Twelve principles for open innovation 2.0

Curated on Posted on by Stefaan Verhulst

Martin Curley in Nature: “A new mode of innovation is emerging that blurs the lines between universities, industry, governments and communities. It exploits disruptive technologies — such as cloud computing, the Internet of Things and big data — to solve societal challenges sustainably and profitably, and more quickly and ably than before. It is called open innovation 2.0 (ref. 1).

 The promise is sustainable, intelligent living: innovations drive economic growth and improve quality of life while reducing environmental impact and resource use. For example, a dynamic congestion-charging system can adjust traffic flow and offer incentives to use park-and-ride schemes, guided by real-time traffic levels and air quality. Car-to-car communication could manage traffic to minimize transit times and emissions and eliminate road deaths from collisions. Smart electricity grids lower costs, integrate renewable energies and balance loads. Health-care monitoring enables early interventions, improving life quality and reducing care costs.

Such innovations are being tested in ‘living labs’ in hundreds of cities. In Dublin, for example, the city council has partnered with my company, the technology firm Intel (of which I am a vice-president), to install a pilot network of sensors to improve flood management by measuring local rain fall and river levels, and detecting blocked drains. Eindhoven in the Netherlands is working with electronics firm Philips and others to develop intelligent street lighting. Communications-technology firm Ericsson, the KTH Royal Institute of Technology, IBM and others are collaborating to test self-driving buses in Kista, Sweden.

Yet many institutions and companies remain unaware of this radical shift. They often confuse invention and innovation. Invention is the creation of a technology or method. Innovation concerns the use of that technology or method to create value. The agile approaches needed for open innovation 2.0 conflict with the ‘command and control’ organizations of the industrial age (see ‘How innovation modes have evolved’). Institutional or societal cultures can inhibit user and citizen involvement. Intellectual-property (IP) models may inhibit collaboration. Government funders can stifle the emergence of ideas by requiring that detailed descriptions of proposed work are specified before research can begin. Measures of success, such as citations, discount innovation and impact. Policymaking lags behind the market place….

Keys to collaborative innovation

  1. Purpose. Efforts and intellects aligned through commitment rather than compliance deliver an impact greater than the sum of their parts. A great example is former US President John F. Kennedy’s vision of putting a man on the Moon. Articulating a shared value that can be created is important. A win–win scenario is more sustainable than a win–lose outcome.
  2. Partner. The ‘quadruple helix’ of government, industry, academia and citizens joining forces aligns goals, amplifies resources, attenuates risk and accelerates progress. A collaboration between Intel, University College London, Imperial College London and Innovate UK’s Future Cities Catapult is working in the Intel Collaborative Research Institute to improve people’s well-being in cities, for example to enable reduction of air pollution.
  3. Platform. An environment for collaboration is a basic requirement. Platforms should be integrated and modular, allowing a plug-and-play approach. They must be open to ensure low barriers to use, catalysing the evolution of a community. Challenges in security, standards, trust and privacy need to be addressed. For example, the Open Connectivity Foundation is securing interoperability for the Internet of Things.
  4. Possibilities. Returns may not come from a product but from the business model that enabled it, a better process or a new user experience. Strategic tools are available, such as industrial designer Larry Keeley’s breakdown of innovations into ten types in four categories: finance, process, offerings and delivery.
  5. Plan. Adoption and scale should be the focus of innovation efforts, not product creation. Around 20% of value is created when an innovation is established; more than 80% comes when it is widely adopted7. Focus on the ‘four Us’: utility (value to the user); usability; user experience; and ubiquity (designing in network effects).
  6. Pyramid. Enable users to drive innovation. They inspired two-thirds of innovations in semiconductors and printed circuit boards, for example. Lego Ideas encourages children and others to submit product proposals — submitters must get 10,000 supporters for their idea to be reviewed. Successful inventors get 1% of royalties.
  7. Problem. Most innovations come from a stated need. Ethnographic research with users, customers or the environment can identify problems and support brainstorming of solutions. Create a road map to ensure the shortest path to a solution.
  8. Prototype. Solutions need to be tested and improved through rapid experimentation with users and citizens. Prototyping shows how applicable a solution is, reduces the risks of failures and can reveal pain points. ‘Hackathons’, where developers come together to rapidly try things, are increasingly common.
  9. Pilot. Projects need to be implemented in the real world on small scales first. The Intel Collaborative Research Institute runs research projects in London’s parks, neighbourhoods and schools. Barcelona’s Laboratori — which involves the quadruple helix — is pioneering open ‘living lab’ methods in the city to boost culture, knowledge, creativity and innovation.
  10. Product. Prototypes need to be converted into viable commercial products or services through scaling up and new infrastructure globally. Cloud computing allows even small start-ups to scale with volume, velocity and resilience.
  11. Product service systems. Organizations need to move from just delivering products to also delivering related services that improve sustainability as well as profitability. Rolls-Royce sells ‘power by the hour’ — hours of flight time rather than jet engines — enabled by advanced telemetry. The ultimate goal of open innovation 2.0 is a circular or performance economy, focused on services and reuse rather than consumption and waste.
  12. Process. Innovation is a team sport. Organizations, ecosystems and communities should measure, manage and improve their innovation processes to deliver results that are predictable, probable and profitable. Agile methods supported by automation shorten the time from idea to implementation….(More)”

Society’s biggest problems need more than a nudge

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 at the Conversation: “So-called “nudge units” are popping up in governments all around the world.

The best-known examples include the U.K.’s Behavioural Insights Team, created in 2010, and the White House-based Social and Behavioral Sciences Team, introduced by the Obama administration in 2014. Their mission is to leverage findings from behavioral science so that people’s decisions can be nudged in the direction of their best intentions without curtailing their ability to make choices that don’t align with their priorities.

Overall, these – and other – governments have made important strides when it comes to using behavioral science to nudge their constituents into better choices.

Yet, the same governments have done little to improve their own decision-making processes. Consider big missteps like the Flint water crisis. How could officials in Michigan decide to place an essential service – safe water – and almost 100,000 people at risk in order to save US$100 per day for three months? No defensible decision-making process should have allowed this call to be made.

When it comes to many of the big decisions faced by governments – and the private sector – behavioral science has more to offer than simple nudges.

Behavioral scientists who study decision-making processes could also help policy-makers understand why things went wrong in Flint, and how to get their arms around a wide array of society’s biggest problems – from energy transitions to how to best approach the refugee crisis in Syria.

When nudges are enough

The idea of nudging people in the direction of decisions that are in their own best interest has been around for a while. But it was popularized in 2008 with the publication of the bestseller “Nudge“ by Richard Thaler of the University of Chicago and Cass Sunstein of Harvard.

A common nudge goes something like this: if we want to eat better but are having a hard time doing it, choice architects can reengineer the environment in which we make our food choices so that healthier options are intuitively easier to select, without making it unrealistically difficult to eat junk food if that’s what we’d rather do. So, for example, we can shelve healthy foods at eye level in supermarkets, with less-healthy options relegated to the shelves nearer to the floor….

Sometimes a nudge isn’t enough

Nudges work for a wide array of choices, from ones we face every day to those that we face infrequently. Likewise, nudges are particularly well-suited to decisions that are complex with lots of different alternatives to choose from. And, they are advocated in situations where the outcomes of our decisions are delayed far enough into the future that they feel uncertain or abstract. This describes many of the big decisions policy-makers face, so it makes sense to think the solution must be more nudge units.

But herein lies the rub. For every context where a nudge seems like a realistic option, there’s at least another context where the application of passive decision support would be either be impossible – or, worse, a mistake.

Take, for example, the question of energy transitions. These transitions are often characterized by the move from infrastructure based on fossil fuels to renewables to address all manner of risks, including those from climate change. These are decisions that society makes infrequently. They are complex. And, the outcomes – which are based on our ability to meet conflicting economic, social and environmental objectives – will be delayed.

But, absent regulation that would place severe restrictions on the kinds of options we could choose from – and which, incidentally, would violate the freedom-of-choice tenet of choice architecture – there’s no way to put renewable infrastructure options at proverbial eye level for state or federal decision-makers, or their stakeholders.

Simply put, a nudge for a decision like this would be impossible. In these cases, decisions have to be made the old-fashioned way: with a heavy lift instead of a nudge.

Complex policy decisions like this require what we call active decision support….(More)”

Insights On Collective Problem-Solving: Complexity, Categorization And Lessons From Academia

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Part 3 of an interview series by Henry Farrell for the MacArthur Research Network on Opening Governance: “…Complexity theorists have devoted enormous energy and attention to thinking about how complex problems, in which different factors interact in ways that are hard to predict, can best be solved. One key challenge is categorizing problems, so as to understand which approaches are best suited to addressing them.

Scott Page is the Leonid Hurwicz Collegiate Professor of Complex Systems at the University of Michigan, Ann Arbor, and one of the world’s foremost experts on diversity and problem-solving. I asked him a series of questions about how we might use insights from academic research to think better about how problem solving works.

Henry: One of the key issues of collective problem-solving is what you call the ‘problem of problems’ – the question of identifying which problems we need to solve. This is often politically controversial – e.g., it may be hard to get agreement that global warming, or inequality, or long prison sentences are a problem. How do we best go about identifying problems, given that people may disagree?

Scott: In a recent big think paper on the potential of diversity for collective problem solving in Scientific American, Katherine Phillips writes that group members must feel validated, that they must share a commitment to the group, and they must have a common goal if they are going to contribute. This implies that you won’t succeed in getting people to collaborate by setting an agenda from on high and then seeking to attract diverse people to further that agenda.

One way of starting to tackle the problem of problems is to steal a rule of thumb from Getting to Yes, by getting to think people about their broad interests rather than the position that they’re starting from. People often agree on their fundamental desires but disagree on how they can be achieved. For example, nearly everyone wants less crime, but they may disagree over whether they think the solution to crime involves tackling poverty or imposing longer prison sentences. If you can get them to focus on their common interest in solving crime rather than their disagreements, you’re more likely to get them to collaborate usefully.

Segregation amplifies the problem of problems. We live in towns and neighborhoods segregated by race, income, ideology, and human capital. Democrats live near Democrats and Republicans near Republicans. Consensus requires integration. We must work across ideologies. Relatedly, opportunity requires more than access. Many people grow up not knowing any engineers, dentists, doctors, lawyers, and statisticians. This isolation narrows the set of careers they consider and it reduces the diversity of many professions. We cannot imagine lives we do not know.

Henry: Once you get past the problem of problems, you still need to identify which kind of problem you are dealing with. You identify three standard types of problems: solution problems, selection problems and optimization problems. What – very briefly – are the key differences between these kinds of problems?

Scott: I’m constantly pondering the potential set of categories in which collective intelligence can emerge. I’m teaching a course on collective intelligence this semester and the undergraduates and I developed an acronym SCARCE PIGS to describe the different types of domains. Here’s the brief summary:

  • Predict: when individuals combine information, models, or measurements to estimate a future event, guess an answer, or classify an event. Examples might involve betting markets, or combined efforts to guess a quantity, such as Francis Galton’s example of people at a fair trying to guess the weight of a steer.
  • Identify: when individuals have local, partial, or possibly erroneous knowledge and collectively can find an object. Here, an example is DARPA’s Red Balloon project.
  • Solve: when individuals apply and possibly combine higher order cognitive processes and analytic tools for the purpose of finding or improving a solution to a task. Innocentive and similar organizations provide examples of this.
  • Generate: when individuals apply diverse representations, heuristics, and knowledge to produce something new. An everyday example is creating a new building.
  • Coordinate: when individuals adopt similar actions, behaviors, beliefs, or mental frameworks by learning through local interactions. Ordinary social conventions such as people greeting each other are good examples.
  • Cooperate: when individuals take actions, not necessarily in their self interest, that collectively produce a desirable outcome. Here, think of managing common pool resources (e.g. fishing boats not overfishing an area that they collectively control).
  • Arrange: when individuals manipulate items in a physical or virtual environment for their own purposes resulting in an organization of that environment. As an example, imagine a student co-op which keeps twenty types of hot sauce in its pantry. If each student puts whichever hot sauce she uses in the front of the pantry, then on average, the hot sauces will be arranged according to popularity, with the most favored hot sauces in the front and the least favored lost in the back.
  • Respond: when individuals react to external or internal stimuli creating collective responses that maintains system level functioning. For example, when yellow jackets attack a predator to maintain the colony, they are displaying this kind of problem solving.
  • Emerge: when individual parts create a whole that has categorically distinct and new functionalities. The most obvious example of this is the human brain….(More)”

Workplace innovation in the public sector

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Eurofound: “Innovative organisational practices in the workplace, which aim to make best use of human capital, are traditionally associated with the private sector. The nature of the public sector activities makes it more difficult to identify these types of internal innovation in publicly funded organisations.

It is widely thought that public sector organisations are neither dynamic nor creative and are typified by a high degree of inertia. Yet the necessity of innovation ought not to be dismissed. The public sector represents a quarter of total EU employment, and it is of critical importance as a provider and regulator of services. Improving how it performs has a knock-on effect not only for private sector growth but also for citizens’ satisfaction. Ultimately, this improves governance itself.

So how can innovative organisation practices help in dealing with the challenges faced by the public sector? Eurofound, as part of a project on workplace innovation in European companies, carried out case studies of both private and public sector organisations. The findings show a number of interesting practices and processes used.

Employee participation

The case studies from the public sector, some of which are described below, demonstrate the central role of employee participation in the implementation of workplace innovation and its impacts on organisation and employees. They indicate that innovative practices have resulted in enhanced organisational performance and quality of working life.

It is widely thought that changes in the public sector are initiated as a response to government policies. This is often true, but workplace innovation may also be introduced as a result of well-designed initiatives driven by external pressures (such as the need for a more competitive public service) or internal pressures (such as a need to update the skills map to better serve the public).

Case study findings

The state-owned Lithuanian energy company Lietuvos Energijos Gamyba (140 KB PDF) encourages employee participation by providing a structured framework for all employees to propose improvements. This has required a change in managerial approach and has spread a sense of ownership horizontally and vertically in the company. The Polish public transport company Jarosław City Transport (191 KB PDF), when faced with serious financial stability challenges, as well as implementing operational changes, set up ways for employees’ voices to be heard, which enabled a contributory dialogue and strengthened partnerships. Consultation, development of mutual trust, and common involvement ensured an effective combination of top-down and bottom-up initiatives.

The Lithuanian Post, AB Lietuvos Pastas (136 KB PDF) experienced a major organisation transformation in 2010 to improve efficiency and quality of service. Through a programme of ‘Loyalty day’ monthly visits, both top and middle management of the central administration visit any part of the company and work with colleagues in other units. Under budgetary pressure to ‘earn their money’, the Danish Vej and Park Bornholm (142 KB PDF) construction services in roads, parks and forests had to find innovative solutions to deal with a merger and privatisation. Their intervention had the characteristics of workplace partnership with a new set of organisational values set from the bottom up. Self-managing teams are essential for the operation of the company.

The world of education has provided new structures that provide better outcomes for students. The South West University of Bulgaria (214 KB PDF) also operates small self-managing teams responsible for employee scheduling. Weekly round-tables encourage participation in collectively finding solutions, creating a more effective environment in which to respond to the competitive demands of education provision.

In Poland, an initiative by the Pomeranian Library (185 KB PDF) improved employee–management dialogue and communication through increased participation. The initiative is a response to the new frameworks for open access to knowledge for users, with the library mirroring the user experience through its own work practices.

Through new dialogue, government advisory bodies have also developed employee-led improvement. Breaking away from a traditional hierarchy is considered important in achieving a more flexible work organisation. Under considerable pressure, the top-heavy management of the British Geological Survey (89 KB PDF) now operates a flexible matrix that promotes innovative and entrepreneurial ways of working. And in Germany, Niersverband (138 KB PDF), a publicly owned water-management company innovated through training, learning, reflection partnerships and workplace partnerships. New occupational profiles were developed to meet external demands. Based on dialogue concerning workplace experiences and competences, employees acquired new qualifications that allowed the company to be more competitive.

In the Funen Village Museum in Odense, Denmark, (143 KB PDF) innovation came about at the request of staff looking for more flexibility in how they work. Formerly most of their work was maintenance tasks, but now they can now engage more with visitors. Control of schedules has moved to the team rather than being the responsibility of a single manager. As a result, museum employees are now hosts as well as craftspeople. They no longer feel ‘forgotten’ and are happier in their work….(More)”

The report Workplace innovation in European companies provides a full analysis of the case studies.

The 51 case studies and the  list of companies (PDF 119 KB) the case studies are based on are available for download.

E-Government Strategy, ICT and Innovation for Citizen Engagement

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Brief by Dennis Anderson, Robert Wu, Dr. June-Suh Cho, and Katja Schroeder: “This book discusses three levels of e-government and national strategies to reach a citizen-centric participatory e-government, and examines how disruptive technologies help shape the future of e-government. The authors examine how e-government can facilitate a symbiotic relationship between the government and its citizens. ICTs aid this relationship and promote transparencies so that citizens can place greater trust in the activities of their government. If a government can manage resources more effectively by better understanding the needs of its citizens, it can create a sustainable environment for citizens. Having a national strategy on ICT in government and e-government can significantly reduce government waste, corruption, and inefficiency. Businesses, CIOs and CTOs in the public sector interested in meeting sustainability requirements will find this book useful. …(More)”

Wiki-fishing

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The Economist: “….Mr Rhoads is a member of a network started by the Alaska Longline Fishermen’s Association (ALFA), which aims to do something about this and to reduce by-catch of sensitive species such as rockfish at the same time. Network fishermen, who numbered only 20 at the project’s start, agreed to share data on where and what they were catching in order to create maps that highlighted areas of high by-catch. Within two years they had reduced accidental rockfish harvest by as much as 20%.

The rockfish mapping project expanded to create detailed maps of the sea floor, pooling data gathered by transducers fixed to the bottoms of boats. By combining thousands of data points as vessels traverse the fishing grounds, these “wikimaps”—created and updated through crowdsourcing—show gravel beds where bottom-dwelling halibut are likely to linger, craggy terrain where rockfish tend to lurk, and outcrops that could snag gear.

Public charts are imprecise, and equipment with the capability to sense this level of detail could cost a fisherman more than $70,000. Skippers join ALFA for as little as $250, invest a couple of thousand dollars in computers and software and enter into an agreement to turn over fishing data and not to share the information outside the network, which now includes 85 fishermen.

Skippers say the project makes them more efficient, better able to find the sort of fish they want and avoid squandering time on lost or tangled gear. It also means fewer hooks in the water and fewer hours at sea to catch the same amount of fish….(More)”

Selected Readings on Data and Humanitarian Response

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By Prianka Srinivasan and Stefaan G. Verhulst *

The Living Library’s Selected Readings series seeks to build a knowledge base on innovative approaches for improving the effectiveness and legitimacy of governance. This curated and annotated collection of recommended works on the topic of data and humanitarian response was originally published in 2016.

Data, when used well in a trusted manner, allows humanitarian organizations to innovate how to respond to emergency events, including better coordination of post-disaster relief efforts, the ability to harness local knowledge to create more targeted relief strategies, and tools to predict and monitor disasters in real time. Consequently, in recent years both multinational groups and community-based advocates have begun to integrate data collection and evaluation strategies into their humanitarian operations, to better and more quickly respond to emergencies. However, this movement poses a number of challenges. Compared to the private sector, humanitarian organizations are often less equipped to successfully analyze and manage big data, which pose a number of risks related to the security of victims’ data. Furthermore, complex power dynamics which exist within humanitarian spaces may be further exacerbated through the introduction of new technologies and big data collection mechanisms. In the below we share:

  • Selected Reading List (summaries and hyperlinks)
  • Annotated Selected Reading List
  • Additional Readings

Selected Reading List  (summaries in alphabetical order)

Data and Humanitarian Response

Risks of Using Big Data in Humanitarian Context

Annotated Selected Reading List (in alphabetical order)

Karlsrud, John. “Peacekeeping 4.0: Harnessing the Potential of Big Data, Social Media, and Cyber Technologies.” Cyberspace and International Relations, 2013. http://bit.ly/235Qb3e

  • This chapter from the book “Cyberspace and International Relations” suggests that advances in big data give humanitarian organizations unprecedented opportunities to prevent and mitigate natural disasters and humanitarian crises. However, the sheer amount of unstructured data necessitates effective “data mining” strategies for multinational organizations to make the most use of this data.
  • By profiling some civil-society organizations who use big data in their peacekeeping efforts, Karlsrud suggests that these community-focused initiatives are leading the movement toward analyzing and using big data in countries vulnerable to crisis.
  • The chapter concludes by offering ten recommendations to UN peacekeeping forces to best realize the potential of big data and new technology in supporting their operations.

Mancini, Fancesco. “New Technology and the prevention of Violence and Conflict.” International Peace Institute, 2013. http://bit.ly/1ltLfNV

  • This report from the International Peace Institute looks at five case studies to assess how information and communications technologies (ICTs) can help prevent humanitarian conflicts and violence. Their findings suggest that context has a significant impact on the ability for these ICTs for conflict prevention, and any strategies must take into account the specific contingencies of the region to be successful.
  • The report suggests seven lessons gleaned from the five case studies:
    • New technologies are just one in a variety of tools to combat violence. Consequently, organizations must investigate a variety of complementary strategies to prevent conflicts, and not simply rely on ICTs.
    • Not every community or social group will have the same relationship to technology, and their ability to adopt new technologies are similarly influenced by their context. Therefore, a detailed needs assessment must take place before any new technologies are implemented.
    • New technologies may be co-opted by violent groups seeking to maintain conflict in the region. Consequently, humanitarian groups must be sensitive to existing political actors and be aware of possible negative consequences these new technologies may spark.
    • Local input is integral to support conflict prevention measures, and there exists need for collaboration and awareness-raising with communities to ensure new technologies are sustainable and effective.
    • Information shared between civil-society has more potential to develop early-warning systems. This horizontal distribution of information can also allow communities to maintain the accountability of local leaders.

Meier, Patrick. “Digital humanitarians: how big data is changing the face of humanitarian response.” Crc Press, 2015. http://amzn.to/1RQ4ozc

  • This book traces the emergence of “Digital Humanitarians”—people who harness new digital tools and technologies to support humanitarian action. Meier suggests that this has created a “nervous system” to connect people from disparate parts of the world, revolutionizing the way we respond to humanitarian crises.
  • Meier argues that such technology is reconfiguring the structure of the humanitarian space, where victims are not simply passive recipients of aid but can contribute with other global citizens. This in turn makes us more humane and engaged people.

Robertson, Andrew and Olson, Steve. “Using Data Sharing to Improve Coordination in Peacebuilding.” United States Institute for Peace, 2012. http://bit.ly/235QuLm

  • This report functions as an overview of a roundtable workshop on Technology, Science and Peace Building held at the United States Institute of Peace. The workshop aimed to investigate how data-sharing techniques can be developed for use in peace building or conflict management.
  • Four main themes emerged from discussions during the workshop:
    • “Data sharing requires working across a technology-culture divide”—Data sharing needs the foundation of a strong relationship, which can depend on sociocultural, rather than technological, factors.
    • “Information sharing requires building and maintaining trust”—These relationships are often built on trust, which can include both technological and social perspectives.
    • “Information sharing requires linking civilian-military policy discussions to technology”—Even when sophisticated data-sharing technologies exist, continuous engagement between different stakeholders is necessary. Therefore, procedures used to maintain civil-military engagement should be broadened to include technology.
    • “Collaboration software needs to be aligned with user needs”—technology providers need to keep in mind the needs of its users, in this case peacebuilders, in order to ensure sustainability.

United Nations Independent Expert Advisory Group on a Data Revolution for Sustainable Development. “A World That Counts, Mobilizing the Data Revolution.” 2014. https://bit.ly/2Cb3lXq

  • This report focuses on the potential benefits and risks data holds for sustainable development. Included in this is a strategic framework for using and managing data for humanitarian purposes. It describes a need for a multinational consensus to be developed to ensure data is shared effectively and efficiently.
  • It suggests that “people who are counted”—i.e., those who are included in data collection processes—have better development outcomes and a better chance for humanitarian response in emergency or conflict situations.

Katie Whipkey and Andrej Verity. “Guidance for Incorporating Big Data into Humanitarian Operations.” Digital Humanitarian Network, 2015. http://bit.ly/1Y2BMkQ

  • This report produced by the Digital Humanitarian Network provides an overview of big data, and how humanitarian organizations can integrate this technology into their humanitarian response. It primarily functions as a guide for organizations, and provides concise, brief outlines of what big data is, and how it can benefit humanitarian groups.
  • The report puts forward four main benefits acquired through the use of big data by humanitarian organizations: 1) the ability to leverage real-time information; 2) the ability to make more informed decisions; 3) the ability to learn new insights; 4) the ability for organizations to be more prepared.
  • It goes on to assess seven challenges big data poses for humanitarian organizations: 1) geography, and the unequal access to technology across regions; 2) the potential for user error when processing data; 3) limited technology; 4) questionable validity of data; 5) underdeveloped policies and ethics relating to data management; 6) limitations relating to staff knowledge.

Risks of Using Big Data in Humanitarian Context
Crawford, Kate, and Megan Finn. “The limits of crisis data: analytical and ethical challenges of using social and mobile data to understand disasters.” GeoJournal 80.4, 2015. http://bit.ly/1X0F7AI

  • Crawford & Finn present a critical analysis of the use of big data in disaster management, taking a more skeptical tone to the data revolution facing humanitarian response.
  • They argue that though social and mobile data analysis can yield important insights and tools in crisis events, it also presents a number of limitations which can lead to oversights being made by researchers or humanitarian response teams.
  • Crawford & Finn explore the ethical concerns the use of big data in disaster events introduces, including issues of power, privacy, and consent.
  • The paper concludes by recommending that critical data studies, such as those presented in the paper, be integrated into crisis event research in order to analyze some of the assumptions which underlie mobile and social data.

Jacobsen, Katja Lindskov (2010) Making design safe for citizens: A hidden history of humanitarian experimentation. Citizenship Studies 14.1: 89-103. http://bit.ly/1YaRTwG

  • This paper explores the phenomenon of “humanitarian experimentation,” where victims of disaster or conflict are the subjects of experiments to test the application of technologies before they are administered in greater civilian populations.
  • By analyzing the particular use of iris recognition technology during the repatriation of Afghan refugees to Pakistan in 2002 to 2007, Jacobsen suggests that this “humanitarian experimentation” compromises the security of already vulnerable refugees in order to better deliver biometric product to the rest of the world.

Responsible Data Forum. “Responsible Data Reflection Stories: An Overview.” http://bit.ly/1Rszrz1

  • This piece from the Responsible Data forum is primarily a compilation of “war stories” which follow some of the challenges in using big data for social good. By drawing on these crowdsourced cases, the Forum also presents an overview which makes key recommendations to overcome some of the challenges associated with big data in humanitarian organizations.
  • It finds that most of these challenges occur when organizations are ill-equipped to manage data and new technologies, or are unaware about how different groups interact in digital spaces in different ways.

Sandvik, Kristin Bergtora. “The humanitarian cyberspace: shrinking space or an expanding frontier?” Third World Quarterly 37:1, 17-32, 2016. http://bit.ly/1PIiACK

  • This paper analyzes the shift toward more technology-driven humanitarian work, where humanitarian work increasingly takes place online in cyberspace, reshaping the definition and application of aid. This has occurred along with what many suggest is a shrinking of the humanitarian space.
  • Sandvik provides three interpretations of this phenomena:
    • First, traditional threats remain in the humanitarian space, which are both modified and reinforced by technology.
    • Second, new threats are introduced by the increasing use of technology in humanitarianism, and consequently the humanitarian space may be broadening, not shrinking.
    • Finally, if the shrinking humanitarian space theory holds, cyberspace offers one example of this, where the increasing use of digital technology to manage disasters leads to a contraction of space through the proliferation of remote services.

Additional Readings on Data and Humanitarian Response

* Thanks to: Kristen B. Sandvik; Zara Rahman; Jennifer Schulte; Sean McDonald; Paul Currion; Dinorah Cantú-Pedraza and the Responsible Data Listserve for valuable input.

Knowledge Unbound

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MIT Press: “Peter Suber has been a leading advocate for open access since 2001 and has worked full time on issues of open access since 2003. As a professor of philosophy during the early days of the internet, he realized its power and potential as a medium for scholarship. As he writes now, “it was like an asteroid crash, fundamentally changing the environment, challenging dinosaurs to adapt, and challenging all of us to figure out whether we were dinosaurs.” When Suber began putting his writings and course materials online for anyone to use for any purpose, he soon experienced the benefits of that wider exposure. In 2001, he started a newsletter—the Free Online Scholarship Newsletter, which later became the SPARC Open Access Newsletter—in which he explored the implications of open access for research and scholarship. This book offers a selection of some of Suber’s most significant and influential writings on open access from 2002 to 2010.

In these texts, Suber makes the case for open access to research; answers common questions, objections, and misunderstandings; analyzes policy issues; and documents the growth and evolution of open access during its most critical early decade. (Free Download)”

 

Data Mining Reveals the Four Urban Conditions That Create Vibrant City Life

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Emerging Technology from the arXiv: “Lack of evidence to city planning has ruined cities all over the world. But data-mining techniques are finally revealing the rules that make cities successful, vibrant places to live. …Back in 1961, the gradual decline of many city centers in the U.S. began to puzzle urban planners and activists alike. One of them, the urban sociologist Jane Jacobs, began a widespread and detailed investigation of the causes and published her conclusions in The Death and Life of Great American Cities, a controversial book that proposed four conditions that are essential for vibrant city life.

Jacobs’s conclusions have become hugely influential. Her ideas have had a significant impact on the development of many modern cities such as Toronto and New York City’s Greenwich Village. However, her ideas have also attracted criticism because of the lack of empirical evidence to back them up, a problem that is widespread in urban planning.
Today, that looks set to change thanks to the work of Marco De Nadai at the University of Trento and a few pals, who have developed a way to gather urban data that they use to test Jacobs’s conditions and how they relate to the vitality of city life. The new approach heralds a new age of city planning in which planners have an objective way of assessing city life and working out how it can be improved.
In her book, Jacobs argues that vibrant activity can only flourish in cities when the physical environment is diverse. This diversity, she says, requires four conditions. The first is that city districts must serve more than two functions so that they attract people with different purposes at different times of the day and night. Second, city blocks must be small with dense intersections that give pedestrians many opportunities to interact. The third condition is that buildings must be diverse in terms of age and form to support a mix of low-rent and high-rent tenants. By contrast, an area with exclusively new buildings can only attract businesses and tenants wealthy enough to support the cost of new building. Finally, a district must have a sufficient density of people and buildings.

While Jacobs’s arguments are persuasive, her critics say there is little evidence to show that these factors are linked with vibrant city life. That changed last year when urban scientists in Seoul, South Korea, published the result of a 10-year study of pedestrian activity in the city at unprecedented resolution. This work successfully tested Jacobs’s ideas for the first time.
However, the data was gathered largely through pedestrian surveys, a process that is time-consuming, costly, and generally impractical for use in most modern cities.
De Nadai and co have come up with a much cheaper and quicker alternative using a new generation of city databases and the way people use social media and mobile phones. The new databases include OpenStreetMap, the collaborative mapping tool; census data, which records populations and building use; land use data, which uses satellite images to classify land use according to various categories; Foursquare data, which records geographic details about personal activity; and mobile-phone records showing the number and frequency of calls in an area.
De Nadai and co gathered this data for six cities in Italy—Rome, Naples, Florence, Bologna, Milan, and Palermo.
Their analysis is straightforward. The team used mobile-phone activity as a measure of urban vitality and land-use records, census data, and Foursquare activity as a measure of urban diversity. Their goal was to see how vitality and diversity are correlated in the cities they studied. The results make for interesting reading….(More)

The Wisdom of Networks – and the Lessons of Wikipedia

Curated on Posted on by Stefaan Verhulst

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)”