Monthly Archives: December 2014

MARLs: Market Adoption Readiness Levels

If you are going to send a rocket to the moon, you need to be very sure of every component and instrument that forms part of that expedition. Technology Readiness Levels (TRLs) are measures devised by NASA in the 1980s to assess the maturity of evolving technologies – devices, materials, components, etc. – that they use within their course of business. The idea is that when a new technology is first invented, it is not suitable for immediate application. New technologies are subjected to experimentation, refinement, and ongoing testing. Once the technology is sufficiently proven, it can be incorporated into the system – in this case, a spaceship.

There is a major distinction between digital applications which can drive the EU economy quickly and competitively in the global market, and the traditional techno-centric discourse which largely relies on the concept of TRLs.

The TRL model is driven by the degree of maturity requested from technology and is particularly suited to its original context. NASA typically deals with high-risk technologies that carry high development costs. It creates projects that are aimed at very few end users, and which yield important user data only after final deployment.

But rocket ships are not the technologies that drive modern economy. Most of what drives the EU economy are low-risk, cheap-to-deploy applications, which engage early adopters and generate data from users at early stages of deployment. These models require a broader set of parameters to account for the agile, iterative nature of technological innovation in the digital space.

A creative application will typically be low-risk, cheap to run (especially relative to rocket ships), easy to understand, and can potentially get millions of early adopters, even as an experimental proof-of-concept. This may account for the fact that the largest number of successfully-funded projects on Kickstarter in 2013 were developed in the music domain – a rise of 305% compared to the previous year. It is highly unlikely that someone will die from deploying music technology projects to fans / backers at early stages of development.

Yet early deployment will often guarantee a dedicated following with a vested interest in the project – people who will willingly contribute to the project, consider themselves privileged to be part of the select few who are “in the know”, and who can proudly display a sense of ownership of the invention for helping it get off the ground and become successful.

The appropriate way to measure the impact of these early adopter models would have to account for 1) the level of risk; 2) the number of potential early adopters; 3) potential to yield data from early adoption; and finally 4) the technology readiness. I propose we call them Market Adoption Readiness Models (MARLs).

For a potential investor, a large number of early adopters (and their substantial related datasets) have often proven to be sufficient incentives for investment and acquisition in early stages of development (which would traditionally occupy the space between the experimental TRL3 and more advanced TRL7). In the creative applications sector therefore, the market is extremely agile, with development of applications being cheap and typically low risk, and a great potential of investment and acquisition through clearly demonstrable social and economic benefits in early stages.

In addition to this, the agile nature of the digital market and the relatively cheap deployment of competitive applications requires active development and evolution of technologies via constant innovation and new iterations of products and systems. It is essential that the product constantly evolves, or else it will lose out to competition. It is important therefore to focus primarily on early deployment in order to maximise on the creative engagement with the tools by early adopter creative content maker communities. This ensures the potential for growth through feedback loops and iterative stages of active development, and capitalises on collaboration and agile and adaptive innovation for maximum market competitiveness.

For this reason I consider the MARLs model to be intrinsically associated with the disruptive nature of the Allternet, where continuous participation, constant innovation and creative engagement are encouraged via a series of open platforms.

Market Adoption Readiness Levels provide a framework for assessing technologies that may be creative and experimental, but usefully eliminate inertia, unnecessary delays, and creative paralysis. They generate conversation points and active engagement through early adoption, feedback and iteration. They leverage the ‘minimum viable product’ approach to digital innovation suited to an entrepreneurial environment where data is the primary currency.

This year, in order to gather a large amount of data about our solar system, a team of scientists and engineers have created a low cost, open source, open access, mass space exploration system called Pocket Spacecraft. Using Kickstarter, thousands of people have joined the project to create their own ‘minimum viable product’ expedition to the moon.

In 2014, even space exploration itself can be exempt from TRLs.

The rise of Generation C

In his paper Mapping Digital Makers, Julian Sefton-Green defines digital making as the process of using digital technologies creatively in order to make new products or digital artefacts . The approach to this form of making has its roots in the world of computer programming, but although programming skills often form part of the process, concepts from art and design, engineering and problem solving are also significant components of the intellectual framework. Active engagement with digital tools contributes to an understanding of how digital media work, and in so doing both a more creative and a more active critical engagement with prevailing technological environments results. With an understanding of how digital technologies can make meaning for people comes opportunity for enterprise in creating new value and meeting market needs.

David Gauntlett’s Making is Connecting explores the ways in which digital making constructs participatory cultures that positively transform societies. Central to that process is the notion of play. Gauntlett uses Lego bricks as a practical, physical example of the kinds of processes that digital making encourage: the ability to create and re-create from simple building blocks. As a frequently improvisational and social activity, digital making includes trial-and-error and collaborative approach to learning. Digital making not only contributes to the making of games, but also emulates game-like thinking in its approach – seeking solutions, reaching goals and solving problems through exploration and experimentation.

Digital making is often expressed as ‘hacking’, which presumes a hands-on approach to re-using, reappropriating, remodelling and reinventing existing technologies in order to make new and previously unimagined ones. Those new technologies may be virtual, physical or some combination of the two, but the process of digital making that underpins the hacker activity is a productive and creative one that blurs the line between user and creator, producer and consumer, performer and audience. Creative processes from pre-digital media forms provide a range of metaphors with which to understand digital making: e.g. editing, composing, producing, developing. Gauntlett’s Lego example provides perhaps the best analogy, since digital making is an inherently iterative process, in the sense that everything that can be made in the digital environment can be remade and repurposed again.

Digital making not only retrieves and reinforces the agency of citizenry when it comes to culture and media, it also provides a uniquely fertile space for creative enterprise and entrepreneurship due to the abundance of raw materials, the removal of physical restrictions on creativity and the speed with which a new tool can be taken to market, tested, altered, revised and remade. Digital making is both creative engagement and empowering opportunity with a low entry barrier, low risk and potential for high rewards.

It’s helpful to think of the shift in patterns of media creation and consumption as not simply some new behaviours and approaches, but as representative of a complete generational shift. Digital paradigms for Generations X and Y were web access, content delivery and information consumption. Today, we are in the world of Generation C, who are instead focused on Creation, Curation, Connection and Community. According to a research report released by Google 90% of Generation C are Content Creators.

Following data showing that “the recording industry is making more money from fan-made mashups, lip-syncs and tributes on YouTube than from official music videos” (IFPI), some of the Creative Industries who had previously been reluctant to accept new ways of participation and co-creation of content, welcomed content creators as legitimate alternative routes to monetisation in content co-creation. According to Francis Keeling, global head of digital business for Universal Music Group:

“It’s a massive growth area. We’re very excited about the creativity of consumers using our repertoire and creating their own versions of our videos”

The Google report claims that 39% of Generation C are aged 35 years or above, thus dispelling the myth that Generation C are strictly young digital natives. Amongst those are professionals who are regular content creators, and 60-70% regularly curate online content. Generation C paradigms are therefore different from those of Generations X and Y: their priorities are web uploads, content creation and information curation.

In this new Generation C-dominated market, Creative SMEs are becoming leading cultural producers. Generation C content creators are active contributors to culture and major cultural influencers, who build followers and a critical mass, which in turn creates opportunities for monetisation. Creating culture is therefore important for business. Every content creator who is able to earn from their content is a micro-company, and therefore monetization of creative content is contributing to the rise of the numbers of Creative SMEs.

Apple reports that the iTunes App Store has generated over €11bn for creative developers since its launch in 2008. An equivalent, but open, agile and fast technology framework for content creators allowing a combination of virtual and tangible applications could contribute to a considerable profit for EU Creative SMEs, spearheading innovation in manufacturing, interaction and communication, and driving new markets and business models.

Creative SME Content Creators require tools based on open platforms which they can reuse, recycle and upcycle, suitable for agile development environments which allow ad-hoc creation and connectivity through mesh networks, and fast uploads into the cloud. The aim is to create a rich ecosystem which impacts on culture, society, employment, and economic profit.

In other words, Generation C are looking for their own Lego bricks. By creating Application Programming Interfaces (APIs), Graphical User Interfaces (GUIs) and Tangible User Interfaces (TUIs) that connect with existing bodies of data and digital cultural artefacts, we lower the barrier of entry to a world of content creators; we enable the kind of play that creates revenue for stakeholders right across the value chain; and we contribute to that participatory culture.

[co-authored by Andrew Dubber]

Legislation and ethics in the Allternet

In 1935, Edwin Armstrong introduced his employers at RCA to his new radio broadcasting technology, Frequency Modulation. His employers saw FM as a legitimately groundbreaking technology, a massive improvement to existing broadcast systems, but also a disruptive innovation to their existing business models and their status quo. For the next 19 years, they lobbied government and fought successfully in the courts against the technology, driving Armstrong to poverty and extreme hardship.

A new technological ecosystem provides both opportunities and challenges for a society and to those interested in retaining the incumbent technological infrastructures. Those challenges are often legal in nature, partly because the law is a powerful mechanism of control and prevention of change – but also because by disrupting the ways in which we communicate, behave and make use of information, we often create case scenarios that lie outside those imagined as possible at the time the relevant laws are written. As a result, these challenges need to be identified, negotiated and managed if the disruptive technologies are to be harnessed for the good of society.

Legislation frameworks need to support innovation for the greater good. However, in order for innovation to take place, transgression of the letter of the law is often inevitable. That does not mean that ethical issues such as privacy, safety, fairness and the agency of individuals can be ignored – quite the opposite. Where legislation does not reflect the realities of the new technological environment, fairness and the interests of the greater good are often set at odds against the legal infrastructure of the status quo.

Innovations should be tested in terms of their capacity for emancipatory potential – not simply for economic stakeholders but for the participation of all stakeholders and citizens. The Swedish concept of ‘lagom’ (just enough) provides a useful guiding principle for business enterprise in the field. While there is clear urgency to innovate, invest and exploit in the field of IoT, a rapacious ‘gold rush’ mentality will do more harm than good.

Experiments with IoT need to consider perennial ethical principles – in terms of privacy, security, equality, labour exploitation, protection of the vulnerable, and so on – but it’s important to understand that the legal aspects and normative values have to be considered and reflected upon at a very early stage in the design and implementation cycle. IoT innovation is currently in its early experimental stage, but already it is challenging existing frameworks and regulatory systems that were designed to operate within a different ecosystem.

Dialogue between innovators and legislators needs to be ongoing, and focus on the ethical ‘first principles’ from which the laws arise, rather than from the rules themselves. Disruptive innovation will often be transgressive by nature, but it need not be at odds with what is good for society, culture and the economy.

Once again, Uber provides us with a very good case in point. The service is actively breaking new ground and as a result new legislations are already needed. London cab drivers traditionally require years of training and testing in “the knowledge” but that registration and testing process is seemingly made redundant by technological advances that use GPS. Arguably, the principle (safe passage, good service and fair prices to customers) still applies, but the mandated mechanism that ensures that principle (the knowledge) is no longer strictly required.

As a case study Uber is useful from an ethical and social perspective within the context of European policy. While Uber is massively disruptive, it has also been shown to be open to misuse of information and unethical practice by staff of the service. This is problematic because it adheres to a logic of capital that, like the industry it seeks to disrupt, prioritises the maximisation of shareholder return over social good.

It’s important for IoT innovation to begin from a moral, ethical and legal standpoint, as information carries legal, moral and ethical values and affordances – and especially because IoT technologies provide for communication without the immediate mediation of a human actor – even though that information may be used in a way that directly affects human experience.

Within Europe, we have, right at this moment, a unique opportunity at a time of significant change to engineer significant technological disruption in the interest of the greater societal good, and balance that interest with the need to incentivise innovation and investment in the IoT space. To do so requires that we favour ethics and the social good over the specific requirements of legislation that may no longer be entirely fit for purpose. In the case of Uber, while providing ethical and legal challenges, which need to be addressed, its model is also predicated on the idea that the company makes money if the drivers make money. In this respect, as a profit sharing participatory system, it also provides a case study in economic innovation.

Building the Allternet ecosystems

As much as any social, political and economic factor, the standardisation of railway tracks throughout America in the mid 1800s contributed to the creation of a coherent multi-state nation. Communication, mobility and seamless transition were made possible with the advent of trans-national rail. Not just viable businesses, but entire towns and cities were built on the back of the single, consistent gauge railway and the Pacific Railway Act of 1863 that ensured it.

Likewise today, for the creation of successful and innovative business ecosystems within the frontier of the Allternet, it is necessary to build cohesive, interoperable protocols. These allow for creative, useful and experiential devices and services to be developed to run on them.

Protocols must be centred on easy to understand, layman-level classifications of network types and capabilities. Allternet protocols require clear and simple interfacing through APIs, graphical and/or tangible user interfaces (GUIs and TUIs) that give a high degree of flexibility and freedom. Certification can happen in a modular fashion. As with open source technologies, we can certify an element, people can develop it, and we pass that certification on through the system.

These protocols should not be locked to a particular operating system or proprietary environment. It’s crucial to preserve creative possibilities as well as incorporate open frameworks in the design process. Certification and licensing provides attribution for design inheritance (as with Open Product Licences). This degree of openness and simplicity provides for a variety of new business models and services that can be made available to potential content creators and participants.

Data provides transparency. For example, when using Uber, the passenger requesting a ride knows exactly where the cab is, has a clear idea how much the journey will cost and knows the make, model and licence plate of the car as well as what the driver looks like. For drivers, Uber provides data that reports traffic information, the best routes, highlights busy periods and ways in which drivers can maximise their revenue so they have greater agency as well as a clear basis for decision making about their own work.

Stakeholders provide choice. The creators of simple protocols are, metaphorically, laying railway tracks. The stakeholders and content creators build a wide variety of trains and ancillary services. They may create a luxury passenger car or a goods train. However, standardisation of the tracks is important, because otherwise there is no connectivity.

Sharing provides trust. If the track providers do not take too much revenue (if, for instance, they demand less than a quarter of profits generated by their use), then there is room for stakeholders to make money. This not only incentivises creativity and innovation in new uses of those tracks, but also establishes the necessary trust required to invest in building upon that infrastructure.

Transparency, choice and trust encourage participation. The people who take passengers down the tracks are the service providers. If it is made easy to build on those tracks, then anyone can use them. That in turn creates employment – or further entrepreneurship – that also contributes to that ecosystem. In other words, there is an opportunity for monetisation by contributing to the platform.

If, on the other hand, the contributor is not given the opportunity to make a profit or that profit is too small or risky to incentivise participation, then the platform itself will not make a profit. The Allternet provides a context for the creation of a non-exploitative service to both clients and contributors. Stakeholders view their contribution and involvement as a partnership with the platform.

Just as they did with the establishment of the standardised railway, new and unimagined types of businesses can flourish, and new communities can emerge and thrive, enabled by Allternet protocols.

Powers of data magnitude

Powers introIn their 1977 short film Powers of 10, Charles and Ray Eames demonstrate that different kinds of understanding are possible at different orders of magnitude. When designing data-driven systems, it is crucial to analyse data at the human scale as well as at the mass aggregate scale.

Today we have a model for understanding data at different levels of magnitude: Google Maps. We can zoom in and out of geography, and are able to distinguish and analyse continents with a level of detail appropriate for the scale. That does not include minutiae such as streets, houses and parks. In that frame, we can identify data that is grouped at the level of Europe, Africa and so on – and we do not require more complex insights at that level. We zoom in to distinguish features such as cities and their geospatial relationships. We are able to orient ourselves with more and more levels of granularity, or we can zoom out again to get a sense of the overall picture.

At the human scale, there is a very different requirement of data mapping than there is at a global scale. As such, the notion of ‘zooming in’ provides a very good metaphor for how we should design intelligent data systems.

Data is not only stored in the cloud, it is also analysed in the cloud. Smart IoT systems use Big Data filtering, create ontologies and classifications in order to make sense of that data, consider the context of data usage and use AI to train systems to recognise patterns in data. The wealth of aggregate data accumulated by the Allternet provides, in itself, opportunities for understanding at a high level of analysis, but that analysis may not be relevant at the human scale.

In order for ‘Internet of Things’ projects to be validated, it is essential to run pilots deploying agent-driven applications. In this way, it will be possible to test, for instance, a ‘System of Systems’ in physical space, in relation to a scale comprehensible and useful to the people using the devices within that system. In this way, these projects and systems are contextualised and understood within the broader Allternet space.

There are those who advocate creating a system of systems in abstraction. There is another school of thought that believes we should start from the users. Neither of those two is better nor more important than the other. Instead, it’s about the rules or assumptions that can be made at each level. At the level of reconnaissance, there is a more abstract relationship with data which is about describing contours. At the level of the individual, the relationship is with the person and their specific needs and requirements. Not only are both valid, but there are multiple layers of understanding that can be reached at different levels of magnification.

It’s important not to make assumptions about somebody sitting on the street based on data that is mapped from the perspective of an altitude of 10,000 feet. When you’re sitting next to that person, you will have a very different understanding of what data is useful to you.

Designing data-driven systems is about creating truly intelligent systems that understand and appropriately respond to scale (as with the Powers of 10) – as well as to time, since data takes on different kinds of meaning over time. If you create one set of descriptors at a particular time, you will inevitably need to renew those descriptors when conditions change. The Allternet is, in this respect, like a living ecosystem.

As with data – so with ideas. An idea is always a result of particular affordances and parameters that are on offer at that particular point in time. In the case of EU-funded projects, this is usually mapped up front, rather than allowed to evolve. Any intelligences that we can draw from these projects change too. Because EU projects are locked in the first moment, they struggle to create a good business model. The project is cemented in the past before it has begun. Good business is always a living ecosystem. It needs to continually innovate in order to survive, keep ahead of competition, and reinvent itself.

Understanding data at scale (and over time) reflects the fact that the Allternet acts as a living ecosystem. From that adaptive, reactive and context-aware starting point, novel and disruptive IoT business models can be supported.