New Book on Networked Collaboration

Knowledge Collection Learning
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STATUS UPDATE:
First draft of the insights section is completed:
263421647-Can-networked-communities-steward-public-assets-at-scale.pdf (37.1 MB)

Next step: interactive influencer directory space, currently under development

[This wiki is a working draft of the call for contributions the book. It requires further editing and some CSS/HTML formatting to make it look professional! - please leave your feedback in the comments]

Edgeryders to write handbook on grassroots collaboration in the age of networks

We’re crowdsourcing a book, and we’re calling on emergent influencers to lead a chapter that addresses “networked collaboration”!

As many social projects and responsibilities decentralize and general populations begin to assume greater ownership of their futures, we strive to mentor, empower, learn from, and partner with thought leaders who are developing new solutions for communities that are losing access to legacy resources previously made available by governments, corporations and large NGOs.

“Networked collaboration on the Edge: The Alternative to Problem-Solving Leadership in Times of Crisis” is a digital handbook and collection of case studies and thought pieces that brings together cutting-edge solution-oriented leadership in areas of open source software, eco-friendly communites, non-transactional economies, urban agriculture/sustainabilitiy, collective intelligence experiments and more.

Examples of Networked Collaboration where grassroots solutions will address environmental, political, economic problems

Project \#1 Project \#2 Project \#3
please add photo here please add photo here please add photo here
Add one paragraph description of project (case study) here Add one paragraph description of project (case study) here Add one paragraph description of project (case study) here

We are hacktivists, artists, writers, social innovators, designers, engineers, entrepreneurs, policymakers, researchers and many more that don’t easily fit into categories -- and we're prepared to boost the visiblity of your work through the Edgeryders Influencer Platform

LOTE4: The Stewardship from Edgeryders on Vimeo.

We support your work with crowdsourced research

Host a panel at “Living on the Edge” 5 (#LOTE5)

Your book chapter becomes a social platform through our network

There is great overlap between your work and what our members spend time thinking about. We are non-spectators looking to make things happen now.

Whether we can be of use as focus group participants or research assistants, our 2000+ network of citizen experts are passionate about social innovation and are ready to contribute high-level support to promising causes.

This event in City, Country aims to set the foundations for a global networked collaboration ecosystem where solutions oriented conversations produce openness, collaboration and a “get it done” attitude.

Participants in previous LOTE events have included Amelia Andersdotter, previously member of the European Parliament on behalf of the Swedish Pirate Party, Fabrizio Barca, General Director at the Italian Ministry of Economy and Finance, Robin Chase founder of Zipcar and other notable change makers.

Edgeryders wants to maximize the free flow of information by publishing insights across media types and channels, so a book is a minisite is an interactive campaign is a wiki is a conference session.

All of it integrates with the purpose of bringing greater audience participation and buy-in to your work as it progresses in dialogue with our network and constituent audiences.

Want to author a contribution to the book and conference? Let's talk!

Think about a person or project that you feel is interesting and contributing towards improve something near you (in your country, city, town or village). It can be you, or someone you know. It can also be someone you have never met but would like to have an opportunity to get to know. Get in touch and Shine a light on their work!

We will respond with questions to help you develop it into an engaging case study for you and others to learn from and contribute to. Once you and the editors happy with the result, it goes into the book. But hurry, the final date for submissions is July 10.

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Analysis, art and hypotheses

Hey all,

I am not sure if I can contribute any ongoing case studies - but I would like to help in writing a part that deals with the analysis. Ideally I would do this in collaboration. I could imagine it would be fun doing some of it together with @brenoust . Perhaps we should have a (documented) call and throw a few hypotheses around?

However this would probably become more important later in the project, and I think it is important to get as much going as soon as possible so that the other teams are not sitting in front of a vacuum but there’s something for everyone to work on.

So for that I can offer translation, proof reading and artwork help if someone needs it.

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If you have a hammer, every problem looks like…

… a nail. In my background this is perhaps relatively close to being a hammer. However in my personal experience the systems were mostly not “well behaved” enough. Usually secondary effects (associated with (non statistically random) agglomeration) would become pretty dominant - at least for most of the interesting applications.

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Don’t be shy - put your comments

@Driss , @Mikhail_Volchak and the others - questions are totally okay as well! We can discuss things more and involve the right people directly if we document things properly here.

It looks like @pamela did register already. I hope you can find your password somewhere still - I know how it is ;).

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after the call

Things that were on my mind after the call, were how do we identify who is affected, and how do we identify the ‘needs’ of those directly affected. In other words, how can we be the matchmakers that we want to be, what is wanted? What I got so far from people I talked to here in Georgia is that procedural knowledge is highly needed ‘good’: how to do campaigns/engagement/write project proposals/media strategy/etc. But for the people who would be interested in contributing t the making of the book, that’s different of course. During the call some said it would perhaps be good to give those a skype call with some of the case study people, but I want to know if we can perhaps identify it rather similarly to makerfox: do a matchmaking as we want to do with the case study people themselves?

I also am really interested in the methodology of Pam’s organization. Is she on the platform and does anyone have her handle so I can ping her?

(left on saturday afternoon for family, only to be stuck in the rain and was busy yesterday all day with the flood that occurred here. Will be busy today with it as well, but will try to keep an eye on here)

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Did you manage to get in touch with Pam?

Could it be @pamela maybe?

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What do Effective Medium Approximations look like?

So @trythis, we have a first round of posts ranging from summaries of exchanges with project protagonists, to transcripts of interviews all the way to more or less publishing ready case studies like this one from Egypt.

Going back to your suggestions above about doing EMAs. How would you see us doing it on material like the ones above?

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It’ll take some time but I can start thinking loud

Part 1

The idea is to build a mental model of how different individuals interact with each other, so that when you “zoom out” and look at, say a scene/subculture/small community/society, you can describe it relatively reliably at this higher level.

I will keep things extremely simple, and pretty imprecise for the beginning. The original idea was developed for mixtures of materials, so I’ll use this as a comparison sometimes.

Imagine you have a bag of 10l of water and you add another 10l of apples into the water. The bag of only water felt not very rigid of course. The bag full of apples was relatively rigid. Both together are almost like the water before (unless you press really hard). So rigidity of one material somehow “got lost”. If you’d finely mix the apples into a sort of watery apple sauce - you get slightly different properties again. So basically things depend not only on the individual constituents but also on their arrangement (e.g. large pieces vs small pieces).

You can translate this into a social context by assuming you have only two types of persons in a ratio of 1:1. You can still build very different societies by homogenizing or polarizing. Or clumping the “apple people” together and surrounding them with “water people” or vice versa. You can also build a “layer cake society” or a “statistically random society” (although that is probably much harder than it sounds, because certain constituents usually attract or repel each other).

Now imagine you have you have 9 parts pretty much electrically insulating plastic, and 1 part highly electrically conducting metal.

If you throw them together you don’t necessarily get 9 x conductivity of plastic + 1 x conductivity of metal (and then divided by 10). If we assume the metal pieces are little round balls we would need more than 10 volume % (1 part in 10) to make the stuff conductive. And if we put in a little more metal (e.g. 11%) - almost no change in conductivity is visible. So we add a little more - and again nothing. And a little more - again almost nothing. And a little more - and we get a tiny change. And a little more - and the change is gigantic! Sometimes less than 0.1% addition changes the conductivity by a factor of more than 1000!

Translated to our society example it would mean: Even if you interview people in the streets and make a statistic of a certain opinion - there is almost no change visible at all, initially. But at some point many people have 2 friends within their group who share that specific opinion. Most of these friends also have some connections who share this opinion - and thus a network (a pretty much endless cluster) has appeared.

If people know whom of their friends share this opinion and it is something they are passionate about, then a lot of things can change pretty drastically in a short time for a society. How much it wil change, will often depend on how long the quality of the connection remains “high” - even when you have to connect through several friends of friends.

Societal dynamics can flip, even though there may only be a tiny increase of people with their opinion (or just a change in their awareness/paradigm/narrative) - and they remain a very small minority. If they are in touch through an unbroken connection and can coordinate (propagate signals), they have reached what can be called tipping point, or percolation threshold.

What is required for this is not even necessarily making any sort of addition - only some re-arrangement that allows individuals (or groups) with shared interest to find and coordinate over long distances. And if one has seen this work a few times it can become a powerful self fulfilling prophecy - hardly possible to turn the wheel back on this.

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Wait. Say that again?

There is a burning question in what you wrote above which I cannot articulate but which may be a central driver in the narrative if we can pin point it with exactitude.

If you interview people in the streets and make a statistic of a certain opinion - there is almost no change visible at all, initially. But at some point many people have 2 friends within their group who share that specific opinion. Most of these friends also have some connections who share this opinion - and thus a network (a pretty much endless cluster) has appeared.

If people know whom of their friends share this opinion and it is something they are passionate about, then a lot of things can change pretty drastically in a short time for a society. How much it will change, will often depend on how long the quality of the connection remains “high” - even when you have to connect through several friends of friends.

Societal dynamics can flip, even though there may only be a tiny increase of people with their opinion (or just a change in their awareness/paradigm/narrative) - and they remain a very small minority. If they are in touch through an unbroken connection and can coordinate (propagate signals), they have reached what can be called tipping point, or percolation threshold.

What is required for this is not even necessarily making any sort of addition - only some re-arrangement that allows individuals (or groups) with shared interest to find and coordinate over long distances. And if one has seen this work a few times [well known examples] it can become a powerful self fulfilling prophecy - hardly possible to turn the wheel back on this.

I was reading and some hidden association kept firing off. Finally localised it to this video.

So is the analysis about identifying hidden/less obvious shared interests between different people, projects, organisations, issues, struggles, resources and windows of opportunity? About making it easier for us to find one another and coordinate over long distances? You know like those sparks that light up paths between seemingly isolated people, projects and places in the snipped above?

Contrast with Ondi Timoner’s total disruption project in which we get to gawk at people very far removed, rather than connect with those together with whom we could be levelling up. Here and now. Wherever we are…

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Your questions and then some (Citie)

You asked:

"[1] So is the analysis about identifying hidden/less obvious shared interests between different people, projects, organisations, issues, struggles, resources and windows of opportunity?

[2] About making it easier for us to find one another and coordinate over long distances?

[3] You know like those sparks that light up paths between seemingly isolated people, projects and places in the snipped above?"

[1] Yes. That is an important part, and one reason why we need access to data.

[2] Not necessarily easier in general. Rather, more likely that the right (groups of) people find each other. Coordination over long distance - yes (but physical distance is the least problematic in this respect).

[3] I am not sure I have enough detail to decide on that. I checked the publishers site but it seems to be intended as eye-candy. There seem to be some inconsistencies with regard to the USA as well.

Regarding Ondi: Interestingly I did not have her on the radar before, and I was initially tempted to bash her video thoroughly as an example of misguiding entrepreneurial cheer-leading. However given the documentaries she has done I wonder if this is some sort of insider joke one would get if one had watched them attentively. On the surface it looks like an ad for a slightly modernized version of a best-of album.

What is of critical importance though is that she comes from the human -small scale- end of things, while most of the deciders are high level economics/finance/policy wonks. Of course both aspects are necessary. But I think the main features of a good policy are: a) It does not get in the way. b) It represents the interests of the citizens (not just 0.1%), and the indirectly affected persons (including future generations). I could go on talking about Ondi - an perhaps I should at some point, but I’ll leave it at this for now.

I’ve just run into the release of this report: http://citie.org/wp-content/uploads/2015/06/CITIE_Report_20151.pdf

You may want to go to page 55 directly and see who is behind it (I assume Accenture did the heavy lifting on the financial side). #1: http://www.transatlanticbusiness.org/tabd/ (also: http://www.citizen.org/trade/harmonization/TABD/index.cfm). But I’d say the others look like a decent bunch overall. Especially Nesta seems to have some good people. So overall it probably serves as a decent average OMG-WTF-we-need-to-innovate-document.

If you go to page 53 and read the summary a little, I am tempted to say I rest my case. This is the absolute top-down approach. Of course some of it just specifies things I cover in a) & b) above. However they add other details based on assuming they already know the right answer, which tends to look an awful lot like silicon valley + correlation/causation mix-ups.

In a nutshell their “ecosystem thingy” is trying to farm by weather modification based on plants in a far away land with different weather pattern and ecosystem dynamics. And if it kills all the bees of an apple orchard in the process, who cares - the (high yield) corn is what we’re after! And if the KPI-yield is still too low by Q2 - we can always rent more office space, add fertilizer, and fudge the data.

What you should be doing is watching the locals do their version of three sisters from seed, and taking a lot of notes, up close. Uncomfortably close. You’ll probably learn most from the things that don’t work, let’s call them KFIs. And you will not be done in less than a season - that much is for sure. If you don’t make many the identified mistakes there’s a good chance you’ll increase your yield. Then you can effectively hypothesize about cause and effect, and test if pulling on blades of grass will make them grow faster or taste sweeter. Or if you should introduce a new species or breed with an existing stock.

Of course you can go crazy do Big Data driven agile 5 year sprints/big leaps - and there’s high chances that some good will come out of them, but I doubt it will be worth inflicting this on (any of) the 40 seemingly most import cities. A great forest needs a couple of years to grow, burning it down on the other hand, is a lot faster.

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Context

Interjection 1

It is a pretty wide field, and I believe my perspective on things is not familiar to many. My mental model uses: energy, trust, knowledge, and material resources as basic building blocks. I am not sure from which angle I should best approach this. Perhaps it comes down to risk aversion and risk/reward ratios.

Silicon valley is seems to be the gold standard for “entrepreneurial ecosystems”, and to a lesser degree “anglo saxon (tech) business culture”. Thus very often policies are modeled on their approach to fill in the blanks (of which there are many). If you are not extremely careful I think this is a recipe for disaster. Especially for development of average or below average communities.

  1. Business models that work in an empire often don’t work anywhere else (lingua franca, brain drain, access to resources)

  2. If you are using 25% of the worlds resources for 5% of the population you’re not facing existential risks - thus risk aversion is not necessary. There is always money to fix it, as long as you are in pole position. The bigger risk is losing pole position, thus innovation is a must. Silicon valley/DC is pushing this dynamic to the extreme - it is not a model for the RoW (rest of world).

It would appear that efficiency is very important for the RoW, and one should look for models in the respective places (ideally not on a national basis, and not using GDP).

Innovation, although it is inherently wasteful, is necessary to maintain or improve relative efficiency over time. For small players the (on average) winning strategy should emphasize reduction (not minimization) of cost/risk. Exaptation, adaptation, collaboration, coordination and intricate community relationships are hallmarks of resource constrained systems. Whereas in the USA the phrase is: “As long as you keep trying, there is not shame in failing”. In most other parts of the world there are no second chances for non-elite actors: “Die trying, or lose face” (or both*) is closer to reality.

This means that developments in silicon valley do indeed have to be watched closely, and reacted to in order to pick up and modify the right pieces for local implementation.

Although far simpler (and cheaper) in itself, even crude technology transfer is usually significantly more challenging to do in practice, as one generally lacks the social requirements to do it effectively in the destination location. This is due to competition for resources (particularly highly capable individuals), and more complicated and complex stakeholder interests.

Generally this meant: scarce individuals with entrepreneurial disposition, required ability, and availability, have to coincide with windows of opportunity (technical+economical/alignment of powerful internal and external interests), and physical location. Each factor in itself reducing the likelihood of success significantly. Often up to a point where many rational entrepreneurial actors decide to “go to silicon valley” where the likelihood of success (not normalized for competition) is orders of magnitude higher because environment is more conducive to change and experimentation. Thus making it a self fulfilling prophecy. Not surprisingly the most successful entrepreneurs of silicon valley are not home made, but drained from somewhere else.

Recent high rates of unemployment have allowed the pool of entrepreneurs to grow a little in Europe and other places so that this one critical factor is ameliorated. However it is debatable if this is a desirable or sustainable situation.

I hope I’ll get to write Part 2 soon, where I’ll try to be more concrete and also answer your questions.

*With the natural tendency to form a powerful elite in a relatively slowly changing system comes an aversion to disruption.

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Lego people

Part 2a

To recap from the previous part: we can get different properties of the general system by only rearranging the constituents. No new ingredient, and no large scale re-education programs strictly necessary.

The next step is looking at who is the principle actor in this. Most economic theory assumes these are our “well informed and rational individuals”. Let me try to change the view on things a little. I’ll just arbitrarily say that it is not you who decides most of you actions but it is your network (e.g. family and close friends, political party, or the laws and mores of your society - perhaps depending on the matter in question) who decides, and only to a small degree you yourself have an active role. So this way of looking at the network would replace individuals with bigger clusters (perhaps about 100 (Dunbar’s number). Does this really change things though? Perhaps not as much as one would think. Let’s try the opposite and divide the individual. Not possible? Ha: Are you the same person you were 20 years ago (with respect to your decisions and actions?), the same you will be in 20 years (e.g. with kids or grand-kids)? What would Freud say about that? And even if we leave him out of that - could sunny days, rainy days, habits, workplace, recent experiences, accidents, drugs, or sleep deprivation, (perhaps imagined) pressure from ideals (not to mention ancestors, peers, dependents, or people in positions of authority) not change your reaction? It looks like we’ll get to a very similar situation, only through a different lens that looks at the smaller scale*. So this could be called self-similar. However the structures we’re looking at don’t need to be the same, even when a snapshot of it looks the same - they can have different underlying dynamics.

For example most of the time the influences that inform your “personal” decision are relatively “close” to you. E.g. your family, close friends, and the communities in which you feel (or want to feel) most at home (this increasingly includes online communities - so “close” refers more to an emotional closeness/importance than a location based closeness). But this is not the whole picture. You may also be influenced by certain ideals - in spite of what your current immediate environment thinks (again modern communication technology amplifies this effect). I would argue, if you are some sort of “change maker” it is significantly more likely that you stand out, in some (often invisible) respect, compared to your environment. Maslow’s hierarchy may not apply reliably in such cases.

Now it usually becomes quite important to consider the scale of the clusters we are looking at in our network structure - because they can organize and communicate (internally and externally) by different means. Here are just a few cognitive biases that are mostly rooted in the individual level - and this is just the brain talking to itself!

If we bring in other people - are they all exactly like us? No, for example there may be different types personalities such as MBTI (just one example), who like to approach problems in different ways, or identify them differently. So we have different lego-pieces we can build our solution with? Yes and no.

If we run into bigger problems we tend to make bigger groups (sometimes intentionally using different personality types) to address them, or alternatively take more time and do it alone. Both options have their own issues.

If we make groups, we inevitably get group dynamics, so we usually have the problem that not always the people with the best ideas get heard and promoted (and we have problems to decide what the best idea is in the first place). Certain people end up in certain positions with a high probability, and perhaps more importantly certain members are extremely unlikely to fill certain roles. This likely evolved over time to effectively address problems that were common throughout our long prehistoric existence, and is thus deeply rooted in us. I assume for the problems that (they couldn’t solve and) face us today, they are probably more a liability than an asset - because this behavior keeps derailing us from a path that could lead to a solution. I believe many organizations are doomed to fail, based exclusively on the narrative dominant in their human resources department and their promotion schemes, but that is perhaps a different story.

However generally it is not hard to see, if a group selects a subgroup out of a subgroup, out of a subgroup - each time filtering out specific types of personalities while enriching others, this has consequences. You typically end up with final subgroup that has a very limited perception (because they all see the same things, in the same way, and overlook a large fraction most others would perceive), and often very limited means of communication (because they all prefer a certain mode, and their vocabularies are not complementary) and narratives to guide them in solution design. Does that sound familiar? National governments, organizations’ interest groups, top level experts? Add some cognitive bias, and it is not hard to see why “they” ruin the world so much. The only problem is - most of us are the same. Unless you are in the club of people that hate clubs. So how do we fix that? [Hint]

[@Nadia @alberto if there are articles on edgeryders I could link to on edgeryders that corroborate some of my blathering I could edit the post to link to them. If my stuff is inconsistent with other articles - even better - we could discuss!]

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notes to self

(early) childhood, siblings, gender, sports design, club competition [saturated high end competition/reviews], test design, school, class size, complementary project collaboration, limits of authority support, hidden out-group diversity, long Ts and languages, SNA (+ crime) through the economic lens, Percolation critical exponents - Wikipedia

language “hi pots”/low pots, work in/work out - transaction cost, high end market [reviews sci pubs, norms & stds] picked clean

http://www.people.vcu.edu/~mamcdani/Publications/O'Boyle%20et%20al%20(2012%20JAP%20-%20Dark%20Triad).pdf where to put them (short: https://youtu.be/hilQbVv4nXE?t=107)?

Perc prob language: List of Wikipedias by speakers per article - Meta

cream skimming and mobility of teams

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Change in the shadow of large pyramids

Part 2b

When we see the encouragement to “think outside of the box” - this should be seen as an euphemistic phrase for acknowledgement of systematic failure (or at least under-performance). Asking someone within the organization, who has spent considerable time working on progress(ing) inside the box, to turn around and walk away from it is likely to fail not only due to the cognitive biases that haunt our thinking. Another problem is that large organizations that refrain from admitting to failure or mistakes are seldom trusted to engage with criticizers in a fair way, especially if they have a record of not sticking to their rhetoric. Thirdly, if they were really serious about getting out of the box, why handle this internally - why not go and talk to individuals and small organizations who live (not just think) outside the box? That being said, such an appeal can improve matters if words are backed up by action.

Unfortunately, in practice many such measures to jump start innovation lead to stopgap measures or sacrificing long term gains for cash on hand - without addressing the underlying deficiencies that forced the organization from an orthodox path into untested waters.

I would contend that long term successful innovation is foremost a cultural matter (especially defined by what personalities and behaviors are perceived as appropriate or acceptable in which roles) constrained by available resources. This would mean that the majority of (cultural/behavioral) effects can be expected to impact some 25-50 years after their respective causes are established. A second similarly important time would be when the customs and values indoctrinated into the first generation have been internalized during the socialization of the next generation and impact society. This would be expected to be due 50-75 years after initial changes were made. In consequence one can probably assume an impact distribution that peaks around 50 years after policy adjustments.

If behavioral changes are pushed for on a shorter timescale the cost would probably rise considerably as this would have to be done against the resistance of powerful elements of society that benefit from the status quo. Especially if the typical career duration of approx. 30-40 years is approached. In the aftermath of a disaster the resistance to change may be reduced significantly for some time - but it is rare that the mood is in favor of fundamental change and experimentation, over a stable and projectable future.

There are however many things that can be done on an organizational level (which strictly speaking also has cultural implications) that are met with significantly less resistance. In order of increasing potential resistance to change the are: affecting the routing and format of information, reorganization of sub-groups, internal (temporary or partial) change of roles, and change of relationships with other organizations.

In principle this is a very effective leverage point for relatively large change on relatively short timescales. However because this is so, a thriving industry of profit oriented change management organizations has established itself in the lucrative areas of this field. They generally have the competitive advantage of having similar narratives to those of profit maximizing organizations, using the same tools, and interfacing in familiar manner with the upper management. The unfortunate result is that the advice generally is limited to a small subset of solutions (usually short term catabolism) - often without any viable long term options between them, and the crowding out of unorthodox advice.

As a result I would rather focus energies on the organizations that do not have the means to pay for this service - even though they are providing a valuable but precarious service to society. Particularly deserving of attention would be the subset of organizations than can “repay in kind” without adversely affecting the normal operations (often the case in largely digital economies).

The national and international policy level is similar although (especially in the under-performing organizations) it not unlikely to suffer from one or two more layers of self-selection induced blindness and rigidity. On the other hand the field is significantly more diverse in many aspects, so that a lack of standards may allow for more unorthodoxy.