Tag Archives: Clay Shirky

The road to the unMonastery: three low-cost moves towards becoming a smart community

The Ise-jingū Shinto temple, in Japan, has functioned without interruptions for thirteen centuries. Yet, when the temple’s monks applied for World Heritage status to UNESCO, the United Nations’ cultural agency, UNESCO refused to grant it. Reason: Ise-jingū is made of timber, a non-durable material. Every twenty years or so, monks dismantle and rebuild it, using timber from the same forest as the original temple. From their point of view, the temple is, in fact, 1,300 years old – built with renewable materials. UNESCO’s guidelines, however, had a different perspective: what makes a World Heritage site is the durability of artifacts, not of processes.

Clay Shirky related this story in 2008, and used it to illustrate a powerful insight. Let me quote him in full:

Wikipedia is a Shinto shrine; it exists not as an edifice but as an act of love. Like the Ise Shrine, Wikipedia exists because enough people love it and, more important, love one another in its context. This does not mean that people constructing it always agree, but loving someone doesn’t preclude arguing with them.

Shirky is right. Wikipedia, as all online communities, is a social process. If their participants lose their motivation to stay involved, these communities disintegrate almost instantly.

I have been mulling over this argument in the context of the smart cities debate. Here’s what I figured out: it applies not only to online communities, but also to offline ones like cities. A city is not its streets, its buildings, its physical infrastructure. A city is all this, plus the local knowledge needed to maintain, adapt, evolve, improve its infrastructure. Of these two elements, local knowledge is the most fundamental. If it is preserved, a city destroyed by an earthquake or a great fire can be rebuilt, and preserve its identity; but if local knowledge were to disappear, time and lack of care will bring down the buildings, disrupt logistics and communication, disperse the population. A city – any city – is mostly software. This software’s modules live in the brain of its citizens, so ultimately we – its inhabitants – are the city. UNESCO reached a similar conclusion, and ended up accepting to list Ise-jingū as a World Heritage site.

Inspired by these considerations, for the last few months I have been attempting to collaborate with a city, Matera, that I have a special relationship to and is running to be European City of Culture in 2019. An application for ECOC involves a formal procedure: I imagine it would be possible to enact it as a bureaucratic process, ticking boxes as you go along. Matera, however, has a more interesting approach: using the application as an excuse to think about the city’s medium- and long-term strategy, regardless of whether it gets to be ECOC. In the terms of my metaphor, the application is a way to upgrade Matera’s software.

The city enlisted a pool of respected professional experts, but no expert, however brilliant, can ever outperform the combined effort of 600,000 citizens in the region (and of the many people that, like me, are not originally from there but care about Matera and its territory). The more the citizen’s wealth of information, skill and passion is mobilized, the more creative, smart, sustainable the future steps of the city will be. Among many initiatives to profile its bid, the city is taking three steps in this direction. They are small, low-cost initiatives, but I think they might make a difference.

The first one is an open online community tasked with enriching the work to prepare the application itself. In its early stages, it is now scouting the terrain; it encourages the local people who have interesting experiences or insights that could help craft the application to share them (example, Italian). The idea is to turn a spotlight onto the many interesting, creative things that always and everywhere, people are doing without their democratic institutions knowing about them. In a second phase, the professional experts will produce proposals (for example, about the application’s concept) and discuss them with citizens online, trying to improve them. The community website’s social contract (Italian) is one of constructive collaboration: we have a job to do, and we all commit to a discussion of the highest level we can achieve. For rants, narcissism or cheap cynicism go play with Facebook. The website has not been publicly presented, but it is already up and being used – which is nice in itself, it’s best to do things first, cut ribbons later, if there is time.

The second move is an open data policy. The release of public sector data in open format is a hot topic across Italy, and can count on a small but committed civil sector of the civil society that promotes it with a passion. Releasing high-quality data means investing in the citizenry’s collective intelligence, that needs sound information to produce equally sound contributions to public decisions. In January, a small group of civic hackers gave Matera a gift: they spent a day doing reconnaissance on the state of the city’s data infrastructure. It led to drafting a roadmap towards the release of a first batch of datasets already in 2013. Along this path, city and civil society walk together.

The third move is the most radical: deploy in Matera the first unMonastery. Driven by a mostly Northern European founding group and led by 27-year-old Londoner Ben Vickers, unMonastery draws inspiration from 10th century’s monastic life to encourage radical forms of collaboration and innovation: a sort of lay, off-grid mendicant order striving for a society that can better withstand present and future systemic crises. The social phenomena behind this project are the rise of hacker culture and the deepening of the crisis in Europe. Taken together, these two trends mean more and more young, educated, connected and generous young people. Of these, many aspire to a deep societal fix, and do not think they can bring it about by joining the public service, nor by working for the private sector. They don’t buy into the “gonna change the world” Silicon Valley rhetoric; for them, innovating means tackling the fundamental problems of expanding individual freedom, establishing a fair social deal, crafting an environmentally sustainable society – not inventing gadgets. Their walks of life seem unsettling, even dangerous to most of us (Ben paid his education by obtaining and selling magic items in an online game, then working for one of the first data mining companies); they are technologically savvy, idealistic and almost always poor. UnMonastery offers them a deal similar of that of the monasteries of old: lodging, board and time to think and realize their ideas, relatively free from the need to make money. Matera adds to the mix something unMonasterians find irresistible: an interface to a local community that wants to evolve and has some meaty problems to deal with.

The gamble behind this collaborations is that, living side by side, hackers and Materans discover and explore new paths to make the city more beautiful, livable, sustainable and low cost. Can we invent (partly) decentralized solutions to urban hygiene and urban waste collection problems? What can we learn from the ancient tecnhology of rainwater captation and reuse, in use in Matera as late as the 1800s? How do we solve the problem, of moving people and stuff in the Sassi, where there are far more stairways than roads, without choking the city in private cars?

Corporates, so far have not solved these problems (in some cases they actually contributed to create them – exhibit A being the automotive industry). They can’t afford to: companies have a duty to make a profit, and this means innovating only in ways that lead to generating revenue in short and predictable times. Citizens and their unMonasterian guests are not constrained in the same way. They can afford to explore any solution, even wildly visionary ones, and simply discard them if turns out they don’t work. Net result: many more attempts, many more failures, but by the law of large numbers, more successes as well. Should somebody stumble upon a solution that can morph into a new company, well, why not? Sviluppo Basilicata‘s business incubator is literally across the courtyard from the future unMonastery – they’ll be happy to help.

It’s too soon to draw any conclusion, but Matera seems to have the attitude of a smart city , in my favorite sense of the term: it tries to decentralize knowledge and decisions, creates space for new projects and promotes everyone’s creativity. This was clear in the unMonastery launch event, a beautiful meeting between the city and the foreign hackers (Ben wrote about “Matera’s gift to the unMonastery”). Even the criticism to the project points to a healthy, constructive relationships.

The road is long, and all of these moves could very well fail: but we are off to a good start. A prosperous voyage to Matera and “her” unMonasterians!

If you would like to become an unMonasterian, read this.

Disrupting learning III: enter Clay Shirky

How online conversations scale, and why this matters for public policies

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I care about public policies, and try to contribute to their betterment. The road I am exploring is to take advantage of the social Internet to connect citizens among themselves and with government institutions to assess governance problems, design solutions and implement them – all in a decentralized fashion. I wrote a book to show it has been done, and to argue for it to be done more.

But it remains a tough sell. Many decision makers remain skeptical: why should online conversations converge onto evidence-based consensus? A few people who share a common work method can make an effective group, but a large number of very diverse and self-selected citizens – what I have been arguing for – is likely to collapse under the weight of trolling, controversy and sheer information overload. We have examples in which this did not happen: but we don’t have a theory to guide us in designing conversation environment which produce the desired results. Not good enough.

Some work I have been doing recently might provide a lead. As the director of Edgeryders, I marveled at the uncanny ability of that community to process complex problems – as I had done many times before in my years as a participant to online conversations. But this time I had access to the database, and – together with my colleagues at the Council of Europe and the Dragon Trainer project – I used it to reconstruct a full model of the Edgeryders conversation as a network. The network works like this:

users are modeled as nodes in the network
comments are modeled as edges in the network
an edge from Alice to Bob is created every time Alice comments a post or a comment by Bob
edges are weighted: if Alice writes 3 comments to Bob’s content an edge of weight 3 is created connecting Alice to Bob

I looked at the growth over time of the Edgeryders network as defined above, by taking nine snapshots at 30 days intervals, working backwards from July 17th 2012. For each snapshot I looked at four parameters:

number of connected components (“islands” in the network)
Louvain modularity of the network. This parameter identifies the network’s subcommunities and computes the difference between its subcommunities structure and what you would expect in a random network. Modularity can take any value between 0 and 1: higher values indicate a topology that is unlikely to emerge by chance, so they are the signature that some force is giving the network its actual shape; low values mean that the breakdown into subcommunities is weak, and could well have emerged by chance.
for modularity values indicating significance (above 0.4), the number of subcommunities in which the network is broken down by the Louvain algorithm

These indicators for Edgeryders agree that there is no partitioning in the network. All active members are connected in one giant component, whose modularity values stay consistently low (around 0.3-0.2) throughout the period analyzed. This is not surprising: my team at Edgeryders had clear instructions to engage all newcomers into the conversation, commenting their work (and therefore connecting them to the giant component). From a network perspective, the job of the team was exactly to connect every user to the rest of the community, and this means compressing modularity.

Next, I looked at the induced conversation, the network of comments that were not by nor directed towards members of the Edgeryders team. It includes conversations that the Council of Europe got “for free”, without involving paid staff – and in a sense the most diverse, and therefore the most interesting. To do this, I dropped from the network the nodes representing myself and the other team members and recomputed the four parameters above. Results:

there is a significant number of “active singletons”, active nodes that are only talking to the team members, but not to each other. This might indicate a user life cycle effect: when a new user becomes active, she is first engaged by a member of the paid team, who tries to facilitate her connection to the rest of the community (by making introductions etc. My team has specific instructions to do this). The percentage of active singletons decreases over time, from about 10% to less than 5%.
not counting active singletons, there are several components in the induced conversation network. A giant component emerges in February; from that moment on, the number of components is roughly constant.
the modularity of the induced conversation network (excluding singletons) is high throughout the observation period (over 0.5),
the modularity of the giant component is also high throughout the period (over 0.5). Interestingly, modularity grows in the November-April period, indicating self-organization of the giant component. In February it crosses the 0.4 significance threshold
the number of subcommunities in which the Louvain algorithm partitions the giant component also grows over time, from 3 in April to 11 in July

Subcommunities are color coded. Knowing Edgeryders and being part of its community (and having access to non-anonymized data), I can easily see that some of those subcommunities correspond to subjects of conversation. For example, the yellow group in the upper part of the graph is involved in a web of conversation about the Occupy movement and how to build and share a pool of common resources. Also, looking at the growth of the graph over time, subcommunities seem to grow sequentially more than simultaneaneously. This might be related to the management structure of Edgeryders: we launched campaigns (roughly one every four weeks) to explore broad issues that have to do with the transition of youth to adulthood. Examples of issues are employment/income generation and learning. So, an interpretation could be this: each campaign summoned users interested in the campaign’s issue. These users connected to each other in clusters of conversation, and some of them act as “bridges” across the different cluster, giving rise to a connected, yet highly modular structure. The video above has some nice visualizations of the network’s growth and of the most relevant metrics.

This looks very much like parallel computing (except this computer is made of humans), and could be the engine of scalability. As more people join, online conversation does not necessarily become unmanageable: it could self-organize into clusters of conversation, increasing its ability to process a certain issue from many angles at the same time. Also, this interpretation is consistent with the idea that such an outcome can be helped by appropriate community management techniques.

Ten years ago, Clay Shirky warned us that communities don’t scale. He was right, by his own definition of community – which is what in network terms is called a clique, a structure in which everybody is connected to everybody else. I would argue, however, his definition is not the most appropriate to online communities. Communities do scale, by self-organizing into structures of tight clusters only weakly connected to each other.

If we could generalize what happens in Egderyders, the implications for online policies would be significant. It would mean we can attack almost any problem by throwing an online community at it; and that we can effectively tune how smart our governance is by recruiting more citizens. appropriately connected, into it. We at the Dragon Trainer project are following this line of investigation and developing tools for data-powered online community management. If you care about this issue too, you are welcome to join us onto the Dragon Trainer Google Group; if you want to play with Edgeryders data, you can find them on our Github repository.

Coming soon: posts about conversation diversity and community sustainability based on the same data.