Open innovation in the public sector


Sabrina Diaz Rato in OpenDemocracy: “For some years now, we have been witnessing the emergence of relational, cross-over, participative power. This is the territory that gives technopolitics its meaning and prominence, the basis on which a new vision of democracy – more open, more direct, more interactive – is being developed and embraced. It is a framework that overcomes the closed architecture on which the praxis of governance (closed, hierarchical, one-way) have been cemented in almost all areas. The series The ecosystem of open democracy explores the different aspects of this ongoing transformation….

How can innovation contribute to building an open democracy? The answer is summed up in these ten connectors of innovation.

  1. placing innovation and collective intelligence at the center of public management strategies,
  2. aligning all government areas with clearly-defined goals on associative platforms,
  3. shifting the frontiers of knowledge and action from the institutions to public deliberation on local challenges,
  4. establishing leadership roles, in a language that everyone can easily understand, to organize and plan the wealth of information coming out of citizens’ ideas and to engage those involved in the sustainability of the projects,
  5. mapping the ecosystem and establishing dynamic relations with internal and, particularly, external agents: the citizens,
  6. systematizing the accumulation of information and the creative processes, while communicating progress and giving feedback to the whole community,
  7. preparing society as a whole to experience a new form of governance of the common good,
  8. cooperating with universities, research centers and entrepreneurs in establishing reward mechanisms,
  9. aligning people, technologies, institutions and the narrative with the new urban habits, especially those related to environmental sustainability and public services,
  10. creating education and training programs in tune with the new skills of the 21st century,
  11. building incubation spaces for startups responding to local challenges,
  12. inviting venture capital to generate a satisfactory mix of open innovation, inclusive development policies and local productivity.

Two items in this list are probably the determining factors of any effective innovation process. The first has to do with the correct decision on the mechanisms through which we have pushed the boundaries outwards, so as to bring citizen ideas into the design and co-creation of solutions. This is not an easy task, because it requires a shared organizational mentality on previously non-existent patterns of cooperation, which must now be sustained through dialog and operational dynamics aimed at solving problems defined by external actors – not just any problem.

Another key aspect of the process, related to the breaking down of the institutional barriers that surround and condition action frameworks, is the revaluation of a central figure that we have not yet mentioned here: the policy makers. They are not exactly political leaders or public officials. They are not innovators either. They are the ones within Public Administration who possess highly valuable management skills and knowledge, but who are constantly colliding against the glittering institutional constellations that no longer work….(More)”

Crowdsourcing Cybersecurity: Cyber Attack Detection using Social Media


Paper by Rupinder Paul Khandpur, Taoran Ji, Steve Jan, Gang Wang, Chang-Tien Lu, Naren Ramakrishnan: “Social media is often viewed as a sensor into various societal events such as disease outbreaks, protests, and elections. We describe the use of social media as a crowdsourced sensor to gain insight into ongoing cyber-attacks. Our approach detects a broad range of cyber-attacks (e.g., distributed denial of service (DDOS) attacks, data breaches, and account hijacking) in an unsupervised manner using just a limited fixed set of seed event triggers. A new query expansion strategy based on convolutional kernels and dependency parses helps model reporting structure and aids in identifying key event characteristics. Through a large-scale analysis over Twitter, we demonstrate that our approach consistently identifies and encodes events, outperforming existing methods….(More)”

Will Democracy Survive Big Data and Artificial Intelligence?


Dirk Helbing, Bruno S. Frey, Gerd Gigerenzer, Ernst Hafen, Michael Hagner, Yvonne Hofstetter, Jeroen van den Hoven, Roberto V. Zicari, and Andrej Zwitter in Scientific American: “….In summary, it can be said that we are now at a crossroads (see Fig. 2). Big data, artificial intelligence, cybernetics and behavioral economics are shaping our society—for better or worse. If such widespread technologies are not compatible with our society’s core values, sooner or later they will cause extensive damage. They could lead to an automated society with totalitarian features. In the worst case, a centralized artificial intelligence would control what we know, what we think and how we act. We are at the historic moment, where we have to decide on the right path—a path that allows us all to benefit from the digital revolution. Therefore, we urge to adhere to the following fundamental principles:

1. to increasingly decentralize the function of information systems;

2. to support informational self-determination and participation;

3. to improve transparency in order to achieve greater trust;

4. to reduce the distortion and pollution of information;

5. to enable user-controlled information filters;

6. to support social and economic diversity;

7. to improve interoperability and collaborative opportunities;

8. to create digital assistants and coordination tools;

9. to support collective intelligence, and

10. to promote responsible behavior of citizens in the digital world through digital literacy and enlightenment.

Following this digital agenda we would all benefit from the fruits of the digital revolution: the economy, government and citizens alike. What are we waiting for?A strategy for the digital age

Big data and artificial intelligence are undoubtedly important innovations. They have an enormous potential to catalyze economic value and social progress, from personalized healthcare to sustainable cities. It is totally unacceptable, however, to use these technologies to incapacitate the citizen. Big nudging and citizen scores abuse centrally collected personal data for behavioral control in ways that are totalitarian in nature. This is not only incompatible with human rights and democratic principles, but also inappropriate to manage modern, innovative societies. In order to solve the genuine problems of the world, far better approaches in the fields of information and risk management are required. The research area of responsible innovation and the initiative ”Data for Humanity” (see “Big Data for the benefit of society and humanity”) provide guidance as to how big data and artificial intelligence should be used for the benefit of society….(More)”

From Nairobi to Manila, mobile phones are changing the lives of bus riders


Shomik Mehnidrata at Transport for Development Blog: “Every day around the world, millions of people rely on buses to get around. In many cities, these services carry the bulk of urban trips, especially in Africa and Latin America. They are known by many different names—matatus, dalalas, minibus taxis, colectivos, diablos rojos, micros, etc.—but all have one thing in common: they are either hardly regulated… or not regulated at all. Although buses play a critical role in the daily life of many urban dwellers, there are a variety of complaints that have spurred calls for improvement and reform.

However, we are now witnessing a different, more organic kind of change that is disrupting the world of informal buses using ubiquitous cheap sensors and mobile technology. One hotbed of innovation is Nairobi, Kenya’s bustling capital. Two years ago, Nairobi made a splash in the world of urban transport by mapping all the routes of informal matatus. Other countries have sought to replicate this model, with open source tools and crowdsourcing supporting similar efforts in Mexico, Manila, and beyond. Back in Nairobi, the Magic Bus app helps commuters use sms services to reserve and pay for seats in matatus; in September 2016, MagicBus’ potential for easing commuter pain in the Kenyan capital was rewarded with a $1 million prize. Other programs implemented in collaboration with insurers and operators are experimenting with on-board sensors to identify and correct dangerous driver behavior such as sudden braking and acceleration. Ma3Route, also in Nairobi (there is a pattern here!) used crowdsourcing to identify dangerous drivers as well as congestion. At the same time, operators are upping their game: using technology to improve system management, control and routing in La Paz, and working with universities to improve their financial planning and capabilities in Cape Town.

Against this backdrop, the question is then: can these ongoing experimental initiatives offer a coherent alternative to formal reform? …(More)”.

Organizational crowdsourcing


Jeremy Morgan at Lippincott: “One of the most consequential insights from the study of organizational culture happens to have an almost irresistible grounding in basic common sense. When attempting to solve the challenges of today’s businesses, inviting a broad slice of an employee population yields more creative, actionable solutions than restricting the conversation to a small strategy or leadership team.

This recognition, that in order to uncover new business ideas and innovations, organizations must foster listening cultures and a meritocracy of best thinking, is fueling interest in organizational crowdsourcing — a discipline focused on employee connection, collaboration and ideation. Leaders at companies such as Roche, Bank of the West, Merck, Facebook and IBM, along with countless Silicon Valley companies for whom the “hackathon” is a major cultural event, have embraced employee crowdsourcing as a way to unlock organizational knowledge and promote empathy through technology.

The benefits of internal crowdsourcing are clear. First, it ensures that a company’s understanding of key change drivers and potential strategic priorities is grounded in the organization’s everyday reality and not abstract hypotheses developed by a team of strategists. Second, employees inherently believe in and want to own the implementation of ideas that they generate through crowdsourcing. These are ideas borne of the culture for the culture, and are less likely to run aground on the rocks of employee indifference….

How can this be achieved through organizational crowdsourcing?

There is no out-of-the-box solution. Each campaign has to organically surface areas of focus for further inquiries, develop a framework and set of questions to guide participation and ignite conversations, and then analyze and communicate results in a way that helps bring solutions to life. But there are some key principles that will maximize the success of any crowdsourcing effort.

Obtaining insightful and actionable answers boils down to asking the questions at just the right altitude. If they’re too high up, too broad and open-ended, the usefulness of the feedback will suffer. If the questions are too broad — “How can we make our workplace better?” — you will likely hear responses like “juice bars” and “massage therapists.” If the questions are too narrow — “What kind of lighting do we need in our conference rooms?” — you limit the opportunity of people to use their creativity. However, the answers are likely to spark a conversation if people are asked, “How can we create spaces that allow us to generate ideas more effectively?” Conversation will flow to discussion of breaking down physical barriers in office design, building social “hubs” and investing in live events that allow employees from disparate geographies to meet in person and solve problems together.

On the technology side, crowdsourcing platforms such as Jive Software and UserVoice, among others, make it easy to bring large numbers of employees together to gather, build upon and prioritize new ideas and innovation efforts, from process simplification and product development to the transformation of customer experiences. Respondents can vote on other people’s suggestions and add comments.

By facilitating targeted conversations across times zones, geographies and corporate functions, crowdsourcing makes possible a new way of listening: of harnessing an organization’s collective wisdom to achieve action by a united and inspired employee population. It’s amazing to see the thoughtfulness, precision and energy unleashed by crowdsourcing efforts. People genuinely want to contribute to their company’s success if you open the doors and let them.

Taking a page from the Silicon Valley hackathon, organizational crowdsourcing campaigns are structured as events of limited duration focused on a specific challenge or business problem….(More)”

DataRefuge


DataRefuge is a public, collaborative project designed to address the following concerns about federal climate and environmental data:

  • What are the best ways to safeguard data?
  • How do federal agencies play crucial roles in data collection, management, and distribution?
  • How do government priorities impact data’s accessibility?
  • Which projects and research fields depend on federal data?
  • Which data sets are of value to research and local communities, and why?

DataRefuge is also an initiative committed to identifying, assessing, prioritizing, securing, and distributing reliable copies of federal climate and environmental data so that it remains available to researchers. Data collected as part of the #DataRefuge initiative will be stored in multiple, trusted locations to help ensure continued accessibility.

DataRefuge acknowledges–and in fact draws attention to–the fact that there are no guarantees of perfectly safe information. But there are ways that we can create safe and trustworthy copies. DataRefuge is thus also a project to develop the best methods, practices, and protocols to do so.

DataRefuge depends on local communities. We welcome new collaborators who want to organize DataRescue Events or build DataRefuge in other ways.

There are many ways to be involved with building DataRefuge. They’re not mutually exclusive!…(More)”

RideComfort: A Development of Crowdsourcing Smartphones in Measuring Train Ride Quality


Adam Azzoug and Sakdirat Kaewunruen in Frontiers in Built Environment: “Among the many million train journeys taking place every day, not all of them are being measured or monitored for ride comfort. Improving ride comfort is important for railway companies to attract more passengers to their train services. Giving passengers the ability to measure ride comfort themselves using their smartphones allows railway companies to receive instant feedback from passengers regarding the ride quality on their trains. The purpose of this development is to investigate the feasibility of using smartphones to measure vibration-based ride comfort on trains. This can be accomplished by developing a smartphone application, analyzing the data recorded by the application, and verifying the data by comparing it to data from a track inspection vehicle or an accelerometer. A literature review was undertaken to examine the commonly used standards to evaluate ride comfort, such as the BS ISO 2631-1:1997 standard and Sperling’s ride index as proposed by Sperling and Betzhold (1956). The literature review has also revealed some physical causes of ride discomfort such as vibrations induced by roughness and irregularities present at the wheel/rail interface. We are the first to use artificial neural networks to map data derived from smartphones in order to evaluate ride quality. Our work demonstrates the merits of using smartphones to measure ride comfort aboard trains and suggests recommendations for future technological improvement. Our data argue that the accelerometers found in modern smartphones are of sufficient quality to be used in evaluating ride comfort. The ride comfort levels predicted both by BS ISO 2631-1 and Sperling’s index exhibit excellent agreement…(More)”

Crowdsourced Science: Sociotechnical Epistemology in the e-Research Paradigm


Paper by David Watson and Luciano Floridi: “Recent years have seen a surge in online collaboration between experts and amateurs on scientific research. In this article, we analyse the epistemological implications of these crowdsourced projects, with a focus on Zooniverse, the world’s largest citizen science web portal. We use quantitative methods to evaluate the platform’s success in producing large volumes of observation statements and high impact scientific discoveries relative to more conventional means of data processing. Through empirical evidence, Bayesian reasoning, and conceptual analysis, we show how information and communication technologies enhance the reliability, scalability, and connectivity of crowdsourced e-research, giving online citizen science projects powerful epistemic advantages over more traditional modes of scientific investigation. These results highlight the essential role played by technologically mediated social interaction in contemporary knowledge production. We conclude by calling for an explicitly sociotechnical turn in the philosophy of science that combines insights from statistics and logic to analyse the latest developments in scientific research….(More)”

The value of crowdsourcing in public policymaking: epistemic, democratic and economic value


 &  in The Theory and Practice of Legislation: “While national and local governments increasingly deploy crowdsourcing in lawmaking as an open government practice, it remains unclear how crowdsourcing creates value when it is applied in policymaking. Therefore, in this article, we examine value creation in crowdsourcing for public policymaking. We introduce a framework for analysing value creation in public policymaking in the following three dimensions: democratic, epistemic and economic. Democratic value is created by increasing transparency, accountability, inclusiveness and deliberation in crowdsourced policymaking. Epistemic value is developed when crowdsourcing serves as a knowledge search mechanism and a learning context. Economic value is created when crowdsourcing makes knowledge search in policymaking more efficient and enables government to produce policies that better address citizens’ needs and societal issues. We show how these tenets of value creation are manifest in crowdsourced policymaking by drawing on instances of crowdsourced lawmaking, and we also discuss the contingencies and challenges preventing value creation…(More)”

‘Collective intelligence’ is not necessarily present in virtual groups


Jordan B. Barlow and Alan R. Dennis at LSE: “Do groups of smart people perform better than groups of less intelligent people?

Research published in Science magazine in 2010 reported that groups, like individuals, have a certain level of “collective intelligence,” such that some groups perform consistently well across many different types of tasks, while other groups perform consistently poorly. Collective intelligence is similar to individual intelligence, but at the group level.

Interestingly, the Science study found that collective intelligence was not related to the individual intelligence of group members; groups of people with higher intelligence did not perform better than groups with lower intelligence. Instead, the study found that high performing teams had members with higher social sensitivity – the ability to read the emotions of others using visual facial cues.

Social sensitivity is important when we sit across a table from each other. But what about online, when we exchange emails or text messages? Does social sensitivity matter when I can’t see your face?

We examined the collective intelligence in an online environment in which groups used text-based computer-mediated communication. We followed the same procedures as the original Science study, which used the approach typically used to measure individual intelligence. In individual intelligence tests, a person completes several small “tasks” or problems. An analysis of task scores typically demonstrates that task scores are correlated, meaning that if a person does well on one problem, it is likely that they did well on other problems….

The results were not what we expected. The correlations between our groups’ performance scores were either not statistically significant or significantly negative, as shown in Table 1. The average correlation between any two tasks was -0.05, indicating that performance on one task was not correlated with performance on other tasks. In other words, groups who performed well on one of the tasks were unlikely to perform well on the other tasks…

Our findings challenge the conclusion reported in Science that groups have a general collective intelligence analogous to individual intelligence. Our study shows that no collective intelligence factor emerged when groups used a popular commercial text-based online tool. That is, when using tools with limited visual cues, groups that performed well on one task were no more likely to perform well on a different task. Thus the “collective intelligence” factor related to social sensitivity that was reported in Science is not collective intelligence; it is instead a factor associated with the ability to work well using face-to-face communication, and does not transcend media….(More)”