Bradi Heaberlin and Simon DeDeo at Future Internet: “Social norms have traditionally been difficult to quantify. In any particular society, their sheer number and complex interdependencies often limit a system-level analysis. One exception is that of the network of norms that sustain the online Wikipedia community. We study the fifteen-year evolution of this network using the interconnected set of pages that establish, describe, and interpret the community’s norms. Despite Wikipedia’s reputation for ad hocgovernance, we find that its normative evolution is highly conservative. The earliest users create norms that both dominate the network and persist over time. These core norms govern both content and interpersonal interactions using abstract principles such as neutrality, verifiability, and assume good faith. As the network grows, norm neighborhoods decouple topologically from each other, while increasing in semantic coherence. Taken together, these results suggest that the evolution of Wikipedia’s norm network is akin to bureaucratic systems that predate the information age….(More)”
Juries as Problem Solving Institutions
Over the last two years, a group of scholars from disciplines including political science, political theory, cognitive psychology, information science, statistics and computer science have met under the auspices of the MacArthur Foundation Research Network on Opening Governance. The goal of these meetings has been to bring the insights of different disciplines to bear on fundamental problems of collective problem solving. How do we best solve collective problems? How should we study and think about collective intelligence? How can we apply insights to real world problems? A wide body of work leads us to believe that complex problems are most likely to be solved when people with different viewpoints and sets of skills come together. This means that we can expect that the science of collective problem solving too will be improved when people from diverse disciplinary perspectives work together to generate new insights on shared problems.
Political theorists are beginning to think in different ways about institutions such as juries. Here, the crucial insights will involve how these institutions can address the traditional concerns of political theory, such as justice and recognition, while also solving the complex problem of figuring out how best to resolve disputes, and establishing the guilt or innocence of parties in criminal cases.
Melissa Schwartzberg is an associate professor of political science at New York University, working on the political theory of democratic decision making. I asked her a series of questions about the jury as a problem-solving institution.
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Henry: Are there any general ways for figuring out the kinds of issues that juries (based on random selection of citizens and some voting rule) are good at deciding on, and the issues that they might have problems with?
Melissa: This is a difficult question, in part because we don’t have unmediated access to the “true state of the world”: our evidence about jury competence essentially derives from the correlation of jury verdicts with what the judge would have rendered, but obviously that doesn’t mean that the judge was correct. One way around the question is to ask instead what, historically, have been the reasons why we would wish to assign judgment to laypersons: what the “jury of one’s peers” signifies. Placing a body of ordinary citizens between the state and the accused serves an important protective device, so the use of the jury is quite clearly not all about judgment. But there is a long history of thinking that juries have special access to local knowledge – the established norms, practices, and expectations of a community, but in early periods knowledge of the parties and the alleged crime – that helps to shed light on why we still think “vicinage” is important…..(More)”
The era of development mutants
Guilo Quaggiotto at Nesta: “If you were looking for the cutting edge of the development sector, where would you go these days? You would probably look at startups like Premise who have predicted food trends 25 days faster than national statistics in Brazil, or GiveDirectly who are pushing the boundaries on evidence – from RCTs to new ways of mapping poverty – to fast track the adoption of cash transfers.
Or perhaps you might draw your attention to PetaJakarta who are experimenting with new responses to crises by harnessing human sensor networks. You might be tempted to consider Airbnb’s Disaster Response programme as an indicator of an emerging alternative infrastructure for disaster response (and perhaps raising questions about the political economy of this all).
And could Bitnation’s Refugee Emergency programme in response to the European refugee crisis be the possible precursor of future solutions for transnational issues – among the development sector’s hardest challenges? Are the business models of One Acre Fund, which provides services for smallholder farmers, or Floodtags, which analyses citizen data during floods for water and disaster managers, an indicator of future pathways to scale – that elusive development unicorn?
If you want to look at the future of procuring solutions for the development sector, should you be looking at initiatives like Citymart, which works with municipalities across the world to rethink traditional procurement and unleash the expertise and innovation capabilities of their citizens? By the same token, projects like Pathogen Box, Poverty Stoplight or Patient Innovation point to a brave new world where lead-user innovation and harnessing ‘sticky’ local knowledge becomes the norm, rather than the exception. You would also be forgiven for thinking that social movements across the world are the place to look for signs of future mechanisms for harnessing collective intelligence – Kawal Pamilu’s “citizen experts” self-organising around the Indonesian elections in 2014 is a textbook case study in this department.
The list could go on and on: welcome to the era of development mutants. While established players in the development sector are engrossed in soul-searching and their fitness for purpose is being scrutinised from all quarters, a whole new set of players is emerging, unfettered by legacy and borrowing from a variety of different disciplines. They point to a potentially different future – indeed, many potentially different futures – for the sector…..
But what if we wanted to invert this paradigm? How could we move from denial to fruitful collaboration with the ‘edgeryders’ of the development sector and accelerate its transformation?
Adopting new programming principles
Based on our experience working with development organisations, we believe that partnering with the mutants involves two types of shifts for traditional players: at the programmatic and the operational level. At the programmatic level, our work on the ground led us to articulate the following emerging principles:
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Mapping what people have, not what they need: even though approaches like jugaad and positive deviance have been around for a long time, unfortunately the default starting point for many development projects is still mapping needs, not assets. Inverting this paradigm allows for potentially disruptive project design and partnerships to emerge. (Signs of the future: Patient Innovation, Edgeryders, Community Mirror, Premise)
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Getting ready for multiple futures: When distributed across an organisation and not limited to a centralised function, the discipline of scanning the horizon for emergent solutions that contradict the dominant paradigm can help move beyond the denial phase and develop new interfaces to collaborate with the mutants. Here the link between analysis (to understand not only what is probable, but also what is possible) and action is critical – otherwise this remains purely an academic exercise. (Signs of the future: OpenCare, Improstuctures, Seeds of Good Anthropocene, Museum of the Future)
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Running multiple parallel experiments: According to Dave Snowden, in order to intervene in a complex system “you need multiple parallel experiments and they should be based on different and competing theories/hypotheses”. Unfortunately, many development projects are still based on linear narratives and assumptions such as “if only we run an awareness raising campaign citizens will change their behaviour”. Turning linear narratives into hypotheses to be tested (without becoming religious on a specific approach) opens up the possibility to explore the solution landscape and collaborate with non-obvious partners that bring new approaches to the table. (Signs of the future: Chukua Hakua, GiveDirectly, Finnish PM’s Office of Experiments, Ideas42, Cognitive Edge)
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Embracing obliquity: A deep, granular understanding of local assets and dynamics along with system mapping (see point 5 below) and pairing behavioural experts with development practitioners can help identify entry points for exploring new types of intervention based on obliquity principles. Mutants are often faster in adopting this approach and partnering with them is a way to bypass organisational inertia and explore nonlinear interventions. (Signs of the future: Sardex, social prescriptions, forensic architecture)
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From projects to systems: development organisations genuinely interested in developing new partnerships need to make the shift from the project logic to system investments. This involves, among other things, shifting the focus from providing solutions to helping every actor in the system to develop a higher level of consciousness about the issues they are facing and to take better decisions over time. It also entails partnering with mutants to explore entirely new financial mechanisms. (Signs of the future: Lankelly Chase, Indonesia waste banks, Dark Matter Labs)
Adopting new interfaces for working with the mutants
Harvard Business School professor Carliss Baldwin argued that most bureaucracies these days have a ‘non-contractible’ problem: they don’t know where smart people are, or how to evaluate how good they are. Most importantly, most smart people don’t want to work for them because they find them either too callous, unrewarding or slow (or a combination of all of these)….(More)”
The Wisdom of Networks – and the Lessons of Wikipedia
Philip Reitinger at the Analogies Project: “Douglas Merrill said “All of us are smarter than any of us.” This motto of crowdsourcing – looking to the information that can arise from the combined observation by and intelligence of many – is also the prescription for a more secure cyber future. Crowdsourcing security among machines – rather than people – is our best path forward.
Attackers have the advantage online for many reasons, including the ability to leverage a simple error into a significant compromise, to scale attacks more readily than defenses can scale, and to attack at a distance. While the maxim that defenders have to be right all the time, while attackers only have to be right once, is not literally true, it conveys the dilemma of defenders. The connectivity of our devices and agents is inexorably increasing, creating more targets for attack. The complexity of the software we use and the network we must defend is also increasing, making an attack on the individual target or the network easier. And the criticality of our connected systems to our lives is also growing and will continue to grow. Together, this means that we live in a world of steadily increasing risk.
In this environment, the good guys and gals have one significant but counter-intuitive advantage: the size of the network being defended. The soaring prevalence of smart devices is a risk only until it is not, until we combine the abilities of these devices to observe, to induce, and to act to defend the network itself. The cyber ecosystem is the greatest sensor network imaginable, and the data generated by its sensors can drive collective intelligence and collective action to stem threats and isolate infections. The ability of the network components to defend the network may make the future of cybersecurity on the Internet look very much like Wikipedia – one of the best known examples of crowdsourcing – with some obvious failures, but if of importance, generally quickly corrected….
What is necessary to enable the crowdsourcing of defense among network components? A few years ago, while I was at the Department of Homeland Security, it published a paper entitled “Enabling Distributed Security in Cyberspace: Building a Healthy and Resilient Cyber Ecosystem with Automated Collective Action.” This paper posits three requirements:
- Automation so the network can act at Internet speed;
- Interoperability so the barriers to effective collective (network or “crowd”) action are those we impose by policy, as opposed to those imposed on us by technology or process; and
- Authentication to enhance the decision-making and action of the network against attacks.
It has been five years since the paper was published, and I still think these are the key elements of a more secure Internet future. Until we enable the network to defend itself, using its own wisdom of crowds (of agents), offense wins. People should do what people do best, adjust how the network defends itself, and take action when necessary based on intuition, rather than responding to alerts. So when you think about future Internet security problems, think about Stephen Colbert and Wikipedia….(More)”
Next Generation Crowdsourcing for Collective Intelligence
Paper by John Prpić : “New techniques leveraging IT-mediated crowds such as Crowdsensing, Situated Crowdsourcing, Spatial Crowdsourcing, and Wearables Crowdsourcing have now materially emerged. These techniques, here termed next generation Crowdsourcing, serve to extend Crowdsourcing efforts beyond the heretofore dominant desktop computing paradigm. Employing new configurations of hardware, software, and people, these techniques represent new forms of organization for IT-mediated crowds. However, it is not known how these new techniques change the processes and outcomes of IT-mediated crowds for Collective Intelligence purposes? The aim of this exploratory work is to begin to answer this question. The work ensues by outlining the relevant findings of the first generation Crowdsourcing paradigm, before reviewing the emerging literature pertaining to the new generation of Crowdsourcing techniques. Premised on this review, a collectively exhaustive and mutually exclusive typology is formed, organizing the next generation Crowdsourcing techniques along two salient dimensions common to all first generation Crowdsourcing techniques. As a result, this work situates the next generation Crowdsourcing techniques within the extant Crowdsourcing literature, and identifies new research avenues stemming directly from the analysis….(More)”
Responsible Data reflection stories
Responsible Data Forum: “Through the various Responsible Data Forum events over the past couple of years, we’ve heard many anecdotes of responsible data challenges faced by people or organizations. These include potentially harmful data management practices, situations where people have experienced gut feelings that there is potential for harm, or workarounds that people have created to avoid those situations.
But we feel that trading in these “war stories” isn’t the most useful way for us to learn from these experiences as acommunity. Instead, we have worked with our communities to build a set of Reflection Stories: a structured, well-researched knowledge base on the unforeseen challenges and (sometimes) negative consequences of usingtechnology and data for social change.
We hope that this can offer opportunities for reflection and learning, as well as helping to develop innovativestrategies for engaging with technology and data in new and responsible ways….
What we learned from the stories
New spaces, new challenges
Moving into new digital spaces is bringing new challenges, and social media is one such space where these challengesare proving very difficult to navigate. This seems to stem from a number of key points:
- organisations with low levels of technical literacy and experience in tech- or data-driven projects, deciding toengage suddenly with a certain tool or technology without realising what this entails. For some, this seems to stemfrom funders being more willing to support ‘innovative’ tech projects.
- organisations wishing to engage more with social media while not being aware of more nuanced understandingsof public/private spaces online, and how different communities engage with social media. (see story #2)
unpredictability and different levels of visibility: due to how privacy settings on Twitter are currently set, visibilityof users can be increased hugely by the actions of others – and once that happens, a user actually has very littleagency to change or reverse that. Sadly, being more visible on, for example, Twitter disproportionately affectswomen and minority groups in a negative way – so while ‘signal boosting’ to raise someone’s profile might be well-meant, the consequences are hard to predict, and almost impossible to reverse manually. (see story #4) - consent: related to the above point, “giving consent” can mean many different things when it comes to digitalspaces, especially if the person in question has little experience or understanding of using the technology inquestion (see stories #4 and #5).
Grey areas of responsible data
In almost all of the cases we looked at, very few decisions were concretely “right” or “wrong”. There are many, manygrey areas here, which need to be addressed on a case by case basis. In some cases, people involved really did thinkthrough their actions, and approached their problems thoughtfully and responsibly – but consequences they had notimagined, happened (see story #8).
Additionally, given the quickly moving nature of the space, challenges can arise that simply would not have beenpossible at the start.
….Despite the very varying settings of the stories collected, the shared mitigation strategies indicate that there areindeed a few key principles that can be kept in mind throughout the development of a new tech- or data-drivenproject.
The most stark of these – and one key aspect that is underlying many of these challenges – is a fundamental lack of technical literacy among advocacy organisations. This affects the way they interact with technical partners, the decisions they make around the project, the level to which they can have meaningful input, and more. Perhaps more crucially, it also affects the ability to know what to ask for help about – ie, to ‘know the unknowns’.
Building an organisation’s technical literacy might not mean being able to answer all technical questions in-house, but rather knowing what to ask and what to expect in an answer, from others. For advocacy organisations who don’t (yet)have this, it becomes all too easy to outsource not just the actual technical work but the contextual decisions too, which should be a collaborative process, benefiting from both sets of expertise.
There seems to be a lot of scope to expand this set of stories both in terms of collecting more from other advocacy organisations, and into other sectors, too. Ultimately, we hope that sharing our collective intelligence around lessonslearned from responsible data challenges faced in projects, will contribute to a greater understanding for all of us….Read all the stories here
Platform for Mumbai’s slum entrepreneurs
Springwise: “We recently saw an initiative that empowered startup talent in a Finnish refugee camp, and now Design Museum Dharavi is a mobile museum that will provide a platform for makers in the Mumbai neighborhood.
The initiative is a brainchild of artist Jorge Rubio and Creative Industries Fund NL. Taking the model of a pop-up, it will stop at various locations throughout the neighborhood. Despite being an ‘informal settlement’, Dharavi is famed for producing very little waste due to a culture of recycling and repurposing. The mobile museum will showcase local makers, enable them to connect with potential clients and run workshops, ultimately elevating the global social perception towards life in the so-called ‘slums’. Home to over a million people, Dharavi has the additional tourism pull from appearing on the film Slumdog Millionaire…..(More)”
A Gargantuan Challenge for The Megalopolis: Mexico City calls citizens to help map its complex public bus system
“Mexico City, the largest and oldest urban agglomeration in the American continent. The city is home to an incredible diversity of people and cultures, and its size and its diversity also poses certain challenges. In a city with such big scale (the metropolitan area measures 4,887 mi2) transportation is one of its main problems. Finding ways to improve how people move within requires imagination and cooperation from decision makers and society alike.
The scale and dynamism of Mexico City’s public transport system represents a challenge to generate quality information. Processes for the generation of mobility data are time-consuming and expensive. Given this scenario, the best alternative for the city is to include transport users in generating this information.
The megalopolis lacks an updated, open database of its more than 1,500 bus routes. To tackle this problem, Laboratorio para la Ciudad (Mexico City’s experimental office and creative think-tank, reporting to the Mayor) partnered with 12 organizations that include NGOs and other government offices to develop Mapatón CDMX: a crowdsourcing and gamification experiment to map the city’s bus routes through civic collaboration and technology.
After one year of designing and testing a strategy, the team behind Mapatón CDMX is calling citizens to map the public transport system by participating on a city game from January 29th to February 14th 2016. The game’s goal is to map routes of licenced public transport (buses, minibuses and vans) from start to finish in order to score points, which is done through an app for Android devices that gathers GPS data from the user inside the bus.
The mappers will participate individually or in groups with friends and family for two weeks. As an incentive and once the mapping marathon is finished, those participants with higher scores will earn cash prizes and electronic devices. (A smart algorithm creates incentives to map the longest or most ignored routes, giving mappers extra points.) But what is most valuable: the data resulting will be openly available at the end of February 2016, much faster and cheaper than with traditional processes.
Mapatón CDMX is an innovative and effective way to generate updated and open information about transport routes as the game harnesses collective intelligence of the gargantuan city. Organisers consider that the open database may be used by anyone to create –for example– data driven policy, strategies for academic analysis, maps for users, applications, visualizations, among many other digital products….(More)”
Collective Intelligence in Law Reforms: When the Logic of the Crowds and the Logic of Policymaking Collide
Paper by Tanja Aitamurto: “…shows how the two virtues of collective intelligence – cognitive diversity and large crowds –turn into perils in crowdsourced policymaking. That is because of a conflict between the logic of the crowds and the logic of policymaking. The crowd’s logic differs from that of traditional policymaking in several aspects. To mention some of those: In traditional policymaking it is a small group of experts making proposals to the policy, whereas in crowdsourced policymaking, it is a large, anonymous crowd with a mixed level of expertise. The crowd proposes atomic ideas, whereas traditional policymaking is used to dealing with holistic and synthesized proposals. By drawing on data from a crowdsourced law-making process in Finland, the paper shows how the logics of the crowds and policymaking collide in practice. The conflict prevents policymaking fully benefiting from the crowd’s input, and it also hinders governments from adopting crowdsourcing more widely as a practice for deploying open policymaking practices….(More)”
Biases in collective platforms: Wikipedia, GitHub and crowdmapping
Stefana Broadbent at Nesta: “Many of the collaboratively developed knowledge platforms we discussed at our recent conference, At The Roots of Collective Intelligence, suffer from a well-known “contributors’ bias”.
More than 85% of Wikipedia’s entries have been written by men
OpenStack, as with most other Open Source projects, has seen the emergence of a small group of developers who author the majority of the projects. In fact 80% of the commits have been authored by slightly less than 8% of the authors, while 90% of the commits correspond to about 17% of all the authors.
GitHub’s Be Social function allows users to “follow” other participants and receive notification of their activity. The most popular contributors tend therefore to attract other users to the projects they are working on. And Open Street Map has 1.2 million registered users, but less than 15% of them have produced the majority of the 13 million elements of information.
Research by Quattrone, Capra, De Meo (2015) showed that while the content mapped was not different between active and occasional mappers, the social composition of the power users led to a geographical bias, with less affluent areas remaining unmapped more frequently than urban centres.
These well-known biases in crowdsourcing information, also known as the ‘power users’ effect, were discussed by Professor Licia Capra from the Department of Engineering at UCL. Watch the video of her talk here.
In essence, despite the fact that crowd-sourcing platforms are inclusive and open to anyone willing to dedicate the time and effort, there is a process of self-selection. Different factors can explain why there are certain gender and socio economic groups that are drawn to specific activities, but it is clear that there is a progressive reduction of the diversity of contributors over time.
The effect is more extreme where there is the need for continuous contributions. As the Humanitarian Open StreetMap Team project data showed, humanitarian crises attract many users who contribute intensely for a short time, but only very few participants contribute regularly for a long time. Only a small proportion of power users continue editing or adding code for sustained periods. This effect begs two important questions: does the editing job of the active few skew the information made available, and what can be done to avoid this type of concentration?….
The issue of how to attract more volunteers and editors is more complex and is a constant challenge for any crowdsourcing platform. We can look back at when Wikipedia started losing contributors, which coincided with a period of tighter restrictions to the editing process. This suggests that alongside designing the interface in a way to make contributions easy to be created and shared, it is also necessary to design practices and social norms that are immediately and continuously inclusive. – (More)”