With the advent of the Internet and the development of new digital technologies, the economy is following a trend of decentralization. The most innovative environments are open source communities and peer production is on the rise. The crowd innovates and produces. But the crowd is organized in loose networks, it is geographically dispersed, and contributions to projects follow a long tail distribution. What are the possible reward mechanisms in this new economy?

Our thesis is that in order to reward all the participants in p2p economic activity, and thus to incentivise contributions and make participation sustainable for everyone, we need to do contribution accounting: record everyone’s contribution, evaluate these contributions, and calculate every participant’s fair share. This method for redistribution of benefits must be established at the beginning of the economic process, in a transparent way. It constitutes a contract among participants, and it allows them to estimate their rewards in relation with their efforts. We call this the contribution accounting system.

For the rest of this article we will try to explain why a contribution accounting system is needed in a more decentralized economy, and unavoidable in a p2p economy.

Contribution accounting and exchanges

First, we need to make a distinction between a contribution accounting system and an exchange system. Suppose that we have 3 individuals picking using one basket. The contribution accounting system keeps track of how many cherries everyone puts in the basket, so that when they sell the basket on the market they can decide to redistribute the revenue in proportion to everyone’s contribution. It describes how contributions from multiple individuals amalgamate into a product, during a co-production processes.

Once a product is created, i.e. once the basket is full and ready to go to market, it can be exchanged using an exchange system: barter, currency, etc.

The contribution accounting system is not a currency, not a barter system. It doesn’t refer to an exchange between our 3 individuals who are picking cherries, or between them and another entity like a company. They are not getting paid a salary in exchange of their work. They are collaborating, they all add cherries into the same basket, which is their product to be. The exchange might occur at a later point in time, once their basket is full and ready to go to the market. Meanwhile, they all share the risk of having their cherries being eaten by birds, or of not getting a good price for their basket.

Production processes

A production process that requires more than one individual can be based on the following 3 arrangements, or on a combination of them:

• stigmergic coordination–  Participants don’t have aligned goals, don’t maintain a relationship other than being contributors to the same process. Ex. this is how Wikipedia is built. 
• cooperation – The goals of participants are not necessarily aligned. Ex. in a corporation employees and business owners usually have divergent interests and goals.
• collaboration – Requires a large degree of alignment in goals. Ex. a group of individuals climbing a mountain together.

The traditional capitalist economy is mostly about cooperation, which doesn’t require an tight alignment of interests and goals. Production is sustained through an exchange process, where workers exchange the time they spend on different tasks against wages. The exchange process transfers risk from workers to the owners of capital, but at the same time, the workers are stripped of their rights to the output of their labor. Workers cooperate (despite some inconveniences and misalignment in interests and goals) with the owners of capital in production processes because there exists an economic dependency between the two groups. Workers need money, which are by far the predominant means to acquire basic necessities. On the other side, the owners of capital need labor to generate more wealth. This economic dependency is not symmetrical and makes the system prone to abuse, which explains the existence (and necessity) of unions to counterbalance the tendency for exploitation.

In peer production we have a blend of the 3 arrangements mentioned above, mostly coordination and some stigmergic collaboration. In general, no one works for anyone else. Everyone involved is a peer, an affiliate of a peer production network. The p2p culture prescribes that the output of a collaborative and participatory process should not be owned or controlled by anyone in particular, but shared among participants in a fair way. Immaterial artifacts that are produced in such way (such as software or hardware designs) are usually released as commons (they are openly shared). Material goods can be exchanged on the market, and the revenue generated is shared among all the participants. Service-based models also exist, where services are exchanged on the market against some form of payment, which is redistributed to everyone involved in the providing the service. A good example of service-bases p2p model is the Bitcoin network. If we focus only on the mining aspect, minors form a open network of peer participants, they collectively maintain the hardware infrastructure of the entire network. Minors are rewarded in proportion to the computing power that they provide to the network.

The normal and the long tail modes of production

normal mode of production

In the traditional capitalist economy wages should be regulated by the free labor market, if we make abstraction of all sorts of mechanisms through which this market can be biased (labor unions and governmental intervention included). The market is responsible for the difference in salary between an engineer and a clerk. The notion of jobimplies that a salary is determined and agreed upon before the employee starts working (with the possibility modify the salary based on performance). Since the amount of $ per hours of work is pre-established, the capital owner needs to make sure that the employee produces enough during the work hours. Therefore, a new role is needed within the organization to guarantee this, the beloved project manager. Traditional organizations spend a lot of energy doing time management, because usually the interest of the worker is not perfectly aligned with the interest of the capital owner (see cooperative production above). Classical organizations operate on the normal mode of production (from the ”normal curve” or ”bell curve”), where the number of workers is minimized, and the majority of employees in a category of roles produce almost the same amount. Very few workers produce less than the norm, because they are eliminated (i.e. fired). Very few produce more, because there are no incentives to do so, the association with the mission of the traditional enterprise is weak, the sense of belonging is usually low (usually fabricated by the HR department), the sense of ownership is almost absent, etc.

long tail mode of production

The situation is very different in a peer production environment, which is open to participation, is decentralized in terms of allocation of resources, and uses a horizontal governance system.

In peer production, we see a log tail distribution of contributions, which means that a very large number of individuals are involved in production, only a very small percentage of those contribute a lot, the great majority of them contribute very little, and most of the production is done by those who make small contributions. A prearrangement on revenue is impossible in this context. First, because the production process is very dynamic and relations of production cannot be contract-based. Second, the process involves a great number of individuals that are distributed all over the planet, therefore it is impossible to do time management. Moreover, no one can force anyone else to work more. In this mode of production we need to evaluate rewards after the fact, based on deliverables or based on the type of activity and its potential to increase the probability of production of valuable products. A system is needed to account for everyone’s contribution, to evaluate these contributions and turn them into rewards.We call this an access to benefits algorithm.

In some sense, the access to benefits algorithm is a distributed solution to time management, which can be applied to large scale and very dynamic peer production processes. It embodies positive and negative incentives, and can contain parameters to influence individual participation and quality of contributions, it can regulate behavior, it gamifies production. For example, a reputation system can be tied to the access to benefits algorithm: a higher reputation results in a higher reward, all other things being equal, and vice versa. Moreover, it can also contain parameters to incentivise periodic and frequent contributions, and to prioritize important processes.

Contribution accounting and network resource planning

The long tail mode of production needs a contribution accounting system in order to allow fair redistribution of rewards. It allows participants to record contributions of various types and it uses an access to benefits algorithm to turn them into benefits. But this is only the first part of the story.

In the OVN model contributions are attributed to the creation of resources, which can be documents, designs, parts or full prototypes, etc. (some contributions go into infrastructure of community development and they lack clear resource or deliverables). From the resource level, contributions aggregate at the project level. A project is an open venture, or a business unit. It is the smallest unit within the OVN that can generate all sorts of benefits, including revenue.

The fact that contributions can be attributed directly to resources (not projects) is very important for commons-based peer production (CBPP), which builds on open source. On Github, pieces of open source software (OSS) can be picked up by someone and remixed into something else. Open source hardware (OSHW) development follows the same path, i.e. designs (mechanical, electronic, optical) are forked and remixed. This ability to fork and remix parts of more complex systems makes open source development a very efficient process. This explains why modularity and interoperability are very important properties of OSS and OSHW. If rewards are envisioned for the work done, CBPP needs to find a way to account for contributions at the resource level and to track the way resources are put together in different contexts (projects are considered contexts). If contributions are only recorded at the project level, projects become silos of economic activity with a reduced possibility of benefits flows between them.

Taking into consideration the structure of OSS development, the solution to the benefit/reward redistribution problem is to attach some information to individual resources created that allows their reevaluation later, when they get remixed and integrated into larger systems, in other contexts. The metrics of evaluation can vary depending on the context. This is the role of the network resource planning system NRP, which allows benefits/rewards to propagate upwards through value streams and the creation of a single resource can generate rewards from many different sources (many projects), depending on how many successful projects are using it.

This goes even further, because this same NRP also provides a growth mechanism for CBPP networks. To illustrate this, imagine that members of a CBPP community decide to attribute equity to resources that are created by other communities. (Example: SENSORICA decides to integrate a piece of open source hardware developed by another OSHW community). First, why would SENSORICA affiliates decide to diminish their revenue by giving equity to other groups when they can just copy the open source design? The economic rationale is to reduce efforts required to internalize new capacity (new knowledge and know how around that piece of open hardware) and to increase the speed of execution (a first to market advantage). CBPP networks grow by affiliation. By offering equity to other CBPP communities they are essentially building bridges to innovate faster and improve production processes. This is the higher-level structure of networks-of-networks (see the Open Alliance).

We believe that in order to sustain the CBPP we need to create infrastructure that allows attribution of value-related properties to individual resources, to allow reevaluation of these individual resources in context, and to facilitate the formation of networks-of-networks that preserve the individuality of every community part of it, but at the same time brings them together on the same economic platform.

Contribution accounting in transition models

As the economy transitions to a networked state, existing organizations are trying to adapt. We already see traditional corporations going from in-house R&D, to outsourcing R&D and more recently to crowdsourcing R&D. This movement is forced by the need to innovate fast, and by the fact that open source lowers the price to a point where traditional high-tech corporations can be put out of business. Crowdsourcing R&D means utilizing all sorts of schemes to attract the participation of the crowd into innovation processes that are sponsored by these corporations. In early crowdsourcing practices corporations tried to control the innovation by signing non-disclosure agreements with the participants. Crowdsourcing platforms were created to match corporate projects with skilled individuals. The practice was competitive, i.e. the company would chose a winner among different proposals, and usually the winner was rewarded with money. This practice gradually became more open, since the first iteration of crowdsourcing platforms were not very successful in attracting highly skilled individuals. In order to attract innovation, in order to grow open innovation communities around them, corporations need to think seriously about the reward mechanisms they put in place. It is not so difficult to understand why the early crowdfunding platforms were not very good attractors. I would not compete in a call by a company to design something for a few bucks, with a good probability of losing the race, knowing that the company will monopolize the work and probably make a lot of profits on it. The trend is to go from closed crowdsourcing to truly open source innovation, which must be accompanied by a broadening of the reward system. Since companies are going to deal with the crowd more and more, they need a contribution accounting system to account for contributions. See this presentation by SENSORICA making the distinction between competitive crowdsourcing and collaborative crowdsourcing.

In parallel to the adaptation of traditional companies we also see the creation of hybrid organizations and models. For example, in the realm or hardware, we have the emergence of ecosystems like Arduino and 3D Robotics/DIY Drones. They are composed of a traditional for-profit organization surrounded by an open source community. This post describes the situation. The difference here is that in most cases the open source community pre-existed the traditional for-profit, the later being created to manufacture and to distribute the products that are based on the innovation created by the open community. These hybrid models, the ones that are sustainable and successful, maintain an precarious equilibrium between the profit motive that can arise within the centralized traditional organization the open and sharing culture within the open innovation community. In some cases, this equilibrium is not maintained and the synergy between the two entities disappears, destroying the ecosystem. This was the case of Makerbot and the RepRap community, well captured in the Netflix documentary Print the Legend.

Photo by Muffet

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The following are the key “lenses” through which I view and discuss the ongoing transformation to panarchy. Each of these lenses provide crucial understandings and insights into facets of panarchy, but panarchy itself emerges only as a result of the interactions between all of these elements. Like all complex systems, panarchy itself is an emergent property.

• Commons
• Complex Systems & Networks
• From the Bell Curve to the Long Tail
• Plurality & Diversity
• Cooperation
• Peer Production
• Open Design

Commons

Commons are systems of shared resources. A lifetime of work by Economics Nobel Prize Recipient Elinor Ostrom reveals a plethora of case-studies with insights and strategies for governing our commons. There are many kinds of commons — ecological, social, information, and technological — but the one thing they all have in common is the need for thoughtful management in order to insure sustainability for future generations.

Complex Systems & Networks

Complex systems and networks are systems that are more than the sum of their parts. Because the parts are interconnected, dynamic relationships between the parts result in emergent properties at the system level. In complex systems “more is different.” Complex systems and networks can range from too rigid to too fluid, but the most interesting of them have mechanisms of self-organization that move them towards a robust and resilient balancing act at the “edge of chaos.”

From the Bell Curve to the Long Tail

The bell curve defines systems with normal distributions where averages are meaningful (because populations are homogenous) and “mass” dynamics are the norm. The long tail, or power law, distribution makes averages meaningless and replaces the “mass” with a plural multitude of diverse members. The transition from the bell curve to the long tail is as relevant in philosophy and culture as it is in economics and politics.

Plurality & Diversity

Plurality refers to the fact that new dynamic systems consist of many interacting parts, whereas diversity refers to the condition that exists when those parts are different. Neither plurality nor diversity is itself sufficient for panarchy, but together they provide an accurate description of the new landscape. This new “multitude” is unlike any civil polity that has existed before, and it will demand infrastructures for governance and economics that are equally unique.

Moreover, governance itself has to exhibit authority, legitimacy, and continuity. We are on the cusp of a “Greek moment” wherein we are faced with the challenge of creating new forms of governance that can be responsive to the needs and demands of a diverse and mobile “global civil society.”

Cooperation

Cooperation is responsible for everything you see around you. Civilization itself would not exist if humanity had not overcome the challenges to cooperation. Much is known about the conditions necessary for cooperation to emerge and succeed, and recently we have seen an explosion of technologies that allow for new forms of cooperation. Much of that cooperation manifests in the new economy where community currencies, smart contracts, and peer production exist in a zone of experimentation and innovation.

Peer Production

Peer production (or as Yochai Benkler terms it “commons-based peer production”) is a new form of bottom-up collaboration to fulfill economic needs and wants. The emergence of “maker” culture is predicated on the consequences of technologies of cooperation. Peer production does not have to be merely economic however. The world of peers produces information at an ever-increasing rate, and also produces new shared understandings, cultural norms, social movements, and political pressures. The new infrastructure that connects people catalyzes peer production in a feedback loop with crucial consequences for our world.

Open Design

Open design refers to the challenge of planning for an unpredictable system what futurist Rick Smyre calls “Preparing for a World that Doesn’t Exist — Yet.” But we can design for adaptability if we follow the insights from Stuart Kauffman’s investigations into evolution and biology. Namely, evolutionary process result in complex systems that maximize their own evolvability. In other words, they evolve to evolve better.
Consequently, Michel Bauwens has claimed that what we need is “an infrastructure for open everything.” This means crafting social and technological systems that are based on a diversity of open standards and are easily extensible. Such an approach insures continuous innovation as landscapes shape their inhabitants and in turn those inhabitants shape new landscapes.

Panarchy: A Multifaceted View

So, how then do these lenses combine to give us a better view of panarchy as a whole?

1. Technologies of cooperation allow human beings to collaborate in ways never before possible, i.e. 1) faster, 2) mobile, and 3) global.
2. A heightened awareness of the climate crisis and the earth as a literal ecological commons compels people to do more with less, i.e. to “make less more” to reduce the combined footprint of 7 billion people by sharing physical as well as information resources. Because technologies of cooperation are ideally suited to building global sharing mechanisms, the result is the emergence of new global commons.
3. Because these new networks are complex systems, they behave ecologically, with similar dynamics, except at faster time scales with larger global reach. In addition, understanding them requires understanding the shift from the bell curve to the long tail.
4. If we are to embrace these changes rather than retreat into an imagined idyllic past, we must embrace both plurality and diversity as core elements of a healthy future civilization. The only structure that can do so is one that operates on what I have called “The Difference Engine” and it embodies principles of open design in social, economic, technical, and political spheres.
5. That system of overlapping, interwoven, interpenetrated, diverse, cooperative networks is panarchy.

To engage with the original please go to Panarchy 101: 7 Crucial Lenses by Paul B. Hartzog

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Viral content seems democratic. But it’s still mostly controlled by big media companies

Marta Figlerowicz, writing for Jacobin, lays out the duplicitous realities of Netarchical Capitalism…

The first YouTube video went live in 2005. The following year, the site began seeing its first viral hits.

Judson Laipply’s “Evolution of Dance,” posted in 2006, reached seventy million views in about eight months. Justin Bieber started uploading videos of his performances in 2007, and within a year he was an Internet star.

Laipply’s and Bieber’s successes seemed extraordinary and astonishingly fast at the time. But the pace and frequency of such viral rises only continued to increase. In April 2010, Greyson Chance became YouTube famous less than a week after posting a cover of Lady Gaga’s “Paparazzi.” Three months later, Yosemitebear’s “Yosemite Mountain Double Rainbow 1-8-10” video blog entry skyrocketed to prominence just as rapidly as the Gregory Brothers’ auto-tuned “Double Rainbow” song.

The subsequent years have provided abundant evidence that our communication paths are becoming even more networked and seamless. We’ve reached a point where anything — not just a song, but any kind of cultural production, including a tweet — can go impossibly, massively viral. Seemingly random online events can attract global attention within days, or even hours, of being posted.

These episodes of sudden ubiquity have sparked dreams of an alternative, more democratic aesthetics. And at first glance, virality might seem like an equalizing, socially subversive phenomenon — a way for the online masses to choose their stars directly, circumventing the traditional gatekeepers and tastemakers.

In 2012, writing in a special issue of Women’s Studies Quarterly on virality, Christine Bacareza Balance hailed the rise of Asian-American YouTube stars as part of a new, grassroots aesthetic movement in which the disadvantaged and the marginalized were finally getting the chance to speak directly to crowds. Similarly, Karine Nahon and Jeff Hemsley speculate in their 2013 book Going Viral that virality might offer observers an extraordinarily clear picture of current social norms and interests.

But a closer look reveals a grimmer reality. Virality is not really a democratic, participatory phenomenon. Instead, it is shaped by the extreme inequalities that the digitally enhanced capitalist market creates. Indeed, one might describe virality as our most immediate, everyday model for what it’s like to live among the 99 percent.

The apparent contingency and grassroots origins of viral events are something of an illusion. Ordinary people on the Internet aren’t usually the ones who make an event go viral. Major sites, like BuzzFeed or the New York Times, or already-popular figures, like Kanye West or Donald Trump, more regularly trigger the process. In fact, as Sharad Goel and his collaborators argue, performers backed by powerful broadcasters and celebrities are the only ones statistically likely to go viral.

Goel and his colleagues distinguish between two kinds of “popular” (i.e. massively shared) online events: those originating from very large broadcasts, and those originating from a huge number of individual acts of social sharing.

The former — for example, a post on the New York Times website, a BuzzFeed listicle, or a Twitter comment made by Beyoncé — bear a strong resemblance to the mass media model that prevailed from the sixties to the nineties; the latter — for instance, the average Jane Doe bringing something to the attention of the John Does on her mailing list — has the feel of a bottom-up movement and is more associated with the term “virality.”

Yet as Goel shows, the Internet’s giant broadcasters — its version of the mass media — are overwhelming the ones that make an online event stand out. The vast majority of the episodes we describe as “viral” have preexisting online celebrities and major news sources to thank. Indeed, being picked up by one of these network hubs is the only reliable predictor of mass online recognition.

In addition to these oligarchic drivers, going viral is extremely rare in statistical terms. Networked dissemination obeys what mathematicians call a “power law.” The vast majority of online content — more than 99 percent of it — inevitably spreads among only a handful of users. But given the structure of our online networks, it is also almost statistically inevitable that a very small percentage of content will shoot around the globe, reaching a vast audience in little time at all.

While the number of viral events continues to increase, the chance that any single video or meme will take off has not substantially increased. What has expanded is the number of Internet users trying to attain viral status.

As Goel and his coauthors report, “even moderately popular events occur in our data at a rate of only about one in a thousand, whereas ‘viral hits’ appear at a rate closer to one in a million.” By contrast, “the vast majority of [sharing] cascades — over 99 percent — are tiny and terminate within a single generation.”

This distribution pattern seems relatively constant no matter how large the network. A huge gap separates the 999,999 posts that nobody re-shares and the one that gets apparently boundless airtime.

In this sense, the few artists or performers who manage to go viral are less a grassroots cultural movement and more an unwitting 0.01 percent. They are the tiny minority whose exorbitant, disproportionate success overshadows the innumerable artists and performers who do not receive — and can never really hope to receive — such exposure.

Unsurprisingly, the difference in remuneration between the less networked artists and performers and those backed by broadcasters is stark. For most artists, online distribution of creative content does not bring in much money, even if one of their songs manages to garner the coveted thousands or millions of views.

Data journalist David McCandless reports in a series of infographics re-published last year in the Guardian that a signed solo artist needs to sell 457 CDs per month to earn the US minimum wage. Online, sales must be higher: 450 or so CDs equals 1,826 downloads on iTunes or 5,478 on Amazon. Streaming services pay even less. To earn a living wage, an artist must net 172,206 plays on Google Play, 666,158 on Rhapsody, 1,117,021 on Spotify, or 4,200,000 on YouTube. This is actually an improvement from McCandless’s 2010 figures. But the numbers are still sobering.

Few artists other than expensively produced, well-advertised stars achieve this kind of download and play rate. Even the most popular singles by recognizable alt-pop bands — say, Chairlift, Matrimony, or Beach House — typically take one or two years to reach a total of forty or fifty million YouTube views. The Internet simply isn’t enough. Online success must be parlayed into a concert tour, an advertising gig, or a contract with a major label before musicians see a healthy jump in their income.

That’s not to say that nobody is making money from mass online dissemination — quite the opposite. Despite the relative unpopularity of most of their content, companies like Amazon and iTunes generate a disproportionate share of their profits from what Chris Anderson has called “the long tail” — songs, books, and other products that only find small, niche audiences.

Consumers value the seemingly unending array of content Amazon and others can offer, and firms are rewarded handsomely. Artists in “the long tail,” meanwhile, don’t make anything close to a living wage.

In addition, as Astra Taylor notes in The People’s Platform, artists who post their work online (especially to open-access sites) often risk losing copyright control over their art altogether: those who copy or re-embed creative content often do not credit — let alone compensate — the original author. Instead of fledgling artists rising on the shoulders of empowered consumers, the contemporary viral-centric paradigm further calcifies the economy’s deep inequalities.

One relatively recent attempt to think about virality in this fashion is the 2013 film 20 Feet From Stardom. The documentary follows a number of predominantly black and female backup singers who worked for mostly male and white pop stars from the eighties onwards. The women interviewed sang with Mick Jagger, David Bowie, Michael Jackson, and Joe Cocker; they also sometimes dubbed white female stars.

But none of them went on to attain star status. They see the documentary as a final chance to achieve appreciation and recognition. This hope is slowly corroded by the fatalistic gaze the film turns on the Internet — through which the youngest of these singers, Judith Hill, has just briefly become a viral celebrity.

Hill was one of Michael Jackson’s backup singers until his death in June 2009. Shortly before the documentary was shot, her cover of one of Jackson’s songs exploded on YouTube, garnering millions of views within days. Repeatedly set against her predecessors, Hill at first appears to be a figure of hope for a more democratic music industry. But after her sudden spike in popularity, Hill fails to immediately receive a solo offer. (The one she does obtain a few years after the documentary immediately gets embroiled in its own Internet-derived controversies.) In the end, none of her own songs achieve the same prominence as her hit cover.

Despite her lack of independent success, Hill soon finds that her online fans criticize her if they see her doing backup work again. She goes so far as to wear a wig while singing backup, but after discovering her ruse, her fans shame her. As the film follows Hill walking around New York or practicing a refrain, it is unable to either account for her brief spurt of fame or her frustrating fall.

In the end, rather than embodying an alternative to the undemocratic status quo, Hill’s story exemplifies the unequal dynamics of an older musical economy — and shows how contemporary online culture has intensified them.

Contrary to what many seemingly scientific self-help books want us to believe, we can do very little to ensure that our artistic contributions will attract a large following. Already-established celebrities and organizations overwhelmingly make these decisions, not ordinary content creators. Indeed, virality shows that equal distributions of attention are an ideal that is very easily abandoned in our contemporary public sphere, extremely open as it might appear to be to any and all forms of self-expression.

Image by Loowgreen / Flickr.

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Annemarie Naylor

In the course of our work, we have called for common libraries as platforms for the production, exchange and consumption of knowledge and know-how – principally, in recognition of our increasingly read/write world, and in seeking to emphasise the scope for the capture and curation of the ‘long tail’ to grow the knowledge base to which we all have access.

However, we recently came across two films which we think others might find interesting:-

1. The Internet’s Own Boy – https://docs.google.com/file/d/0B-9D0aLWNasxaVFhZVBHTVRpcGM/edit?pli=1
2. The Radical Tactics of the Offline Library – http://vimeo.com/95351775 /

The former concerns Aaron Swartz and, whilst tragic, highlights what a person with a passion for making the world a more transparent place can do if s/he is able to harness support via digital channels and translate that into social action. The Radical Tactics film is also available in long hand and offers a comprehensive ‘history of the library as the locus for copying rather than storing knowledge and know-how’.

The latter helpfully underlines that the UN Declaration of Human Rights states: “Everyone has the right to freely participate in the cultural life of the community, to enjoy and to share in scientific advancements and its benefits.” Unfortunately, it also says: “Everyone has the right to protection of the moral and material interests resulting from any scientific, literary or artistic of which one is the author.”

There is, then, an ongoing battle for the commons as ‘intellectual property’ in the form of the Open Knowledge project, and despite considerable evidence to support the view that traditional patents and copyright provisions stifle innovation; notably, the BRIC and other developing countries have woken up to the potential to get ahead by embracing peer-to-peer licensing (rather than patents/copyright), so there will be considerable scope to make a strong economic case for open knowledge going forward.

To put this into some kind of local perspective: the UK faces unprecedented reductions in public library service budgets over the next 3-5 years. The Government, for its part, is preparing to recommend a number of actions to address growing concern in the run up to the General Election. In the interim, we are more and more reliant upon Amazon and Google.

The former now boasts 41% of the book-selling market in the UK today, just introduced terms in relation to publishers that will enable it to print books (that go out of stock) on demand from its warehouses, and all of this at a time when there are just 1,500 independent book shops left – no book shops at all in many places. Meanwhile, the latter has sought to perpetuate the traditional commodification of knowledge and know-how, albeit through channel shift, at the same time as reducing the search for knowledge and know-how to a corporately driven ‘question and answer’ machine. This, contrasts sharply with #humansearch services like Ask NYPL.

In effect, then, we are witnessing the wholesale privatisation of knowledge production, exchange and consumption.

This is why we’re doing our utmost to establish an open course and community-led alternative: http://www.commonlibraries.cc It also explains our interest in approaches to sharing knowledge.

We are keen to identify organisations like the Waiting Room and Islington Mill Studios who are self-organising access to knowledge/learning in a host of different ways. So, if you have any examples / suggestions about whom we should look to for further inspiration or, else, approach as potential partners – please do let us know.

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