Decentralization — Why We Need Technology Infrastructure Upgrades

Wulf A. Kaal**

Abstract

The article shows that the technological precursors of decentralization require a reexamination of technological infrastructure for decentralized systems. The article examines the role of technology-based networking in the evolution of decentralization. The evolution of increased networking capabilities had real economic consequences. Platform business proliferation, the API economy, the sharing economy, and the network information economy are key examples. Similar economic consequences can be expected in the aftermath of the decentralized technology infrastructure evolution. The article concludes with a discussion of decentralized technology infrastructure upgrades that enable the evolving age of technology, business, and societal decentralization.

Key Words: Decentralization, History, Digital Assets, Decentralized Finance, Blockchain, Start-up, Decentralized Commerce, Emerging Technology, Token Models, Incentive Design, Tokens, Distributed Ledger Technology, Decentralized Infrastructure

JEL Categories: K20, K23, K32, L43, L5, O31, O32

I. Introduction

The emergence and evolution of decentralization was made possible by the increasing technology-based network capability of society. Through process innovation in the creation of products and services, disruptive techno­logical innovations facilitate exponential technological improvements that create the necessary environment for increased network capabilities of society. Technologies that facilitated increased network capability include telecommunications, the digital transformation, the internet of things (IoT), social media, cloud computing, and peer-to-peer networking, among others. The open source movement emerged out of these disruptions and continues to make significant contributions to ever increasing connectivity and increased network capabilities of society. The open source movement solidified the philosophy and ideas that created the foundation for future decentralization.

Disruptive technology-based innovation is a gateway for the increased network capabilities of society. Scientific discoveries change the existing technological product paradigms and provide the foundation for more competitive new technologies and products to emerge. By enabling dis­continuous innovations of processes, products, and services, disruptive techno­logical innovations facilitate exponential improvements in the value proposition for customers.

Technology-based networks created the historical foundation for today’s level of connectivity and network capability for the benefit of society. The historical elements that brought the levels of network connections to today’s standards include the internet boom in the 1980s in combination with telecommunications as well as the digital transformation of businesses and society that ramped up in the late 1990s. The emergence of social media and the internet of things (IoT) at the turn of the century further extended increased network capabilities of society.

The proliferation of the open source movement created a significant extension of the ideas that motivated earlier technology-based networks. The cyberpunk movement during the development and proliferation of the internet in the 1980s created an ethos of openness in the developer community. In turn, the realization in the software development community that interoperability of software means survivability, gave rise to an ethos of interoperability. Interoperability required the development of software that could work on different platforms. That evolving tradition of openness, interoperability, sharing, and cooperation for the greater good of optimized code gave rise to the open source movement. Open source developers are self-organized without a centralized coordinator, other than through the project objective itself. Collaborator and contributors rarely meet face-to-face, are self-coordinated with contributions coming from disparate locations around the world. Contributors volunteer their time to write, share, and generally support their software without monetary compensation.

The modalities of historical instances of increased network capabilities of society provide a precedent for the evolution of decentralization. While the unprecedented increased network capabilities of society around the globe is still in many ways in its infancy, the historical network capability precedent provides an outlook for the possible future of decentralization.

Disruptive innovation in the internet age creates an environment that enables ever increasing decentralization. Disruptive innovation is characterized by scientific discoveries that change the existing technological product paradigms and provide the foundation for more competitive new technologies and products to emerge. Disruptive techno­logical innovations can help facilitate exponential improvements in the value proposition for customers. These improvements typical consist of dis­continuous innovations of processes, products, and services. Disruptive technological innovation can be characterized by the emergence of completely new technologies, the new combination and applica­tion of existing technologies, and the application of new technologies to specific societal problem areas, each precipitating a significant paradigm shift for product technology or creating entirely new paradigms. Disruptive innovation exemplifies Schumpeter’s “Creative Destruction,” that is, the creation of com­petitive strength through innovation that is followed by new demand in new markets while destroying older and less competitive technologies and existing markets that are based on older and less competitive technologies.

Since the mid-1990s, the implications of disruptive technologies and innovation were becoming increasingly apparent. Disrupter startups were able to increasingly attract new lower-end consumers by of­fering inexpensive substitutes for products and then gradually move upmarket by attracting higher-end consumers. Legacy businesses had to act quickly when disrupters appear and either acquire the disrupter or incubate a competing business that embraces the disruptive technology. A market leader’s lack of investment in disruptive technologies often results in the abrupt loss of market dominance or even total replacement in such markets. Market leaders often shortsightedly refuse to cannibalize their market dominance through the use of disruptive technologies. This enables small entrepreneurial firms with no established customer base to take advantage of disruptive tech­nologies and redefine such markets.

Revolutionizing products in the past few decades that were based on disruptive technological innovation and increased network capabilities of society were typically smaller in size, lighter, cheaper, more convenient and flexible, more reliable, had better unit performance with higher efficiency, and were more user friendly than prior products. These characteristics typically require significant advances and growth in artificial intelligence and technologies including micro- or nanotech­nologies, as well as materials and component technologies. A simple example is the disruption that came with the invention of the smart phone, which allows people around the world to access information instantaneously at an unprecedented scale.

So-called big-bang disruptions typically involve increased compatibility and connectivity with existing products and services. Big-bang disruptors often offer a much cheaper product in comparison with the established products, but they are also better integrated with other products and services and are often more inventive and flexible. In the social media age, big-bang disruptors can successfully exploit con­sumers’ advanced access to product information and consumers’ ability to con­tribute to products and share such contributions and product improvements via social media and other outlets. Internet fads and products can be accessible to consumers in the entire world within a matter of days. Big-bang disrupters typically launch businesses without a foundation, using cloud computing, open platforms built on the internet, and fast-cycling mobile devices. Big-bang dis­rupters often produce multiple new products to identify which products may take hold in the market. While most such products fail, the payoff associated with the unconstrained growth of those products that succeed is substantial and facilitates and often accelerates other forms of disruptive innovation.

Several examples help illustrate the power of disruptive innovation and its consequences. Corporate history is littered with numerous examples of successful companies that drifted into obscurity after failing to embrace change. Nokia, Kodak, and Blackberry are prominent examples. All these firms collapsed after fast changes in their respective markets rendered their products/services no longer competitive.

Several core common denominators are often associated with companies that are less successful in a business environment of disruptive innovation. Such companies usually prefer to concentrate on the execution of established business models built around existing and successful products or services. Less successful companies are also often slow in embracing algorithmic technologies, data analytics, big data, and platforms. Executives with a knowledge of, and focus on, innovation and consumer experience — i.e., those individuals responsible for the initial success of a company and best placed to deliver relevancy — often find themselves marginalized from core decision-making processes in companies that focus on established products.

Less successful companies often share a myopic and short-term focus on shareholder value maximization that has led to an unhealthy emphasis on firm share price, market valuations, and financial metrics that obscure issues of relevancy. Listed companies, in particular, are prone to put too much emphasis on financial metrics, such as return on net assets, return on capital deployed, and internal rate of return. Of course, it is important to focus on financial metrics. However, it is also important to realize that an emphasis on measures that aim at quarterly earnings and short-term stock price performance can easily distract an organization from the important business task of identifying strategies that can help a firm remain relevant in the future. Budgeting is important in this regard. Successful companies are well padded for potential problems.

The disruptive change coming from technological innovation is often directly linked to the emergence of financial technology (fintech). Fintech — the intersection of finance and technology — has revolutionized the traditional landscape of many financial products and services and changed the lives of business owners. Since the beginning of the 21st century, the merging of financial services and technology has been one of the fastest growing markets, giving rise to companies seemingly overnight. Technology enables startup companies to compete with financial market leaders.

FinTech is spurring economic growth and development in many parts of the world. The introduction of technology into the once obsolete financial system meant that service providers are now taking heed of customers’ needs. The innovation of financial services via technology has created systems that are faster, cheaper and more convenient for the consumer. As a result, customers turn away from the legacy institutions that once dominated financial services. To counteract this trend, established banks and financial services providers are now turning to technology companies to innovate and improve their products and services. The joint venture between Goldman Sachs and Apple to introduce the Apple Credit card illustrates this point. Goldman Sachs appears to acknowledge that the future of banking is with the consumer market, a market it mostly ignored in the past. Fintech brings information closer to the edge and serves the consumers, it disrupts centralized structures in finance and forces the disrupted financial conglomerates to serve the consumer better. As such, Fintech epitomizes some of the core principles of decentralization.

Like fintech, the merger of the regulatory and legal markets with technology (RegLegalTech) is changing the legal and regulatory landscape and decentralizes the application of regulation in many industries. The RegLegalTech sector has evolved from support systems to fully integrated and automated services that increasingly disrupt diverse sets of industries. RegLegalTech can generally be defined as information technology services and software, as well as platforms and their applications. Since the 1970s, with the invention of the first legal databases, RegLegalTech has supported existing ways of operating and practicing law. In fact, RegLegalTech created the need for additional lawyers to evaluate the new legal materials that are made more quickly available and more easily accessible by technology. At first, RegLegalTech made law firms and lawyers more efficient in performing their activities. Examples include automated billing, document storage, practice management, and accounting software. In the early 2010s, RegLegalTech became more advanced and started to include technology that assisted legal professionals in due diligence and e-discovery processes. Since 2015, RegLegalTech has continued to evolve in unprecedented ways. Multiple startup companies and their investors have started to capitalize on technologies, and their applications are already replacing some junior lawyers and disrupting the existing parameters for the practice of law.

II. Technology-Based Network Capability

Significant factors that helped inaugurate the increasing societal trends toward decentralization include: ever-increasing technology-based connectivity and the increased network capabilities of society.

1. Telecommunication

The meteoric rise of the telecommunications market has increased network capabilities of society at unprecedented historical levels. Smartphone’s role in shaping human interaction in the 21st century has been as dramatic as it is far-reaching. Smartphones have revolutionized society in less than a decade. With more than 1 billion users worldwide and 2.5 million ever increasing apps available across Google and Apple’s digital marketplaces, smartphones are revolutionizing many markets and impact human behavior at unprecedented levels. With the launch of the iPhone in 2007, smartphone adoption rates quickly exceeded other technological milestones such as the TV, the personal computer, the telephone, and the light bulb. The smartphone outpaced the TV as the consumer technology with the fastest adoption rate, reaching 40 percent market saturation in just 2 1/2 years. Over sixty percent of internet traffic today comes from mobile devices rather than desktops, which long served as the dominant online portal. Increasing evidence exists that smartphone-enabled search engines and digitally managed contact lists are affecting how the human brain processes information. Internet-connected devices have already become a kind of external memory source for many people. The role of smartphones for societal change can also not be underestimated. Take for instance, when the Arab Spring began rippling through the Middle East in early 2011. Demonstrators and journalists alike used smartphones to gather information quickly and disseminate it. The smartphone quickly proved to be a powerful tool for social change. For the unbanked, who lack access to traditional bank accounts but who nonetheless have high rates of mobile phone ownership, the smartphone and mobile money are playing a critical role in financial inclusion. For the unbanked, the smartphone provides access to stored value accounts and a growing set of financial services that can change their lives.

2. Digital Transformation

Digitization, digitalization, and digital transformation are fundamentally reshaping business and society. Digitization generally is a reference to optimizing business and other processes by way of removing paper and removing paper-based processes through the use of electronic and digital technology. With the digitization of paper, the manual or mechanical labor that was previously necessary to process and work with paper-based processes may no longer needed. Digitization is the start of a process that may lead into digitalization, which means the use of digitized and natively digital technologies and of data. In contrast with digitization, digitalization allows the creation of new revenue and improves business, beyond mere process optimization. Digital information and a digital business culture are at the core of the digitalization of businesses. Digital transformation, in turn, refers to process innovation in combination with business model upgrades for businesses. Digital transformation often implies the fundamental transformation of a business with new capabilities, enhanced innovation, and the creation of new revenue streams.

A good illustration of a digital transformation is provided by the John Deere company.[1] John Deere built its business as a manufacturer of equipment with a more traditional business strategy and outlook. With the emergence of digitization and internet technologies in the late 1990s, John Deere was able to move from a mere equipment manufacturing business to a service and data company. Unlike so many other businesses that perished in the age of accelerating digital innovation because they were unable to let go of the past and their core business, John Deere embraced the digital transformation and created entirely new revenue streams. Through its data capabilities, John Deere became a trusted advisor to farmers and helped farmers increase their yield and optimize their businesses. Because of the new business lines coming out of its digital transformation, John Deere had the opportunity to combine its new businesses with other innovative business models from different sectors. The digital transformation of John Deere’s business culminated in John Deere’s emergence as a disruptive company that had redefined the farming industry.

The digital transformation of business and society has multiple interdependent dimensions. The information and information technology dimensions are integral parts of digitalization and its value creation. Without the transformation of digitization into information technology, the digital transformation economy where digital transformation of a given business moves to the core of that business, could not have emerged. The digitization of content was a natural precursor to the internet of things and its progeny. The proliferation of digital services in the internet of things, in turn, required a certain depth of digitalization in order for it to connect with and transform other technologies and to create new business assets.

Just like previous transformational periods for business and society, the digital transformation of business and society inaugurated unprecedented societal change that necessitated a new infrastructure. Similar to the changes instituted by the steam engine and the combustion engine during the industrial revolution, which required new infrastructure tools, such as improved streets, copper wiring for electricity, light bulbs, new laws, institutions etc., digital transformation was inhibited until the needed infrastructure was built, laws were updated, and new institutions were created.

The inherent disruption associated with digital transformation creates challenges for existing businesses. Similar to the disruptive change during the industrial revolution, the digital transformation of business began with many competing startups, inventors, and businesses, but most businesses were flushed out, resulting in only a few winners. These winning businesses made significant lasting contributions to society. Just as the inventions that empowered the industrial revolution disrupted old industries while giving rise to new ones, digital transformation provided the same disruption. Digitization was a precursor to peer-to-peer transactions at scale. Correspondingly, the digital transformation of business enabled for the first time in history a form of decentralized production at lower cost.

3. Internet of Things

The increasing connectivity in society that was inaugurated by the telecommunications industry, especially by the smartphone, and the digital transformation is further extended by the emergence of the internet of things (IoT). IoT as a phenomenon is probably best described as a giant network involving connectivity between people, people and devices, and devices and other devices. Connecting non-human devices and service providers via the internet is at the heart of IoT. Such connected devices can include anything from washing machines to coffee makers and toasters as well as components of machines, e.g. the soap box of the washing machine that may automatically order new liquid soap from a connected service provider, such as Amazon and importantly, sensors and related devices, for security, monitoring, agricultural and other uses.

The ideal typical conditions for the proliferation of IoT can be traced to a combination of factors. Connecting an unprecedented amount of devices over the internet was made possible through the proliferation of broadband internet connections and is further expanded through the emergence of 5G telecommunication networks and skyrocketing smartphone penetration worldwide. At the same time, an increasing amount of devices are being created with built-in Wi-Fi and sensors that further multiply the availability of connectivity and with it connected devices. Significantly, the cost of technology is decreasing at the same time.

Big data, generated by mobile telecommunication and IoT devices is also a significant driver of increased network capabilities of society. Being able to access and evaluate entire datasets, rather than a small sample thereof, allows researchers to understand unprecedented correlations. Improved understanding of correlations in network data, in turn, facilitates accelerated and improved connectivity. Big data in the form of digitized data that grows at exponential rates and can be captured and manipulated electronically draws on several core sources including the in­ternet of things, public records, social media, and cameras, as well as satellite tracking. Big data benefits not only include industry and researchers, but also in­crease consumer connectivity and choice through publicly available websites providing big data analyses intended to support consumers’ decision-making processes.

AI increased network capabilities of society. Many sectors of the economy are already significantly affected by the rapid advances in AI during the past decade. Most significantly, AI has the capacity to process and allocate the data generated by IoT and will help companies figure out ways to track, store, and analyze the significant increases in data that will be generated by many billions of devices. With the help of AI, the new data provided by IoT can help increase and optimize the connectivity of people to people, people to devices, and devices to devices. AI can help improve what and how people and devices should be connected because the connections serve their respective needs.

4. Social Media

Social media has increased network capabilities of society at unprecedented rates in human history. The social media-generated increase in virtual communication resulted in about one fourth of humanity interacting on social media in some capacity.

According to recent estimates, overall 2.3 million worldwide active social media users exist. The overwhelming majority of large corporate brands have two or more social media platforms. Social media has changed the way most businesses operate and run on a daily basis.

Social media facilitates a more democratic proliferation of information dissemination in society. Network effects facilitate the unprecedented expansion and proliferation of social media. Social media networks become more useful and powerful with each added user. As users interact with others, social networks become more powerful as they grow. Information sharing via social media happens at scale and creates power and influence for the creators. Social media as a means of distributing information, allows the content creators to harness that power because power is allocated to the most popular content. The longer the information is in circulation, the more discussion it generates and the greater the impact of social media. According to some estimates, the average life expectancy of a given content posted on the web is 2.6 days, compared to 3.2 days for content shared on social media, a difference of over 23%.[2]

Cross-pollination from telecommunications and the IoT has accelerated the proliferation of social media and the associated increase in network capabilities of society. Across the globe, consumers spend most time online with their mobile devices. According to some estimates, consumers in Indonesia spend over ninety percent of their time online via mobile devices, followed by over seventy percent in the USA and China.[3] Whereas technology-based disruptive innovation mostly creates challenges for brick-and mortar businesses, social media allows business across the fray to generate demand, insights, and create targeted product offerings. Traditional brick-and-motor businesses and e-commerce businesses benefit from social media alike.

Social media improves the exchange of knowledge and removes societal boundaries. For example, cross-racial dating and marriages have increased through online dating portals. Social media can help spread otherwise highly specialized knowledge shared by specialists. Ultimately, social media’s function is to incentivize people to see and respond to content. The use of social media is significantly increasing in learning.[4] It raises the level of interaction and helps create a more skilled and knowledgeable work force. Enhanced knowledge sharing, in organizations and society at large, can help eliminate silos and information privileges and, thus, removes boundaries.

Social media transfers knowledge from the edges of society into the mainstream. Because social media allows people to communicate with one another more freely, it supports the creation of influential social organizations among once-marginalized groups. Social media allows people who hold otherwise marginalized or underappreciated views to meet kindred spirits online and form groups that promote their shared ideas. When these newly formed social networks grow they can increase their influence incrementally and promote their perspectives until they become more mainstream. Otherwise invisible social, ethical, environmental, political issues can thus gain traction rather quickly. Increased visibility of these issues can transfer the balance of power on these issues from the hands of a few to the mainstream of the masses.

The increased network capabilities of society that are promoted by social media can change society’s coordination functions. Traditional modes of coordinating human behavior by way of political decision making, democratic institutions, business governance, among many others, used centralized means of information dissemination to coordinate behavior. As the information that influences the coordination of human behavior increasingly comes from the edges, the coordination of human behavior changes. Despite the control of the internet through several companies, using a more diverse set of information sources, humans can coordinate their behavior through the internet for a more diverse set of causes that would have remained marginalized in the centralized environment before the rise of social media.

The social media crowd takes over an otherwise centralized societal coordination function. Whereas in the past, product information was centrally disseminated and evaluated on consumer’s behalf, with the rise of social media, it is possible to assess products or information through the power of the crowd. For instance, when products attract a lot of shares on social media, it typically benefits sales of a given product. The consumer crowd on social media uses shares, that is, how often a given post or information was shared with their network, as a proxy for a quality assessment. On the other hand, the lack of shares for a given product can trigger consumer distrust. Product or content specific conduct on social media thus becomes a form of ‘social proof.’[5] Because the incentive design for social proof is suboptimal, the social media coordination function is still largely flawed. Decentralized technology solutions, however, can tap into the coordination function that was inaugurated by social media and improve it.

5. Cloud Computing

Cloud computing has facilitated a significant extension of the digital transformation by way of further enhancing connectivity at the enterprise level. Cloud computing is characterized by the on-demand availability of digital and computing resources, such as computing power or data storage. Contrasting prior solutions that used a local server or a personal computer to manage computing resources, in cloud computing, a network of remote servers hosted on the internet is used to store, manage, and process data. Users access these resources on-demand without direct active management by the user. Data centers provide a prominent example of cloud computing. Data centers provide services such as computing power or data storage available to many users over the internet without any direct active management or control by the users.

Historically, cloud computing began as attempts to optimize networks. While references to cloud computing emerged in computer science as early as 1996, in internal documents at Compaq, the term “Cloud computing” itself became more commonly used after Amazon in 2006 released its Elastic Compute Cloud product. The first attempts at cloud computing started with virtual private networks (VPNs) in the 1990s. Telecom companies in the 1990s used VPNs to replace dedicated point-to-point data circuits with similar quality of service but at lower costs. VPNs allowed them to use network bandwidth more effectively. Computing and telecom companies started to use a cloud symbol to denote the demarcation point between network responsibility for the user versus the network provider.

The rapid development of cloud computing has significant disruptive effects. In the future, it is hard to imagine that traditional data centers and the traditional models for delivering information technology (IT) and IT services will be able to survive or stay competitive. For companies, owning their own hardware and building their own data centers does not appear to be cost effective in the future. Cloud computing vendors will solve the computing hardware problem, leading to computing infrastructure to becoming a commodity except for maintenance on local equipment. Businesses that operate primarily from the cloud are more flexible, more productive, and overall, more efficient.

The future of cloud computing brings humanity to ever increasing connectivity. Individual networks will become redundant and most systems will be integrated into a network. Because of the increased connectivity, enabled by cloud computing, software applications integrate seamlessly with each other and with the human environment, regardless of location. One-to-one application integration processes will be transformed via meta languages into mass enabled applications that can connect with each other to exchange data. Consumers will expect applications to be more connected and more versatile and the applications with the most connectivity are becoming the most effective and, thus, most popular.

6. Peer-to-Peer Networking

The historical development of peer-to-peer networking inaugurated the decentralized technology evolution. The term peer-to-peer networking describes a distributed applications architecture that distributes and partitions computing workloads or tasks between peer computers or nodes. Such nodes are equal contributors with equal privileges in the application, forming the peer-to-peer network of nodes. The distributed nature of the network is made possible through the removal of centralized hosts and servers. Instead, the nodes that form the network make computing resources, such as disk storage, network bandwidth, and processing power, directly available to each other. Unlike traditional client-server models, that divide the consumption and supply of computing resources, nodes in decentralized peer-to-peer networks are both consumers and suppliers of computing resources.

The transition from a traditional client-server computing architecture to a peer-to-peer networking architecture was made possible by the inversion of the role of the audience in the network. The demand for a file in a traditional client-server architecture is directly proportional to the bandwidth it consumed. By contrast, in the peer-to-peer network, higher demand for a file triggers higher levels of seeding nodes for the high demand file. The higher seeding level for the file lowers the delivery cost for each distributed file. Accordingly, a peer-to-peer computing architecture is more efficient than the traditional client-server architecture. The traditional client-server architecture is subject to the linearly increasing per-unit costs whereas with a peer-to-peer network, cost decreasse with each added node. Network effects proliferate in peer-to-peer networks as each node that joins the network both consumes network resources but also provides resources to the network. Because of its cost structure, the traditional architecture is more subject to competition than the peer-to-peer architecture.

The heritage of peer-to-peer networks goes back half a century. The transition from a traditional client-server computing architecture to a peer-to-peer networking architecture was made possible by several core projects and their developer teams. While this short history of peer-to-peer networks perhaps was made most famous by the file sharing system Napster, which was released in 1999, the following projects, most of whom are still active, are worth mentioning in chronological order:

1. In 1969, the Arpanet connected several preeminent computing research institutions and treated each institution node as an equal computing peer, not in a client-server format.

2. In 1979, Usenet was based on the Unix-to-Unix protocol and allowed Unix machines to exchange files,

3. In the late 1990s, Napster file sharing was made possible through the then new data compression technologies. In less than a year, Napster had over one million members.

4. In 2000, Gnutella allowed users to find each other remotely, removing Napster’s need of central indexing servers. At the same time, Freenet significantly enhanced user anonymity by connecting users only through intermediate nodes and storing encrypted snippets of files;

5. In 2001, BitTorrent allowed nodes to connect directly through a TCP port and later implemented distributed hash tables for peer-to-peer discovery. Even if government authorities shut down specific servers, the BitTorrent network could not be shut down because nodes could update their own routing tables indefinitely.

6. In 2009, Bitcoin was released by Satoshi Nakamoto as a blockchain with a distributed registry that allowed it to store with each node an incrementally growing registry of transactions that could not be changed. The underlying consensus mechanism of Bitcoin could be abstracted into many different use cases above and beyond storing data and transacting in a store of value.

III. Open Source Movement

The open source movement is defined by the core characteristics of open source software. The Open Source Initiative defines open source software by its terms of distribution, not just the free access to source code. The following are core defining criteria of open source software:

1. Free redistribution.

2. The program includes source code and allows distribution of source and binary code and obfuscating source code is prohibited.

3. Derived works can be distributed under the same terms as the original code.

4. The integrity of the author’s source code has to be maintained.

5. Any open source license must not discriminate against any person or group of persons.

6. Any open source license must not discriminate against anyone who wishes to make use of the open source code in a specific field of endeavor.

7. Licensed rights associated with open source code transfer to anyone to whom the code is redistributed.

8. Open source code licenses are not specific to a product and anyone who is a recipient of the open source code by way of distribution has the same rights as the original software licensee.

9. An open source software license must not restrict other software distributed along with the licensed open source software.

10. An Open source software license must be technology-neutral and cannot be predicated on any individual technology or type of technology interface.[6]

The definition of open source software provided by the Open Source Initiative follows several core rationales that apply to open source code. For instance, the requirement of free redistribution creates incentives for contributors to focus on long-term objectives. Un-obfuscated original source code is necessary in order to modify the original code and thus enable the original code to evolve. Evolution of open source code necessitates experimentation and in turn requires open redistribution of code modifications. Changes to original source code must be identifiable by way of the distribution of pristine base sources plus patches so the authors’ incentives and reputation are protected and contributors and users know what original work they are supporting and changing. To ensure optimal diversity of contributors, no contributor can be discriminated against in the open source development process by way of an open source license. Therefore, open source licenses cannot incorporate any restrictions and commercial users are freely included.[7]

1. History

The core open source software development community emerged from the early days of the development of the Internet. During the 1960 and 1970s, the academic research and software development at leading universities in the United States necessitated the exchange of information. Because the academic community needed core infrastructure products for their respective projects, yet infrastructure elements were not in place at the time, the exchange of information became a natural side effect of software development and research.

Corporate research laboratories followed a similar pattern of exchange and community effort in software development in the early 1960 and 1970s. For instance, Bell Labs and Xerox’s Palo Alto Research Center wanted to incentivize intrinsically motivated projects among their highly skilled developer workforce. Accordingly, such corporate research laboratories gave their developers near complete autonomy in the pursuit of personal projects that had a rather limited association with the corporate products or services. What made this autonomy even more remarkable was the sharing of information the corporate entities permitted for the furtherance of the research, in the spirit of academic freedom. The academic research in combination with the significant freedom facilitated by corporate research laboratories in these years created a culture of exchange and cooperation that permeated the software development communities around the world for decades to come.

The proliferation of the open source software movement derives in part from the nature of the developed software itself. The realization in the software development community that interoperability means survivability, especially during the infancy of the software development movement, gave rise to an ethos of interoperability. Interoperability required the development of software that could work on different platforms. In turn, the ethos of interoperability necessitated exchange and cooperation among the developer community itself.

Several examples illustrate the power of open source software development. An open source software program such as Apache, for instance, is used by the majority of web servers on the public internet.[8] Apache is an open source software product that was developed by teams of hundreds of developers around the world. Users of Apache around the world also report bugs or request enhancements. Developers and users alike are not paid for their efforts. Fully funded commercial products developed by Sun, Oracle, Microsoft, among other companies are forced to compete with Apache.

Unix is another example of a successful open source project. Some of the biggest internet-based platform companies of the world, including Google and Amazon, use the Linux operating system. The development process that enabled the Unix operating system in the 1970s provides an ideal example of the evolution of open source development. Unix epitomizes interoperability because its functionality can be extended through user programs built on a standard programming interface. Unix programs are also designed around a standardized text interface and a core kernel that manages the system and other processes. The software that was originally developed at AT&T’s Bell Laboratories was subsequently installed freely across institutions.

2. Proliferation

According to some estimates, open source software accounts for between 78%[9] and 98%[10] of all core digital infrastructure software. Many of the most successful open source projects can trace their adoption increases over the last twenty five years to the accelerating global E-Commerce uses for open source code. Examples include and open source operating systems such as Linux and BSD Unix, open source web-servers such as Apache, iPlanet and Netscape, e-mail servers such as Sendmail, as well as open source languages such as Java, Python, GCC, Tk/TCL, and Perl. Because of their increasing applications and use cases, the most significantly proliferating existing open source projects include: Linux, Apache, Mozilla, Bugzilla, Topologilinux, Frozen Bubble, Tux Typing, Project @ssistant, and Junit.[11]

The open source movement is a natural derivative of the software development community culture. Software development is a community effort by nature. Accordingly, a tradition of sharing and cooperation for the greater good of optimized code is a natural part of software development. Open source developers are generally self-organized. Collaborator and contributors rarely meet face-to-face, are self-coordinated with contributions coming from disparate locations around the world. Contributors volunteer their time to write, share, and support their software without monetary compensation.

The proliferation of open source software can also be traced to the increasing use of open source software by governments and commercial enterprises. Starting in 2016, several worldwide operating corporations, including Google, Walmart, AT&T, and Microsoft, among others, joined or expanded the open source ecosystem. Similarly, governments around the world are embracing the open source movement. Bulgaria, the USA,[12] Norway, Brazil, and China, among several others have increased their open source uses and contributions. For governments, adopting open source software can increase security because vulnerabilities are often identifiable by experts before they materialize in applications. Moreover, open source software is typically much cheaper for governments as it can be modified for multiple needs in multiple departments without the need to purchase commercial software licenses and the need to commit and get locked in by a single commercial software vendor.

3. Contributors’ Incentives

Why would software developers and architects choose to make unpaid volunteer contributions to open source projects? A variety of motivational factors influence the contribution process for open source projects. Software developers perform a cost-benefit analysis when they decide to make an open source project contribution and throughout the respective project. Dedicating time and efforts are costly because the volunteer is not making money in the meantime and is slowing down on other projects he or she may be working on at the same time. Those opportunity costs, e.g. the cost of being able to do something in the meantime that would generate an economic benefit, need to be offset.

Incentives to contribute to open source projects come in many forms and offset the opportunity costs to the software developer. First and perhaps foremost, the developer obtains a personal satisfaction and joy out of working on an open source project and contributing to its mission. This personal joy can have many facets but may include the feeling of satisfaction that comes from contributing to something that makes the contributor feel like he or she created something that makes the world a better place. The open source contribution can also give developers a significant sense of freedom and autonomy as nobody typically supervises the open source development. Peer recognition of one’s programming skills has also most certainly been a significant motivator for contributors since the early days of open source projects. Moreover, the software developer may learn something during the open source project that increases his or her skillset. The new skills may make the software developer a stronger developer with enhanced employment opportunities. As a matter of fact, a corporation that employs a software developer who works on open source projects may benefit indirectly from the enhanced skillset of the software developer, which in turn may improve the corporations’ products.

The transparent nature of open source projects facilitates comparatively higher levels of signaling for contributors. Because anybody can access the open source code, contributors’ peers and future employers can examine the individual contribution as well as its quality. Quality measures here refer to the impact of a respective contribution, whether it solved a problem that others could not solve and how innovative and workable the solution was.

Open source software development taps into the herd mentality of the software development community. Some lone-wolf programmers may simply want an audience to impress their peers. Yet, many open source software projects become so popular because the quality of the project and the code inaugurated by a lone-wolf may be so high that other programmers become inspired by the vision of the project. The herd mentality of the software community suggests that developers want to be part of the moving train in software development. In other words, they want to work on projects with a vision that attracts a large number of other developers and creates a critical mass. Several factors have to be combined to create liftoff for an open source project including but not limited to the following:

1. Vision

2. Overall industry trend

3. High level of talent

4. High quality code

5. High number on the core development team

Open source contributions can have a commercial objective. Peer recognition derived from open source contributions can lead to funding for the developers’ projects via venture capital and it can lead to paid engagements from startups or corporations job offers. Even if software engineers may predominantly make open source contributions to impress their peers, the open source work can also function as a signaling device to get involved in interesting cutting-edge projects that may in the long-run enhance the resume and open opportunities for the contributor that would otherwise not exist.

Developers may not be entirely altruistically motivated when they join an open source project. Open source projects have the capacity to lower development cost because of the path dependencies that are being created by open source software and the legacy effects that are associated with that. More junior developers can learn with and from open source code. When they enter the workforce such junior developers are already familiar with the core concepts, which reduces their overall cost and makes it more likely to engage with open source code.

4. Shortcomings

Despite all of the advantages, open source projects are subject to several shortcomings. Perhaps most significantly, most open source projects cannot reach critical mass to further their development agenda. Only a small number of elite open source projects can attract developer contributions. The majority simply cannot attract a sufficient amount of developers who believe in the vision of the project to create critical mass. Once critical mass is accomplished the respective project can become almost a self-fulfilling prophecy. The development of Linux is one of those examples.

Unlike their centralized counterparts, open source projects can be subject to separation movements. Because no centralized authority decides the direction of development, open source projects are more prone to cliques of developers that develop their own belief system regarding certain aspects of the development process. For instance, the strong belief by some developers in product design features that resulted in the separation of the Berkeley Unix program and Sendmail during the late 1980s.

Perhaps if the open source movement had an optimally incentivized democratic decision-making tool, such separation of interests and development would become less likely. If the voting constituents in an open source movement knew that their decisions as a whole are driven by optimal incentives for each voter to find the truth, they are more likely to accept the outcome of a given vote. The emerging decentralization technology has enabled a debate on the feasibility of such a voting tool. Early research suggests that it is theoretically feasible.[13]

The usability of open source products is often underdeveloped and support and testing are often less evolved and not as readily available in open source projects. Because open source software is often the product of experts in their respective fields, open source software and products are often geared towards the expert users who are typically able to get access to the code and add value themselves quickly. Because of the expert nature of open source contributions, contributors are generally more interested in their actual work product, e.g. code, rather than explaining it to other users by way of documentation and testing. The lack of documentation in open source projects can partially be explained by the community driven effort to eliminating bugs. Yet, the average developer and consumer typically require more support through user-friendly interfaces, backwards compatibility and comprehensive and easily accessible documentation. Simply adding comments in the source code, as often practiced in open source projects, may simply not be sufficient. Recognizing the need to upgrade documentation and testing, some larger open source projects, including most notably Linux[14] and Mozilla,[15] have started to make developer documentation web pages available to the community. Testing strategies for open source projects are still largely restricted to the insiders of a given projects’ developer community.

Software patents have emerged as a challenge to the open source development process in the early 2000s. A litany of patents and patent litigation emerged in the early 2000s and undermined the open source development process. Since the early 2000s, the ideas imbodied in code were subjected by the courts to enhanced legal protections. Patent litigation initiated by the SCO Group in early 2003 presented the first wave of patent enforcements. After its acquisition from Novell, the SCO Group held at least partial rights to UNIX and began to enforce these patents against among others: Novell, IBM, DaimlerChrysler.

As a result of the litigation and its aftermath, it became much easier to obtain patents, even for more common ideas that previously would not have been protected. For example, almost 300 patents can potentially be used against the Linux kernel alone.[16] The level of innovation was high in the software industry in the early 2000s, when the courts increased the patentability of software. What makes things worse, courts decided to increase the protections for software despite lacking proof that additional patentability of software would increase the level of innovation. As a result, corporations began filing and acquiring thousands of software patents that enabled them to strategically undermine competitor projects.

As a result of the accelerating patentability of open source solutions, developers increasingly fear they could inadvertently infringe patents during the open source development process. In turn, developers often lack the knowledge and skills to make the determination as to whether their open source contributions may infringe existing software patents. Exacerbating the problem, in 2004, Linux contributors became subject to mandatory attestation requirements as to their respective rights to make an open source contribution to Linux.[17] The combination of these factors inhibits the open source development process.

The increased patentability of code also raises an incentive problem for developers. It is questionable if developers are sufficiently incentivized to contribute to an open source project if they could join a traditional closed project. Similarly, the concern that increased patentability of scientific output will limit research is discussed in the literature under the label of the ‘‘anti-commons’’ problem.[18]

5. Level of Decentralization

The level of decentralization in the developer community of individual open source projects provides an early indicator as to how much trends in the open source movement can foreshadow the decentralization movement. The level of decentralization here is defined by how homogeneous the developer community is in a given open source project. Depending on the open source project, the level of decentralization may differ significantly.

The degree of decentralization in open source communities and projects is dictated by the degree of hierarchies in the governance of a given project. Some open source communities may have an entirely flat hierarchy among developers. This would typically mean that all developers are on the same level and there are no power disparities between individual developers. Decisions are made based on unanimity or some form of consensus. In this flat hierarchical governance structure, the degree of decentralization is highest because no power disparities exist between developers.

The open source development community is not immune to centralization. Humans have a natural inclination to use knowledge and resources to exert power over others. In more centralized open source projects, a hierarchical differentiation may exist between contributing developers. In the existing hierarchical structure among open source projects, developers may be invited to join the ranks of core developers after demonstrating their value to the other project contributors and, thus, earning their respect. As core developers, they may have enhanced power over the governance structure and enhanced access right to the code, e.g. the right to incorporate their modification into the code base. This is of course a two-way street in the sense that developers may also be demoted to -co-developer etc. if they cannot maintain their reputation or are subject to personality clashes etc.

Hierarchies among developers in a given open source project bring with them a more centralized power structure. In such open source projects, the core developers have typically more power than ordinary codevelopers. Some open source projects, such as Apache, have instituted multiple levels of developers. Such projects may therefore be deemed more centralized. This power disparity manifests itself in executive decision making. Here, core developers with high levels of power may have increased voting rights on product development of strategic implementation and overall project strategy. Centralization here connotes the degree of influence a given developer at a certain rank may have in the governance of the project.

The meritocracy of open source projects may be seen as justifying and / or offsetting centralization of power in a given open source project. Contributors’ knowledge and quality of output (e.g. work products and code demonstrated by a given contribution,) is used to determine a contributors’ perceived merit. The respective level of perceived merit of a given contributor, in turn, leads to power. The community of contributors may find it justifiable to allocate a higher rank to a developer who solved a very significant problem for the project as a core developer.

Allocating a higher degree of power to a given developer based on perceived merit can often turn out to be a fallacy. While the merit of a given contributor and its transference to power may depend on a given project’s organizational structure, timing and the obstacles that had to be overcome may often play a role in the allocation of power. For instance, a one-off contribution at the beginning of a project may not mean that the respective developer continues to maintain the required expertise and merit to continually justify the higher rank. In other words, deflation is not built into the perception of merit and free riding is possible.

IV. Economic Instantiation of Increased Network Capabilities

The ever-increasing technology-based connectivity and increased network capabilities of society have had several historic economic instantiations. The combination of technology development and business applications of technological innovations created the historical foundation for network-based decentralized structures. Economic incentive design is an integral part of decentralized technology and decentralized network proliferation. For example, token economic incentive designs in decentralized systems are an important network feature. The existing economic network designs are a precursor of what future economic applications and incentive designs for decentralized networks could encapsulate.

1. Platform Business Proliferation

Internet-based platform businesses have been proliferating since the dot.com boom at the end of 2000. A platform business model enables exchanges between two or more interdependent but otherwise disconnected groups, such as producers and consumers, to transact business and create value. Examples include Google, Facebook, YouTube, Airbnb, Uber, eBay, Alibaba, and PayPal. Platform businesses create scalable networks of users and resources that can be accessed on demand. To build a growing digital environment and the associated revenues, companies have integrated their core business functions into platforms to create synergies with third parties. To participate in the value creation of platforms, companies are either trying to become a part of an existing ecosystem or create an ecosystem for their unique offering, service, or products.

The platforms facilitate and coordinate unprecedented connectivity between multiple entities, individuals, business partners, and individual end users. The entities and individuals include the platform owners, the platform itself, the data that is generated by the platform and monetized by the platform, the technology that is improved by the platform and in turn enables the platform itself to be operational for business, as well as creative communities, users extractors, other joint ventures or partners.

Platform businesses thrive because they facilitate increased connectivity between consumers and producers. Digital and internet-based platform businesses that increased the connectivity between consumers and producers have had significant disruptive effects on many industries. For example, Amazon and Uber, among many others, have built multi-billion-dollar businesses at unprecedented speed in the corporate world. In their paths, these platform businesses are often challenging or removing entire incumbent businesses and disrupting entire industries. This new business paradigm, depends on the ability to create unique technology platforms that are intelligent, open, scalable, and increase connectivity.

Platform businesses build and enhance technology infrastructure. The connectivity improvements have knock on effects on technology development because the platforms generate data that is used by the platforms to monetize but also to improve their own technologies. The thus improved technologies, in turn, enable the platforms to improve their services and product offerings which generates even more data. The feedback effects between data generation and technology optimization and vice versa creates a permanent learning and optimization environment for platform businesses.

Internet-based platform services are partially so successful because their peer-to-peer capabilities, in connecting consumer and producers, make them compelling, efficient, and attractive to consumers in a fast-changing world, leading consumers to place their trust in new businesses and brands. Search algorithms, data analytics, and improvements in usability have increased trust in consumers by minimizing bad experiences, maximizing great experiences, and avoiding unwanted issues. With the increasing availability of big data, deep learning, machine learning, sensors and sensor data, such technology-driven evolution of internet-based platform businesses can be expected to expand rapidly. The S&P 500 index has seen many of platform-based companies become its largest and fastest growing listed companies.

Once internet-based platform businesses become fully fledged ecosystems, they can further scale and optimize their business. Whereas in the past, business innovation required coordination of materials, sourcing, distribution, customer sales and service mostly in silos to protect from competition, today a business ecosystem enables customers, partners and vendors alike to efficiently exchange value. Because ecosystems lower barriers to entry and enhance connectivity between organizations, consumers, individual departments and related industries, they help companies get closer to customers. The connectivity-based profitability is further increased because ecosystems allow the connected businesses to gather and analyze big datasets generated by the ecosystem for the betterment of all ecosystem participants. This data sharing allows ecosystem participants to learn more about their shortcomings and optimize their businesses. For example, Amazon was able to utilize data coming from multiple data points in its ecosystem to optimize its distribution and supply channels and personalize customer recommendations that created significantly higher sales.

The business models promulgated by the increasing proliferation of platform businesses will likely become the de-facto standard for the platform-based digital transformation of the future. The digital transformation of business, starting in the 1990s, was a critical factor for business success that enabled the proliferation of platform businesses and technology innovation. For example, the increasing use of telecommunications, the digitization, IoT, social media, cloud computing, and peer-to-peer networking, in combination with big data functionalities allowed for more seamless integration with cloud computing. The increased flexibility and proliferating scale of the digital transformation via cloud computing allows the enhancement of existing legacy business processes far more easily. Facilitated by platforms and ecosystems, companies can engage in joint ventures and partnerships and grow quicker together through the easier integration of services and products.

2. API Economy

Application programming interfaces (APIs) provide unprecedented connectivity in digital applications and business. An API is a computing interface or computing communication protocol between a server and a client. Its job is to provide standard best in class services generally offering specific solutions, most often used by the provider as part of their offering to end customers, that can be used by partnering companies to gain the advantage proven technology provides. Two very successful early entrants into the API markets were PayPal and Salesforce, enabling very sophisticated solutions that would be nearly impossible to equal. APIs make it easier to integrate and connect data, algorithms, systems, and people, share data and information and authenticate people and things by leveraging third-party algorithms and enabling transactions. Through these features, APIs help create new user experiences, new product/services and business models. APIs simplify the building of client-side software through a set of procedures and functions that enable applications that access the features or data of an application, operating system, or other service. APIs create the standards that allow companies to exchange data and build seamless omni-channel experiences for their customers. Because of their key accessibility features, APIs facilitate the interoperability of otherwise centralized unconnected computing systems.

The term “API Economy” generally refers to APIs’ ability to increase organizational effectiveness and profitability in businesses through its ability to increase interoperability of otherwise disparate systems. Historically, mostly software professionals concerned themselves with the use of APIs to overcome incompatible software systems. Over time, however, the increased compatibility of software solutions and heightened interoperability of systems increased the value proposition of emerging technologies. The ability to attain additional revenue through the application and use of third-party APIs was perhaps most visible in enterprise applications of mobile solutions, social networking, financial services, and web-based applications.

APIs disrupt traditional value-chain hierarchies. Through the use of APIs, companies no longer need to control the entire value chain because it is much cheaper and technologically often easier to create application features in separate products that connect via APIs to existing ecosystems and/or other products. Through the connectivity in APIs, companies can combine individual products as building blocks that, if connected, can function as a single product or proposition that satisfies particular consumer needs that are otherwise not fulfilled in the ecosystem but technologically possible.

The ever-growing API Economy benefits from technology-based increases in network capabilities of business and society and vice versa. Technologies that increase network capabilities of business and society invariably rely on APIs to facilitate interoperability and / or increased connectivity. Such technologies and businesses include telecommunications, mobile phones, the digital transformation of businesses, the IoT, social media, cloud computing and peer-to-peer networking. As these technologies and business proliferate, the API Economy grows in lockstep.

The API Economy thrives particularly because several sectors increasingly relied on APIs and merged their efforts via APIs to create significant synergies. An organizations’ profitability in a given sector benefits from the creation of new API-powered capabilities and services. The more popular a given service that relies on APIs, the more the underlying business will consider APIs as a factor in its business model and strategy.

APIs foster connectivity-based innovation. Companies can use APIs to expand their innovative product offerings and designs by connecting their existing offerings via APIs with building blocks to other products and designs that are external to the company. Such API-based business expansions often result in more efficient and more scalable distribution channels for the respective company. API platforms enable the expansion of existing products into more comprehensive products by delivering much needed additional features and capabilities. For example, a banks’ API strategy, that is their ability to connect to other services and products, is instrumental to their respective brands and ecosystems.

APIs can transform businesses into platforms that expand value. Platforms can expand and multiply the creation of value in a given business. Such value creation is possible because platforms enable business ecosystems inside and outside of the respective company.

3. Sharing Economy

Peer-to-peer connectivity is at the heart of the sharing economy. The term ‘sharing economy’ is often used to refer to the distribution of services and goods and the partial use of others’ property rights in goods. For instance, you might provide your car, or your time, as part of a peer-to-peer transaction, often over a platform built to unite the interested parties. Unlike traditional centralized ways of production and selling to consumers by hiring employees, platform companies in the sharing economy typically provide the technological setup that allows individuals to share their property rights in goods or sell their services without centralized employment. Individuals who connect via platforms in the sharing economy share their property rights in, for example, cars, homes, or rent out their personal skillsets and time in a peer-to-peer form of engagement.

The sharing economy has become part of modern society’s mainstream. The origins of the sharing economy can be traced back to an emphasis on sustainability, resource efficiency, and community. As the sharing economy evolved, not only did its services and industry acceptance proliferate, the sharing economy’s credo of “Access over ownership” became more mainstream. The public had grown accustomed to receiving services and goods on-demand via digital and mobile technologies. On-demand access to goods and services became part of modern society, it became no longer a preference and habit of millennials alone.

The sharing economy necessitated a reframing of legacy legal regimes and frameworks. The legal frameworks that regulate disrupted and associated industries were often incompatible with the emerging trends generated by the sharing economy. Cities and co-municipalities had to learn that the sharing economy requires a proactive stance to channel the sharing economy’s outputs and associated new requirements into economic development while at the same time protecting the public with regulation. While some cities have joined forces to declare common commitments and principles for sharing cities[19] and many co-municipalities are developing transportation-as-a-service platforms to better meet the needs of all residents, some states in the United States have passed legislation that in some ways undermine the sharing economy.[20] Yet, some countries, such as Denmark, have changed their internal regulations to better accommodate sharing economies.[21]

The values that enabled the kickstart of the sharing economy morphed from an emphasis on connectivity for the sake of sustainability to a focus on connectivity and community as a commodity. In other words, connectivity and community building via increased connectivity became a purpose and meaning by itself. The purpose of sharing economy participants shifted from connectivity for a cause, such as a community for sustainability, toward mass consumption for convenience and transactional efficiency.

The ultimate sign of the sharing economy’s success is its increasing recognition in policy, economic, and business circles, as part of the overall economy. The sharing economy has the potential to shape entire markets that are better connected and more efficient. It has started to blur the lines between industries and even former competitors.

4. Networked Information Economy

The networked information economy[22] is the extension and combination of factors emanating from the proliferation of internet-based platform businesses, the API economy, as well as elements from the sharing economy. Based on the proliferating peer-to-peer exchange of information, the networked information economy may be replacing the centralized industrial information economy of the late-nineteenth century.[23] The greater role of decentralized individual action is made possible through much easier access to information, by way of social media, among others. With the easier access to information comes the significant reduction in communication costs. Peer-to-peer production is a natural corollary of cost efficiencies created by organizing on peer-to-peer bases.

The network information economy’s emphasis of increased flow and availability of information is made possible by several core factors. Lower communication cost and more diverse sources of information from the edges of the system and society enable the coordination of productive efforts. The availability of information in structures is not consumptive and does not deplete. Computing power in structures is progressively less expensive and production cost are correspondingly low. Because individual inputs come increasingly from the edges of the system, the inputs are less homogenous and more diverse which increases the utility of network membership for each member or node.

V. Technological Precursors of Decentralization

We can learn from history. The modalities of historical increases in society’s network capabilities provide a precedent for the evolution of decentralization. The technologies and technological trends that enabled the increases in telecommunications, internet proliferation, e-commerce, the digital transformation of society, social media, and the internet of things, among several others, have inaugurated unprecedented societal network capability.

These technologies and trends also opened the gateway for a deeper structural reform of society. Heightened network capability of society is in many ways just a precursor to a more fundamentally networked societal structure. Just as social media groups are created regardless of ethnical origin, race, citizenship or creed, networks in society can cooperate and co-create at an unprecedented level. Such cooperation and co-creation are already possible with centralized internet structures based on existing technologies. Take for instance the creation of Wikipedia and the volunteerism that makes it strong and growing every day. Volunteers co-create content and information for the greater good of society. The structural reforms emanating from existing technologies are often described as globalization. Yet, the term globalization insufficiently describes the social structures and network capability created by the technologies.

1. From Disruptive Fintech to Decentralized Finance (DeFi)

The digital transformation of business enabled disruptive innovation and change. Startups have capitalized on the customer-experience- aspects of the digital transformation of their business and created peer-to-peer disruptive business solutions. The disruptive change coming from customer-focused technological innovation is often directly linked to the emergence of fintech. The innovation of financial services via technology has created systems that are faster, cheaper and more convenient for the consumer.

The disruptive peer-to-peer features of fintech epitomize the core principles of decentralization. Fintech brings information closer to the edge and serves the consumers, it disrupts centralized structures in finance and forces the disrupted financial conglomerates to serve the consumer better. As such, Fintech is precursor of future disruption generated by decentralized technologies.

Decentralized Finance (DeFi) is an extension of the customer-experience-focused digital transformation that was enabled by the proliferation of fintech. As an emerging movement in 2019, DeFi attempts to apply decentralized technology solutions to further disrupt financial services. The particular form of disruption in DeFi comes from its attempts to make financial transactions permissionless, completely open to anybody, and borderless. Through the use of blockchain technology and its progeny, DeFi promises to empower its customers with reduced transaction costs, broader financial inclusion, and open access across borders. The disruption through DeFi may be mitigated by existing financial institutions’ attempts to leverage decentralized technologies in a controlled environment that allows the utilization of its benefits, such as transparency and interoperability, while also facilitating centralized oversight.

2. Digital Transformation as a Pathway to Decentralization

The digital transformation of business enabled for the first time in history a form of decentralized production at lower cost. With the digital representation of content, centralized production was less needed, e.g. printing presses and other forms of material representation of content became redundant for certain businesses, and decentralized content production became significantly less expensive. Digitization has enabled decentralized production because content could be more easily accessed and produced with fewer resources regardless of location. Content could come for the first time from the edges of the system rather than through centralized production mechanics. And, content could be more easily distributed and shared with fewer points of control and oversight. At the same time, per unit costs of goods and services can be lowered and overall transaction cost depreciated.

The same factors that enabled and accelerated the digital transformation of business also help facilitate and extend decentralization. Digitization of content in combination with the proliferation of the internet and increasing online access via smartphones has motivated many businesses to consider new digitally-fueled revenue producing product lines to stay competitive. Cloud computing has further extended the digital transformation at the enterprise level by facilitating the, often real-time, interaction between individuals and between businesses. Machine learning, IoT, and analytics in combination with blockchain technology and AI enable the digital transformation at the speed of the customer experience. With the increasing influence of the customer experience on the digital transformation, decentralized business opportunities are proliferating.

Tokenization of assets is a natural part of technology-enabled decentralization. The tokenization of assets refers to the process of issuing a digital asset that forms the digital representation of an existing real-world asset. Similar to the process of securitization, where financial institutions pool illiquid real-world securities to form newly created securities that convert into cash and can be traded, tokenization takes liquid or illiquid real-world assets and converts them into digital assets or tokens that can be traded on secondary markets.

The digitization of content was a natural precursor of tokenization via decentralized technology. The digitization of content was a natural precursor to the internet of things and its progeny. The proliferation of digital services in the internet of things, in turn, required a certain depth of digitalization to work with other technologies and to create new business assets. Tokenization of assets via decentralized technology can therefore be seen as the extension of digitalization. Tokenization of existing assets, for instance, tokenized real estate is the instantiation of a fractural part of the respective piece of real estate as a whole, requires a certain depth of decentralized infrastructure solutions.

3. From IoT to Decentralized Web (Web 3.0)

Internet-based platform businesses have been proliferating since the dot.com boom in the late 1990’s. Internet-based platform services are so successful because their peer-to-peer capabilities make them compelling, efficient, and attractive in a fast-changing world, leading people to place their trust in new businesses and brands. Search algorithms, data analytics, and improvements in usability have increased trust in consumers by minimizing bad experiences, maximizing great experiences, and avoiding unwanted issues. With the increasing availability of big data, deep learning, machine learning, sensors and sensor data, such technology-driven evolution of internet-based platform businesses can be expected to expand exponentially.

The IoT proliferation is offset by diminished consumer confidence. By the year 2020 the majority of experts estimate that a total of 30 to 50 billion devices will connect to the internet.[24] The sheer amount of devices creates unprecedented cyber security issues.[25] Cyber security attacks can now be launched by unsophisticated parties at minimal cost with maximal potential for damage. Cyber security attacks, in turn, are among the factors that help explain the declining consumer confidence on the internet. Several studies have provided evidence on the acceleration of trust issues in the internet around the globe.[26] Trust issues in the United States can clearly be distinguished in international comparison.[27]

The trust crisis is exacerbated by deficiencies in the internet infrastructure. Since its inception, the internet has become a network of vertically and horizontally integrated monopolies. These monopolies create information silos and constrain knowledge exchange. The resulting lack of competition impedes innovation, including at the protocol level and diminished consumer protection and rights. These deficiencies in today’s internet age consistently and progressively undermine trust on the web.

Consumer confidence and trust are becoming increasingly digitized and automated. The traditional trust and cohesion mechanisms have reached their limits. Slow and expensive experiences have resulted in greater distrust in established institutions and their products and services. The old-world focus on more regulations, processes, and procedures is being replaced by new forms of trust. People are much less trusting of organizations or procedures, but instead trust machines and algorithms and the underlying code. Trust has started to become digitized and automated. Humans trust machines on the internet to store and process information and to transact with each other and with machines.

Peoples’ increasing reliance on digitized, coded, and automated replacements of traditional cohesion mechanisms may be misplaced. The existing internet is designed for hierarchical societal structures and with an underlying authoritative and hierarchical trust model. Many inefficiencies are associated with the traditional hierarchical trust model including serious cyber security vulnerabilities.

Decentralized technology solutions may soon be able to replace existing technology on the internet. For example, startups have been experimenting with decentralized authentication engines to verify fake news, among other applications. Such decentralized technology solutions may soon be able to verify the trust humans place in machines and enable a more trusting environment for internet-based transactions. While society is not yet convinced that distributed or decentralized peer-to-peer networks can deliver enhanced digitized trust, the experimentation with decentralized solutions has started to personalize and humanize digital trust.

4. From Social Media to Decentralized Coordination

Social media transfers knowledge from the edges of society into the mainstream. Social media allows people who hold otherwise marginalized or underappreciated views to meet kindred spirits online and form groups that promote their shared ideas. When these newly formed social networks grow they can increase their influence incrementally and promote their perspectives until they become more mainstream. Otherwise invisible social, ethical, environmental, political issues can thus gain traction rather quickly. Increased visibility of these issues can transfer the balance of power on these issues from the hands of a few to the mainstream of the masses.

The increased network capability of society that is promoted by social media can change and improve the coordination of human behavior in society. Social media data and metrics can replace centralized coordination of human behavior. For example, social media posts often identify emergency information more accurately and more timely than centralized media reports. Similarly, for groups that coordinate their conduct, as for example in the Arab Spring and other reform movements, coordination via social media is not merely relegated to information exchange, but can actually coordinate protest movements. In the product context, social media conduct of groups as they relate to products becomes a very powerful placement and marketing device. Product specific or content specific conduct on social media can become a form of ‘social proof’ for such products or services.[28] However, because the incentive design for social proof is suboptimal, the social media coordination function is still largely flawed.

Decentralized technology solutions can tap into the coordination function that was inaugurated by social media and improve it. Social media allows the enhanced coordination of information that was previously allocated on the edges of society. Because social networks feed off interactions among people, they become more powerful as they grow. Decentralized technology enables the decentralized coordination of powerfully growing social media networks and channel the information and interaction of people. Governing decentralized information flow necessitates decentralized incentive designs. Startups have started to experiment with decentralized technology solutions that tap into the information coordination function facilitated by social media.

5. Cloud Computing as Inertia for Decentralized Networks

Cloud computing introduced the idea of applying resources from the edge of a system, to pool such resources, and to apply them for a greater good. Cloud computing became a reality in 2002 with the release of AWS by Amazon. However, it bears significant similarities to the time sharing systems of the 1960s as technologists and scientists explored ways to make large-scale computing power available to broader groups of users. Later expansion of these concepts involved experimentation with algorithms that helped to prioritize CPUs and increase efficiency for users. The experimentation helped optimize the cloud computing platforms, their infrastructure and applications.

What social media has done for the connectivity between people, cloud computing is doing for the connectivity of applications. Cloud computing enabled existing networks to become integrated into broader networks. Through cloud computing, applications could be integrated seamlessly with each other. Increasingly, one-to-one application integration processes are transformed via cloud computing advances into mass enabled applications that can connect with each other to exchange data and logic. Consumers expect applications to be more connected and more versatile and the applications with the most connectivity are becoming the most effective and, thus, most popular.

Decentralized computing solutions can further extend the progress of cloud computing by connecting the fragmented collective knowledge that was created by cloud computing in silos. Cloud computing has significantly increased connectivity in society and business but at the same time contributed to the creation of monolithic applications that solve a very specific problem for a specific business / department / role. The fragmentation of data and content is already creating problems for collaboration but also for the search, organization, and discovery of data and content. Companies need to find ways to address these problems born out of cloud computing to stay competitive and thrive. Connecting the collective knowledge that was created in silos is a fundamental undertaking that may only truly be accomplished through decentralized networks.

The interoperability of decentralized applications extends the application networks facilitated by cloud computing. To further extend network capability of technology solutions, applications have to be able to integrate with each other regardless of their technological and physical environments. Cloud computing enables future decentralized solutions because it already allows applications to talk to each other. Decentralized networks will further extend the application integration facilitated by cloud computing.

6. Peer-to-Peer Network Expansion

The future of peer-to-peer computing networks goes beyond sharing of computing resources. Current nodes in decentralized networks can share computing resources while doing rather similar tasks. Yet, future peer-to-peer computing networks will thrive by adding nodes to the network that contribute dissimilar resources and capabilities to the decentralized community of nodes. The dissimilarity of contributions allows the decentralized network to thrive because they enable the network to perform tasks that go beyond what individual peers can do by themselves. The network makes those enhanced capabilities available to the totality of nodes in the network, making it grow and proliferate in the process as additional nodes are motivated to join the network to take advantage of the additional capabilities.

Peer-to-peer network models increasingly spawn global socioeconomic experiments and inspire new structures and philosophies in many areas of human interaction. The success of peer-to-peer networks was instrumental in accelerating the transformation of legacy business models into peer-to-peer network incentive models. Such models started to proliferate after the emergence of the BitTorrent protocol in 2012. Peer-to-peer network incentive models are often intended to lower distribution-related costs because of direct negotiations between peers and the associated optimizing feedback loops and decentralized value flows.

VI. The Need for Technology Infrastructure Upgrades

Technologies that enable the increased network capability of society necessitate incremental infrastructure upgrades. Disruptive and game-changing technologies of the past inaugurated infrastructure upgrades that facilitated the expansion of the technology and with it social and societal changes. For instance, utilizing the technological potential of the steam engine and the combustion engine during the industrial revolution required then new infrastructure tools that improved connectivity in society. Those improvements included copper wiring for electricity, light bulbs, new laws, and institutions, among others. Similarly, the digital transformation in the aftermath of the birth of telecommunication, the internet, and digitization was inhibited until the digital infrastructure was built, laws were updated, and new institutions were created.

Decentralization benefits from the earlier technology infrastructure upgrades. Decentralization of business and society requires network technology. Advances in telecommunication, the internet proliferation and the resulting e-commerce, the digital transformation of society, social media, and the internet of things, cloud computing and peer-to-peer networking, among several others, increased the overall availability of network technology. Network technology that enables increased network capability of society, in turn, creates the necessary infrastructure for emerging decentralization.

Decentralization requires its own infrastructure. The technologies of the internet era and its progeny alone may not suffice. Fully decentralized technologies require an enhanced decentralized network infrastructure. For example, the emerging technological decentralization by way of blockchain technology may require a truly decentralized public blockchain. That is, a public blockchain that is not subject to points of centralization and corruption, that is fully secure at the level of proof of work security with a transaction throughput of over one hundred thousand transactions per seconds. Without such basic infrastructure products, on-chain governance of blockchains may not be or may only limitedly be possible. In turn, it is hard to imagine how decentralized infrastructure solutions can emerge without on-chain governance solutions.

The blockchain ecosystem may not be able to grow without a core decentralized infrastructure. This may include a functioning public blockchain that allows the community to build on and around with extensions and application solutions. In 2019, the People Republic of China has announced plans to issue their own centralized e-cryptocurrency. While this is hardly a decentralized infrastructure upgrade, it allows the blockchain community to develop applications around a widely recognized state-sponsored cryptocurrency. In the private sector, the introduction of Facebooks centralized libra cryptocurrency seems to facilitate trust into the technology and regulatory recognition which one day could help jumpstart an application ecosystem around the libra cryptocurrency.

Bibliography

Ballotpedia (2017). Local Government Responses to the Sharing Economy (ridesharing/homesharing), https://ballotpedia.org/Local_government_responses_to_the_sharing_economy_(ridesharing/homesharing) (accessed June 1, 2020).

Benkley, Yochai (2006). The Wealth of Networks: How Social Production Transforms Markets and Freedom. Yale University Press: New Haven.

Black Duck Software (April 15, 2015). 2015 Future of Open Source Survey Results. Synopsis, https://www.slideshare.net/blackducksoftware/2015-future-of-open-source-survey-results (accessed June 1, 2020).

Capiluppi, Andrea, Lago, Patricia, & Morisio, Maurizio (April 2003). Characteristics of Open Source Projects [Conference Paper]. Proceedings of the Euromicro Conference on Software Maintenance and Reengineering, https://www.researchgate.net/publication/4010991_Characteristics_of_open_source_projects [PDF Available].

Carr, Clare (Apr. 13, 2015). The Data Behind the Average Article Lifespan. Parse.ly, https://blog.parse.ly/post/1768/data-on-article-lifespans/ (accessed June 1, 2020).

Chaffey, Dave (Nov. 11, 2019). Mobile Marketing Statistics Compilation. Smart Insights, https://www.smartinsights.com/mobile-marketing/mobile-marketing-analytics/mobile-marketing-statistics/ (accessed June 1, 2020).

Chapman, Lizette, Eidelson, Josh, Cutler, Joyce E. & Bloomberg (Sept. 11, 2019). New Labor Bill Passed by California Senate Would Transform the Gig Economy — And Could Cost Uber $500 Million a Year. Fortune: Tech, https://fortune.com/2019/09/11/gig-economy-california-senate-uber-law-labor-rights-union/ (accessed June 1, 2020).

Code, code.gov (accessed June 1, 2020).

Debian (Apr. 26, 2004). Debian Social Contract, https://www.debian.org/social_contract#guidelines (accessed June 1, 2020).

Edelman (Jan 21, 2018). 2018 Edelman Trust Barometer: Global Report, https://www.edelman.com/research/2018-edelman-trust-barometer (accessed June 1, 2020).

Feller, Joseph & Fitzgerald, Brian (2002). Understanding Open Source Software Development. Addison-Wesley; UK.

Heller, Michael A. & Eisenberg, Rebecca S. (May 1, 1998). Can Patents Deter Innovation? The Anticommons in Biomedical Research. Science Magazine, 280, 698–701.

John Deere, https://www.deere.com/en/ (accessed June 1, 2020).

Kaal, Wulf (Aug. 23, 2019). Blockchain-Based Corporate Governance [Research Paper]. Max Planck Institute Luxembourg for Procedural Law (Dec. 2019), https://ssrn.com/abstract=3441904 or http://dx.doi.org/10.2139/ssrn.3441904

Krishnamurthy, Sandeep (April 2002). Cave or Community? An Emprirical Examination of 100 Mature Open Source Projects. First Monday, https://www.researchgate.net/publication/220167093_Cave_or_Community_An_Empirical_Examination_of_100_Mature_Open_Source_Projects [PDF Available].

Marsden, Dr. Paul (2012). The Social Commerce Handbook. Blacklick: McGraw-Hill Publishing.

MDN Web Docs, developer.mozilla.org (accessed June 1, 2020).

Netcraft (April 15, 2010). April 2010 Web Server Survey, https://news.netcraft.com/archives/2010/04/15/april_2010_web_server_survey.html (accessed June 1, 2020).

Nordrum, Amy (Aug, 18, 2016). Popular Internet of Things Forecast of 50 billion Devices by 2020 is Outdated. IEEE: Spectrum, https://spectrum.ieee.org/tech-talk/telecom/internet/popular-internet-of-things-forecast-of-50-billion-devices-by-2020-is-outdated (accessed June 1, 2020); Reuters (Nov. 8, 2016). Tech Firms Struggle to Make Smart Decices Safer. Forture: Tech, https://fortune.com/2016/11/08/struggle-internet-of-things-security/ (accessed June 1, 2020).

Open Source Initiative (2007). The Open Source Definition (Annotated), https://opensource.org/docs/definition.php (accessed June 1, 2020).

Open Source Initiative (2007). The Open Source Definition, https://opensource.org/docs/osd (accessed June 1, 2020).

Ritzau (May 18, 2018). In World First, AirBnB to Report Income Directly to Danish Authorities. The Local dk, https://www.thelocal.dk/20180518/in-world-first-airbnb-to-report-income-directly-to-danish-authorities (accessed June 1, 2020).

RogueWave Software (2017). 2017 Open Source Support Report: Trends, Issues, and Surprises in OSS, https://www.roguewave.com/sites/rw/files/documents/roguewave-open-source-support-report2017-vf4-digital.pdf (accessed June 1, 2020).

Sailer, Reiner, Jaeger, Trent, Zhang, Xiaolan, & van Doorn, Leendert (2004). Attestation-based Policy Enforcement for Remote Access [Research Paper] from CCS’04, Oct 25–29, 2004, Washington, DC., http://www.cse.psu.edu/~trj1/papers/ccs04.pdf (accessed June 1, 2020).

Seaman, Jeff & Tinti-Kane, Hester (Oct. 2013). Social Media for Teaching and Learning. Pearson Learning Solutions and the Babson Survey Research Group, https://onlinelearningsurvey.com/reports/social-media-for-teaching-and-learning-2013-report.pdf (accessed June 1, 2020).

Share Barcelona, https://share.barcelona/ (accessed June 1, 2020).

SourceForge, SourceForge.net (accessed June 1, 2020).

The Linux Documentation Project, www.tldp.org (accessed June 1, 2020).

Wang, Huaiqing & Wang, Chen (Mar/Apr. 2001). Open Source Software Adoption: A Status Report. IEEE Software, 18:2, 90–95.

** Professor of Law, University of St. Thomas School of Law (Minneapolis, USA). The author is gratefull for ongoing discussions about decentralized technology solutions with Craig Calcaterra. The author is also grateful for outstanding research assistance from Hayley Howe and research librarian assistance from Nicole Kinn. The author did not receive any form of financial incentive for authoring this article.

[1] John Deere, https://www.deere.com/en/ (accessed June 1, 2020).

[2] Carr, Clare (Apr. 13, 2015). The Data Behind the Average Article Lifespan. Parse.ly, https://blog.parse.ly/post/1768/data-on-article-lifespans/ (accessed June 1, 2020).

[3] Chaffey, Dave (Nov. 11, 2019). Mobile Marketing Statistics Compilation. Smart Insights, https://www.smartinsights.com/mobile-marketing/mobile-marketing-analytics/mobile-marketing-statistics/ (accessed June 1, 2020).

[4] Seaman, Jeff & Tinti-Kane, Hester (Oct. 2013). Social Media for Teaching and Learning. Pearson Learning Solutions and the Babson Survey Research Group, https://onlinelearningsurvey.com/reports/social-media-for-teaching-and-learning-2013-report.pdf (accessed June 1, 2020).

[5] Marsden, Dr. Paul (2012). The Social Commerce Handbook. Blacklick: McGraw-Hill Publishing.

[6] Open Source Initiative (2007). The Open Source Definition, https://opensource.org/docs/osd (accessed June 1, 2020), the OSD were originally derived from the Debian Social Contract: Debian (Apr. 26, 2004). Debian Social Contract, https://www.debian.org/social_contract#guidelines (accessed June 1, 2020). Because of the open source nature and its transparency, any definition of open source software is necessarily incomplete and tentative. Several alternatives and critiques were published: Feller, Joseph & Fitzgerald, Brian (2002). Understanding Open Source Software Development. Addison-Wesley; UK; Wang, Huaiqing & Wang, Chen (Mar/Apr. 2001). Open Source Software Adoption: A Status Report. IEEE Software, 18:2, 90–95; Capiluppi, Andrea, Lago, Patricia, & Morisio, Maurizio (April 2003). Characteristics of Open Source Projects [Conference Paper]. Proceedings of the Euromicro Conference on Software Maintenance and Reengineering, https://www.researchgate.net/publication/4010991_Characteristics_of_open_source_projects [PDF Available], 317–330; Krishnamurthy, Sandeep (April 2002). Cave or Community? An Emprirical Examination of 100 Mature Open Source Projects. First Monday, https://www.researchgate.net/publication/220167093_Cave_or_Community_An_Empirical_Examination_of_100_Mature_Open_Source_Projects [PDF Available].

[7] Open Source Initiative (2007). The Open Source Definition (Annotated), https://opensource.org/docs/definition.php (accessed June 1, 2020).

[8] Netcraft (April 15, 2010). April 2010 Web Server Survey, https://news.netcraft.com/archives/2010/04/15/april_2010_web_server_survey.html (accessed June 1, 2020).

[9] Black Duck Software (April 15, 2015). 2015 Future of Open Source Survey Results. Synopsis, https://www.slideshare.net/blackducksoftware/2015-future-of-open-source-survey-results (accessed June 1, 2020).

[10]RogueWave Software (2017). 2017 Open Source Support Report: Trends, Issues, and Surprises in OSS, https://www.roguewave.com/sites/rw/files/documents/roguewave-open-source-support-report2017-vf4-digital.pdf (accessed June 1, 2020).

[11] SourceForge, SourceForge.net (accessed June 1, 2020).

[12] Code, code.gov (accessed June 1, 2020).

[13] For a summary that illustrates the possible opportunities of blockchain-based governance instantiations see: Kaal, Wulf (Aug. 23, 2019). Blockchain-Based Corporate Governance [Research Paper]. Max Planck Institute Luxembourg for Procedural Law (Dec. 2019), https://ssrn.com/abstract=3441904 or http://dx.doi.org/10.2139/ssrn.3441904.

[14] The Linux Documentation Project, www.tldp.org (accessed June 1, 2020).

[15] MDN Web Docs, developer.mozilla.org (accessed June 1, 2020).

[16] See Google Search, https://www.google.com/search?sxsrf=ALeKk03NEi4O4C0iVEBpc3U_vkN-S4UPAQ%3A1591062869345&ei=VbHVXuLRFNeUtAbqzK2oBA&q=300+patents+Linux+kernel&oq=300+patents+Linux+kernel&gs_lcp=CgZwc3ktYWIQAzoECAAQR1DerwFYhc8BYOzPAWgAcAJ4AIABWYgBsgGSAQEymAEAoAEBqgEHZ3dzLXdpeg&sclient=psy-ab&ved=0ahUKEwii0JGJg-LpAhVXCs0KHWpmC0UQ4dUDCAw&uact=5.

[17] Sailer, Reiner, Jaeger, Trent, Zhang, Xiaolan, & van Doorn, Leendert (2004). Attestation-based Policy Enforcement for Remote Access [Research Paper] from CCS’04, Oct 25–29, 2004, Washington, DC., http://www.cse.psu.edu/~trj1/papers/ccs04.pdf (accessed June 1, 2020).

[18] Heller, Michael A. & Eisenberg, Rebecca S. (May 1, 1998). Can Patents Deter Innovation? The Anticommons in Biomedical Research. Science Magazine, 280, 698–701.

[19] Share Barcelona, https://share.barcelona/ (accessed June 1, 2020).

[20] Ballotpedia (2017). Local Government Responses to the Sharing Economy (ridesharing/homesharing), https://ballotpedia.org/Local_government_responses_to_the_sharing_economy_(ridesharing/homesharing) (accessed June 1, 2020); Chapman, Lizette, Eidelson, Josh, Cutler, Joyce E. & Bloomberg (Sept. 11, 2019). New Labor Bill Passed by California Senate Would Transform the Gig Economy — And Could Cost Uber $500 Million a Year. Fortune: Tech, https://fortune.com/2019/09/11/gig-economy-california-senate-uber-law-labor-rights-union/ (accessed June 1, 2020).

[21] Ritzau (May 18, 2018). In World First, AirBnB to Report Income Directly to Danish Authorities. The Local dk, https://www.thelocal.dk/20180518/in-world-first-airbnb-to-report-income-directly-to-danish-authorities (accessed June 1, 2020).

[22] Benkley, Yochai (2006). The Wealth of Networks: How Social Production Transforms Markets and Freedom. Yale University Press: New Haven.

[23] Ibid.

[24] Nordrum, Amy (Aug, 18, 2016). Popular Internet of Things Forecast of 50 billion Devices by 2020 is Outdated. IEEE: Spectrum, https://spectrum.ieee.org/tech-talk/telecom/internet/popular-internet-of-things-forecast-of-50-billion-devices-by-2020-is-outdated (accessed June 1, 2020).

[25] Reuters (Nov. 8, 2016). Tech Firms Struggle to Make Smart Devices Safer. Fortune: Tech, https://fortune.com/2016/11/08/struggle-internet-of-things-security/ (accessed June 1, 2020).

[26] Edelman (Jan 21, 2018). 2018 Edelman Trust Barometer: Global Report, https://www.edelman.com/research/2018-edelman-trust-barometer (accessed June 1, 2020).

[27] Ibid.

[28] See Chapter 3, footnote 6.