>

>> As data stops being a competitive advantage, powerful token-driven network effects will lead to AI agents using blockchains to accumulate tokens>>

>>This will lead to profound questions about the how we govern non-human entities in the economy and society. 🤔 🤔

End of AI Platform Monopolies

So, now we have a global data sharing and monetization network

Right, so where were we? Oh yeah, we now have a global network of interconnected blockchains and DLTs that share value seamlessly with easy-to-use data exchanges (See Part 1). Hopefully, as the industry begins to focus on usability and user design, we will be in a world in which anybody can publish data with a press of a button or voice command. Payments in Bitcoin or other tokens are seamless and automated based on rules coded into smart contracts. For the average user, all they have done is agreed to conditionally share data, as they do today with Facebook and other systems, and next thing they know they have tokens to spend however they want. They can convert to a national currency or merrily purchase their preferred goods and services.

All that matters today for AI platforms is data…

How does this lead to the end of AI platform monopolies? Well in 2017, the only thing that matters is data. Platforms like Google, Facebook, Baidu collect data to feed their AI algorithms (specifically their deep learning algorithms) improving their products. More data improves the products which in turn brings more customers and engagement which in turn generates more data.

When AI is the driver of product improvements proprietary data are the most valuable asset for platforms. In fact, access to proprietary data sets is one of the most important assets for an AI startup. The way to think about it is data is the supply and AI algorithms are the demand. And deep learning models are hungry.

But hold on a moment, blockchains aggregate and commoditize data. That means…

Here is the knockout: blockchains aggregate the supply side for free (almost) for all. Of course, there will be some transaction fees and other friction points, but compared to existing data infrastructure an open, shared data layer essentially commoditizes data. Or at the very least makes proprietary datasets much less valuable.

But that means control of data is no longer the leverage point in value chains…

Firms that control supply — data — no longer dominate markets. Data stops becoming a moat and a competitive advantage. Now the demand-side becomes the most valuable place in the ecosystem. This is where the customer relationship is won with trust. Well, trust, and a simple, easy to use interface, maybe a conversational or voice UX. The only thing that matters in 2020: The customer relationship. (Side note EU’s General Data Protection Regulation, or GDPR, will reinforce this)

Beginning of Blockchain-enabled AI

So we have this global shared data layer right…

A second, a longer-term implication of a global shared data layer is blockchain-enabled AI. Agents (not even particularly intelligent agents) can use blockchains as a ‘substrate’ as Fred Ehrsam has put it in the past.

Deploying and using agents on blockchains rather than using proprietary tools and platforms like Facebook Messenger will be more attractive to developers, users and regulators.

Well developers are going to love it…

For developers, first, they have access to a vast amount of free (on public chains anyway) and structured data, data that they would never be able to buy or generate themselves at first. Second, they have structured and high-quality data (right now, just transaction data, but increasingly all sorts of value store and exchange). Third, native automation tools in smart contracts and hopefully very soon production sidechains make it easier to build reasonable agents that can perform reasonably complex actions. Finally, developers and companies that deploy agents have a native payment channel to be paid almost immediately based on all sorts of conditions like usage or user utility. The business models with tokens and smart contracts are not limited to up-front payment or a paywall. All sorts of new business models will be available for experimental developers.

Users will love it, too. They can get paid just to use agents…

Users benefit because unlike any other environments, they will have direct access to token capital, investment and real interest in the system. When users use a Facebook messenger bot, they get some utility. When they use an agent on a blockchain they can be rewarded or paid with tokens. Depending on the token economics a user can ‘own’ a stake in the agent or company behind the agent. The more the user uses or evangelises the product, the stronger the product and underlying blockchain gets. Network effects with a direct monetary reward thrown in. In a sense, a user is no longer a passive consumer of a service; they are a stakeholder. This model begins to look more and more like a digital cooperative. (Something we are actively exploring at Outlier Ventures with the tokenization of Botanic Technologies’ bot platform, a project named SEED that allows the fair exchange of information between AI and people)

Regulators will love it the most, they might even force data and AI agents to use blockchains…

The last stakeholder, and potentially the deciding factor will be regulators and Governments that demand some element of control or access to AI algorithms. The public and political tide are turning against technology companies. Certainly many Governments around the World are waking up to the power amassed by large US-based tech firms through their exploitation of data. Without overselling it, it seems to me that an open-source, auditable data structure would be an ideal technical solution for regulators that want a window into AI decision making and data used to train models. This would at the very least allow scrutiny of training data to check for bias as well as potentially providing an audit trail for exploration if an agent makes a bad decision. It’s not a leap to imagine regulators actually mandating the use of either a public blockchain or demanding a node in private networks for audibility of AI.

So now we have the perfect environment for autonomous agents…

If this scenario plays out you have more developers, more users and happy regulators. There are many different descriptions, I like Autonomous Economic Agents (AEAs), these new types of decentralised AI are the logical next step when autonomous agents start using blockchains (something FETCH.ai, an Outlier portfolio company are working on). The level of human involvement with the agents will vary; some AIs can be managed by traditional organisations, others will be managed by decentralised autonomous organisations (DAOs). Regardless of the human involvement, the fact is AIs will be accumulating tokens (seen another way, wealth). For example, an autonomous vehicle can be paid in tokens for rides and can pay for re-charging and servicing with tokens. Or an AI DAO could manage a neighbourhood distributed energy grid in which energy is exchanged using smart contracts based on real-time supply and demand.

Cool yeah, this sounds like a pretty big deal…

I don’t think many people have truly thought through the implications of this. A non-human and non-human controlled entity will have the ability to acquire resources and wealth. When people talk about exponential growth, this is exactly what they are talking about. Society and politics are simply not ready to even begin a discussion about these sorts of issues. Can an autonomous agent generate wealth? What is the optimal level of taxation that doesn’t act as a disincentive to activity? We already have enough trouble collecting taxes as it is, how and who will collect taxes from an AI DAO?

Blockchain-enabled AI might seem pie in the sky. But unlike say artificial general intelligence (AGI) we know exactly the problems that need to be solved to bring this vision to reality. There are already rudimentary versions of these agents available today. For more on AI DAOs you must read Trent McConaghy’s AI DAOs, and Three Paths to Get There.

Yea it’s a big deal alright, possibility an economic paradigm shift…

Blockchains combined with artificial intelligence is more than just a technical innovation: it’s an economic paradigm shift. The political philosophy written in next 10 years will be as important as the socialist and labour movement of the late 20th century.

Thanks for reading 👍. If you enjoyed it, please hit the 👏 button and share on Twitter and Linkedin. Honestly though, Ev Williams, surely tokenizing claps is the perfect business model for Medium?

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This is a working thesis and an high level description of the work we are doing at Outlier Ventures. I am looking for feedback so please tweet me Lawrence Lundy. The thesis can certainly be improved upon. I am particularly keen to explore the potential impact of improved unsupervised learning algorithms and reinforcement learning on the need for large data sets. If large data sets are no longer required the outcome would also be that data becomes less valuable which serves to reduce the value of data but wouldn’t enable blockchain-enabled AI.

Thanks to Aron Van Ammers, Joel John & Jason Manolopoulos of Outlier Ventures; Jeremy Barnett a Barrister at St Paul’s Chambers; Omar Rahim of Energi Mine; Toby Simpson of FETCH.ai (an Outlier portfolio company); Mark Stephen Meadows of Botanic Technologies (an Outlier portfolio company) for reviewing and providing valuable feedback. Also to Trent McConaghy for driving and pushing forward the thinking on AI DAOs.

Disrupting Tech Monopolies & AI Tycoons — Part 1

Blockchains & Artificial Intelligence is not just a technical innovation: it’s an economic paradigm shift 💰💰💰

>>Blockchains combined with AI will create the conditions for disruption of platform monopolies>>

>> As data stops being a competitive advantage, powerful token-driven network effects will lead to AI agents using blockchains to accumulate tokens>>

>>This will lead to profound questions about the how we govern non-human entities in the economy and society. 🤔 🤔

Data is siloed…

It is almost banal to say it, but as a society we have a data problem. Most of the World’s data is held on private servers. The client-server architecture of the Internet and the design of corporate IT networks has resulted in data being hosted and stored on private and centralised databases. Lucrative consulting businesses sprung up to help organisations connect systems and try to make it easier share their data internally. Open Application Programming Interfaces (APIs) have gone some way into opening up data externally, especially in the public sector, but nevertheless these fixes are typically forced upon organisations. PSD2 is supposed to force banks to open up their data but they are doing their best to wriggle out of it. See Chris Skinner’s blog here.

Regulation and data privacy further limit sharing…

Even when organisations might be set up to share data and have a culture of sharing and collaboration, privacy laws and data protection legislation has had a chilling effect on data sharing. The Health Insurance Portability and Accountability Act (HIPAA) in the US or the Data Protection Act in the UK explicitly state what data can and cannot be shared. But these are complicated policies. The technical difficulty of implementing data policies, combined with the degradation of user experience those implementations produce, make IT systems costly, inefficient, and unpleasant to use. On top of which the security theatre that surrounds them only adds to the insecurity of participating with such systems. It’s just not worth it for people to go through the risk and hassle of sharing data.

It’s also really hard to make any money from sharing data…

Even when sharing is encouraged internally, technically possible with Open APIs, and legislation is favourable, current data infrastructure makes it difficult to monetise data. The best that happens is that external developers or citizens get free access to data. Lovely stuff for the user of the data, not so much for the publisher. There is no good way to get paid appropriately for published data. Some content can be published using an open-source license, sure, and attribution is great, but it doesn’t pay the bills. Dual-licensing for software is possible. See Oracle’s MySQL database which is dual-licensed under a commercial proprietary license and under the GPLv2 license. But in most cases licensing is costly, difficult to enforce and inefficient. Licensing of personal data is officially non-existent. Despite that in developing countries companies make money from this value. Around the world doctors use Facebook’s WhatsApp to send medical reports, nurses use Gmail to provide remedial advice, and that data, while not licensed, is published to advertisers as users uncaringly share the data.

So basically there is no business model for data sharing…

The fact is today there is no rational economic incentive for individuals to do anything other than give data away for free and for corporations to hoard it. If only there was a solution…

Blockchains are terrible databases, stop going on about it…

First and foremost, despite my clickbait-y headline I want to get this out of the way: public blockchains are in most ways worse than existing databases. They are slower, have less storage, are extremely energy-inefficient and in most cases less private (although zero-knowledge proofs 👏, self-sovereign identity 👏 and Masked Authenticated Messaging (MAM) 👏 will help this). But these are design choices are made to improve one feature: decentralisation. By decentralisation I mean the elimination of a central administrator which leads to extreme fault tolerance and increased data integrity and tamper-evidence. The removal of centralised control and vulnerable centralised data repositories has trade-offs which make most blockchains unsuitable for a ton of use cases that have been spoken about. But in cases where security and tamper-evidence is more important than throughput, speed, capacity, and stable governance, well then public blockchains are well worth exploring. For more on this Adam Ludwin of Chain explains it better than anyone in this post.

Okay, so it’s more secure, but nobody cares about security…

So the question becomes: how important is security to individuals, corporates and Governments, right? The bull case for blockchains is that it matters a lot and it will matter more in the future. If security continues to be an afterthought, well existing databases are cheaper, faster and more convenient, so why bother with blockchains at all?

Well, I tend to believe that security will become more important. Things like the Yahoo! or Equifax hacks certainly shine a light on the vulnerability of centralised data providers but tbh I really don’t think individuals are going to demand change. People are going mad for Amazon Echos and Dots and sticking them in every room, very few people are asking: what data is actually being collected? Where is it being stored? Is it encrypted? How can it be combined with other datasets? Security and data protection matters far more to business and to Government and the so-called Internet of Things will force the change.

Blockchains will actually help manage the sharing of data instead of fighting over it…

Never has so much data been available for collection and analysis. Connected cars are throwing off vast amounts of data, the challenge is that every single stakeholder wants access for their own purposes: car makers want it to improve the driving experience; tire makers want it to see how their tires perform; City administrations want it for traffic prediction; and software makers want it to improve their self-driving software. As sensors are embedded in all sorts of everyday objects, everybody is fighting for who ‘owns’ the data. This is fighting yesterday’s war. Blockchains can provide an open, shared data layer in which all stakeholders have access to data.

So blockchains will actually be quite useful in securing and sharing data…

Sure, not every bit of data will need a fully decentralised blockchain with proof-of-work. In most cases a simple distributed ledger with a Merkle tree will suffice (see DeepMind Health Verifiable Data Audit). Much of the data could even be stored off-chain with just links to the on-chain hash. Regardless of the blockchain flavour, cryptographically-secured distributed ledgers offer a better alternative than centralised databases. Of course, an assumption here is that blockchains don’t suffer the familiar fate of incompatibility by competing blockchains. The community does seem to be fully behind blockchain-connecting projects like Polkadot, Cosmos, Atomic Swap and AION. These services combined with zero-knowledge proofs mean data can be shared privately on public ledgers. At this point, we are close to the ideal of a globally shared database with easy and, ideally, public permissions.

Add in data exchanges…

Now, the final piece. Data exchanges like the Ocean Protocol bring together data buyers and sellers (also including bots and devices). As explained, today data is either given away for free or sits underutilised because people and organisations have no way to monetise it. A blockchain-based data exchange can enforce data quality standards, ownership and usage rules, and pay sellers to rent or sell data. A data exchange provides the missing component to a shared ledger: a business model. People and organisations can easily earn money from their data.

Now we have the infrastructure to share and monetise data…

Sure, people won’t just stop using Google or Facebook tomorrow. The value they provide is far too great. But these new networks will change the conversation. The public will begin reading news stories about how they can be paid when people download their pictures or paid when they upload their smart watch data.

The seed of disruption has been planted. Why allow yourself to be sold for nothing when you can get paid?

If this piqued your interest and you want to know more about the implications Part 2 is available to read here.

Thanks for reading 👍. If you enjoyed it, please hit the 👏 button and share on Twitter and Linkedin.

Thanks to Aron Van Ammers, Joel John & Jason Manolopoulos of Outlier Ventures; Jeremy Barnett a Barrister at St Paul’s Chambers; Omar Rahim of Energi Mine; Toby Simpson of FETCH.ai (an Outlier portfolio company); Mark Stephen Meadows of Botanic Technologies (an Outlier portfolio company) for reviewing and providing valuable feedback. Also to Trent McConaghy for driving and pushing forward the thinking on AI DAOs.

Interview with Lawrence Lundy: Blockchains, Tokens and Convergence

Interview from Blockchain Live Event in London on 20 September

Q1. As Head of Research and Partnerships at one of the first Blockchain-based businesses in Europe, you are clearly heavily invested in Blockchain Technology, but where did you first encounter Blockchain and Distributed Ledger Technology? What about this technology interests you the most?

I was first introduced to Bitcoin back in early 2013 or so and saw the huge potential of a crypto-currency. At the time I had just started work as a mobile analyst and didn’t track developments as almost most of my clients were Fortune 100 companies and few were interested. In 2014, I began to write more and more about Bitcoin, the underlying blockchain and its applicability across markets to provide an alternative to trusted third-parties.

It was not the technical elegance of Bitcoin (although it is) but rather the social and political implications of math enforced decision-making and trust that fascinated me. I thought that if you could automate monetary policy, what else could be automated? This has led me to explore the ideas around distributed autonomous organisations (DAOs), automated governance, futarchy — the idea of using markets to make decisions, and most excitingly the idea of tokenized digital co-operatives. I think that tokens offer the potential to change the hierarchical design of the firm; shareholders, management, and workers. With tokens, workers can be shareholders. Co-ops do this today, and startup employee equity pools do this on a small scale. With tokens, the co-op model could potentially outcompete the traditional firm offering greater rewards for talent.

I do not think there is a more exciting field to work in today; essentially asking the philosophical question: how do we build sustainable economies? Our most recent work called Community Token Economies is an attempt to do just that. Read more here. We are also actively exploring the ideas behind digital co-operatives and building a community around the idea of network cooperativism.

Q2. Your work around Blockchain seems to have a focus on new and innovative applications for the technology — how do you keep ahead of the curve in such an innovation focused industry? What does it take to be innovative with all of the surrounding noise?

It is an ongoing challenge, and increasingly so with the mania around token sales. There is much more noise than signal today, but we have always sought to take a macro view of the industry. The best way to find insight and identify investment and partnership opportunities is to look at the intersections of technologies, as well as studying history and politics.

Ultimately, we are in the midst of the digitisation of the information and communication, and distributed ledgers, the internet of things, 3D printing and artificial intelligence are all part of the larger theme. You need to look back at the invention of the telegram (not the app), the telegraph, radio, the telephone, television and the Internet to help inform your thinking for blockchains. Bitcoin and blockchains are not the first decentralisation technology promising to shake up power structures; it is just the latest. History doesn’t repeat itself, but it does rhyme. So I try to understand the patterns.

Q3. Smart contracts are one of the more widely touted applications for Blockchain, and one in which you have a significant amount of interest — where do you see their use heading in the future? Do they have the potential to reshape industry on a massive scale as the hype seems to suggest?

All technologies go through a hype cycle as people first spot the opportunities and then see the challenges of getting a working product to market. Smart contracts are no different. But as a technology and as a legal construct (if it can ever actually be one) it is extremely early. The underlying networks that these smart contracts run on — Ethereum, QTUM, EOS, Tezos, Bancor, Aeternity, and Waves — are all at different levels of stability and security.

At an abstract level, a program that automatically processes reasonably complex transactions can bring massive system-wide efficiencies and cost reductions. In the real-world however, you encounter all sorts of legal challenges around legalese, disputes, resolution and enforcement. It is likely that when networks are mature enough to handle interacting and connected smart contracts, they will mainly be used as an extension of back-office automation rather than a replacement for lawyers. In the medium-term though much legal work is relatively simple templated contracts and opportunities abound for automating and lowering the cost of legal services.

Q4. Blockchain thus far it seems fair to say has been focused on the Finance industry. With the technology spreading into other industries, and this being an area of interest for yourself, are there any other industries you think are particularly ready for Blockchain application, and why? What makes an industry compatible with Blockchain technology and will we see the emergence of new industries as a result of Blockchain?

Bitcoin was released around the time of the 2008 financial crisis and the early interest from the libertarian right was as a replacement for the banking system. Bitcoin was designed specifically as digital cash and therefore the focus of the media and public for many years was in the finance system.

However, one of the key components of Bitcoin was the underlying transaction ledger and how this was maintained and updated using a proof-of-work blockchain. A shared transaction ledger (note: not a blockchain specifically) has applicability for virtually any transaction of value across a vast array of human and machine activity.

We are still at the stage of development where we are picking apart of the different elements of Bitcoin and testing new combinations of consensus algorithms and distributed ledgers to meet the needs of different use cases. For example, a solution for machine-to-machine transactions has very different throughput and latency requirements than Bitcoin.

Distributed ledgers and blockchains are horizontal technologies not limited by industry. As soon as you conceive of value as broader than money, you can begin to see the possibilities of personal data exchange, or bill of lading for shipping, or provenance of goods. You can argue that we already have the first blockchain industry: bitcoin. Or maybe even two: Ethereum and token issuance. The legal and compliance issues around tokens are certainly a new industry for securities lawyers. However, more broadly, I do not think blockchains will create new industries, other than blockchain SaaS and consulting, instead all industries will utilise the benefits in their technology stack.

Q5. You have a nuanced series of interests within and surrounding Blockchain — for example 3D printing and Robotics. Could you tell us how Blockchain could influence some of these more niche industries and when you think that will happen?

We spent almost all of 2016 developing our investment thesis called Convergence. The original paper can be read here. We take a systems approach and see Bitcoin, blockchains and DLTs as part of a broader macro shift from Web 2.0 to Web 3.0. Our thesis is that blockchain technology when taken broadly to include innovations in decentralised storage, compute, and automation such as smart contracts, oracles and tokens will form a decentralised infrastructure that enables other technologies like machine learning, robotics, IoT, and 3D printing to combine and converge.

We are investing in companies like: uVue, focusing on providing a decentralised software layer for autonomous economic agents primarily in the mobility sector. Botanic who are providing multi-modal trusted personality interfaces to artificial intelligence. And IOTA building a new transactional settlement and data integrity layer for the Internet of Things. All three have existing corporate clients with products today. We believe there are problems to be solved today using decentralised infrastructure and toolkits. This isn’t a 5 year time horizon. These products are being bought and sold today.

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The Token Ecosystem Landscape Map

Making sense of the token mania

At Outlier Ventures we have been thinking about tokens for well over a year now. We published our first report: All You Need to Know About ICOs in November last year. To quote:

“In time tokens may come to represent a fundamental shift in the structure of companies, but already network tokens are having an impressive impact by providing a new business model for open-source and protocol development.”

At the time, $240 million had been raised through token sales, the majority of which from the hacked TheDAO project. From January to September this year, more than $1.7 billion has been raised, overtaking VC funding. This will almost certainly reach over $2 billion by the end of the year. What was a curiosity at the end of 2016 has become the de facto way for blockchain (even non-blockchain startups like Kik) to raise funds. Investors now even refer to equity raised as ‘old school’ raises. This is the kind of rapidly accelerating technological progress we can expect on an exponential growth curve.

We have been following developments carefully and bolstering our token understanding and capabilities. Our first token investment was into IOTA back in June; our second will be announced shortly. We became the first VC to hire a Head of Crypto-economics in Eden Dhaliwal; hired Greg Murphy to head up Regulatory and Token Compliance; and signed a formal partnership with Imperial College London’s Economics and Computer Science Departments to explore game theory and network modelling.

All of our learnings to date led us to outline our vision for the future of token sales in our paper: Community Token Economies (CTEs). This is where multiple parties join forces to realise what we have termed Minimum Viable Community (MVC) in order to achieve network effects more efficiently and rapidly compared to launching a token that at best can only be sub-scale because it can only address a small market need. The first realisation of a CTE will be announced over the next few weeks.

All of this work has been supported by Outlier Ventures Research: the blockchain startup tracker with 1263 startups; the corporate tracker with 245 corporates (to be updated); the Government & Regulation tracker (not public, yet); and our token tracker with over 500 tokens. We have an unparalleled understanding of the market development of the bitcoin, blockchains and now tokens ecosystems.

Below is The Token Ecosystem Landscape Map. 505 tokens categorised into 24 categories: Entertainment, Gambling & Gaming is the largest category with 64 startups and Charitable & Giving the smallest with 4. We have only mapped tokens that have been announced, ongoing, and completed.

More analysis around total funding, funding per category and stack development trends will follow. If you are an investor, corporate or startup interested in the CTE and want more information or analysis please contact me at lawrence@outlierventures.io.

Follow us, Enjoy and Share!

*The ecosystem map is not an endorsement of any particular token.*

Innovations in Blockchains: All You Need To Know About Crowdsales

Outlier Ventures Research has just released our latest research report titled ‘All You Need to Know About Initial Coin Offerings’.

Further to our commitment to open-source: our data (Blockchain Angels Blockchain Ecosystem Tracker — 1070+ startups and growing) and our analysis (Monthly Blockchain Market & Investment Update) to support and help the ecosystem grow, we are going to be publishing regular free research reports that investigate developments in the community.

Some key findings from the report include:

  1. 12% of all bitcoin and blockchain projects that have raised money have used a network token presale
  2. Crowdsales have raised roughly $240 million to date. TheDAO was the largest crowdfunding campaign in history raising at the peak $180 million.
  3. The debate around whether or not tokens are securities misses the broader business model innovation that network token presales are driving

In the report we look into 5 themes in the Crowdsale/ICO/Appcoin/Network Token Presale space:

  1. How terminology around blockchains, initial coin offerings (ICOs) and tokens is leading to dangerous levels of market misunderstanding
  2. Where network token presales fit into the broader crowdfunding market
  3. Regulatory challenges around network token presales & securities law
  4. Business model implications of network token presales
  5. Broader potential of tokens to enable blockchain-chartered companies

“In time tokens may come to represent a fundamental shift in the structure of companies, but already network tokens are having an impressive impact by providing a new business model for open-source and protocol development.”

As a venture builder and investment partnership, we ourselves wanted to understand the role of ICOs in the broader context of fundraising. Specifically to see if there was still a role for a dedicated equity-based crowdfunding platform for blockchain startups. Our findings, the highlights of which are broken down below, confirmed our view ICOs whilst truly revolutionary still have many risks and limitations and are best suited to very specific instances:

  • ICOs are broadly used to fund highly technical blockchain infrastructure for which only early adopter developers can understand the need and where the capital requirement is immediately high.
  • This is particularly important now private money in the VC world, especially Silicon Valley money is drying up, due to the lack of big exits.
  • The ICO seems to be less relevant where a startup is an application (or DApp) whose use-case should be clear to a traditional professional investor who can provide not just capital but an address book and vertical expertise to help make it happen.
  • The majority of startups are put off by both the legal uncertainty and additional complexity of managing so many smaller investors early on in their development cycle.

Blockchain-Enabled Convergence

First published at www.outlierventures.io

Humans often use the past as a guide for the future; this mistake often makes it impossible to adapt to our rapidly changing world. Technological progress is not linear, it’s exponential in nature, making it much harder to grasp. This means we constantly underestimate the pace of change and as software eats more industries, improvements compound as traditionally human-centric industries like healthcare, logistics and agriculture digitise. As these industries come online and capture, process and automate data; ownership of this data will define the state, market and nation over the next half a century. Blockchains are therefore one of the most significant technological innovations since The Internet and fundamental to Web 3.0. Blockchains, distributed ledgers, smart contracts and other decentralisation innovations provide the foundation for a scalable and secure data and asset management layer for the new Web 3.0. It acts as a platform to support individual rights while benefiting from the aggregation of vast amounts of data from the Internet of Things. They also ensure the benefits of artificial intelligence are shared broadly across society and do not aggregate to a few AI owners, or the 0.00001% of the population. The Internet of Things, artificial intelligence, autonomous robotics, 3D printing, as well as virtual & augmented reality

Blockchains are therefore one of the most significant technological innovations since The Internet and fundamental to Web 3.0. Blockchains, distributed ledgers, smart contracts and other decentralisation innovations provide the foundation for a scalable and secure data and asset management layer for the new Web 3.0. It acts as a platform to support individual rights while benefiting from the aggregation of vast amounts of data from the Internet of Things. They also ensure the benefits of artificial intelligence are shared broadly across society and do not aggregate to a few AI owners, or the 0.00001% of the population. The Internet of Things, artificial intelligence, autonomous robotics, 3D printing, as well as virtual & augmented reality are all converging in new and exciting ways. Blockchains will become the decentralised data and asset management layer that links the data and value from these technologies, ushering in the era of blockchain-enabled convergence.

Convergence is not a process that will happen immediately, nor be a simple and linear progression. Trends will combine at different speeds based on technical limitations, political and social barriers, as well as commercial considerations. The market dynamics will vary with industrial manufacturers and telecommunications providers leading the charge in the Internet of Things, while consumer Internet companies like Google and Facebook innovate in artificial intelligence. It is important to grasp the nuances of each market, but in doing so, it’s easy to miss broader macro-trends. The development of blockchains is a good example, as exceptionally talented developers push the boundaries of cryptography with zero-knowledge proofs and smart contracts but fail to see the implications on broader governance structures and political philosophies. These are the kind of things we have been trying to figure out since the dawn of civilisation. It is just as important in technological progress to study Plato and Hume as it is to study Von Neumann and Shannon.

As the rate of change increases, it is critical to understand these technology trends as part of a wider collective rather than as separate developments. Blockchain-enabled convergence is our attempt to capture this wide collective. The first part of the white paper explores blockchains, artificial intelligence, the Internet of Things, autonomous robotics, 3D printing, and virtual & augmented reality to understand the drivers and barriers to adoption. Part two investigates how blockchain-enabled convergence changes the trade value chain from manufacturing and design through logistics and distribution to retail and commerce, and even more profoundly changing the very governance structure of the organisation.

5 Key Themes

The Outlier Ventures white paper explores an extremely broad range of technologies and markets, yet despite this breadth, we found 5 key themes that kept coming up time and time again. These themes are not technological in nature but rather trends that will reshape markets, society and excitingly, the relationship between humans and machines.

1. Web 3.0 — The Global Trust Network

Web 3.0 underpinned by blockchains and decentralized technologies provide global trust. The core design of The Internet was enable the sharing of information. The core design of Bitcoin, and other open permissionless blockchains, is a network of trust for exchanging value and asset ownership. Web 3.0 provides trust and chain-of-ownership; the missing link with the existing Internet infrastructure.

2. The ‘Real’ Sharing Economy

New digital intermediaries have sprung up so individuals can ‘share’ unproductive assets; spare rooms on Airbnb, spare seats on Uber and spare time on TaskRabbit. These ‘sharing economy’ companies are nothing more than a new middleman sitting between a buyer and seller capturing outsized value. Blockchain-enabled convergence allows seamless peer-to-peer exchange of assets and value reducing the need for trust brokers in the middle of a market extracting economic rent.

3. The Killer Business Model: The Decentralized Data Marketplace

A blockchain-based data marketplace helps solve two major problems in artificial intelligence today, the access to data for those that need it, and monetizing unused data for those that have it. A decentralized data marketplace creates an economic mechanism for individuals and organisations to buy and sell data, reducing the incentive to hoard valuable unused data and remunerating the creators of data not just the processors.

4. The Commoditization of Logistics & Production

Blockchain-enabled convergence transforms the trade value chain. Autonomous robotics, AI, IoT and blockchains will digitise logistics and distribution reducing its importance and therefore ability for companies at this point in the value chain to capture profit. Producers can capture more of the value they create and consumers can pay less. In the long-term, technical deflation will hit the knee of the exponential curve as much of production gets commoditised by 3D printing, and virtual and augmented reality make it cheap to design and print products at home.

5. The Rise of the Decentralised Organisation

The global multinational corporation that developed to coordinate global trade is under threat as the dominant form of governing structure. New decentralised processes for business financing with Initial Coin Offerings (ICOs), incorporation, voting, payments and talent and project coordination are enabling start-ups to choose processes that are suitable for smaller, more agile start-ups rather than using an expensive corporate structure designed for large companies.

Special Thanks to Anish Mohammed, Trent McConaghy, @edcafenet, Vijay Michalik, Creative Barcode, @API_economics, David J Klein, and Ethan Gilmore of VarCrypt for conversations and contributions.