Predicting crime, LAPD-style

Curated on Posted on by Stefaan Verhulst

The Guardian: “The Los Angeles Police Department, like many urban police forces today, is both heavily armed and thoroughly computerised. The Real-Time Analysis and Critical Response Division in downtown LA is its central processor. Rows of crime analysts and technologists sit before a wall covered in video screens stretching more than 10 metres wide. Multiple news broadcasts are playing simultaneously, and a real-time earthquake map is tracking the region’s seismic activity. Half-a-dozen security cameras are focused on the Hollywood sign, the city’s icon. In the centre of this video menagerie is an oversized satellite map showing some of the most recent arrests made across the city – a couple of burglaries, a few assaults, a shooting.

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On a slightly smaller screen the division’s top official, Captain John Romero, mans the keyboard and zooms in on a comparably micro-scale section of LA. It represents just 500 feet by 500 feet. Over the past six months, this sub-block section of the city has seen three vehicle burglaries and two property burglaries – an atypical concentration. And, according to a new algorithm crunching crime numbers in LA and dozens of other cities worldwide, it’s a sign that yet more crime is likely to occur right here in this tiny pocket of the city.
The algorithm at play is performing what’s commonly referred to as predictive policing. Using years – and sometimes decades – worth of crime reports, the algorithm analyses the data to identify areas with high probabilities for certain types of crime, placing little red boxes on maps of the city that are streamed into patrol cars. “Burglars tend to be territorial, so once they find a neighbourhood where they get good stuff, they come back again and again,” Romero says. “And that assists the algorithm in placing the boxes.”
Romero likens the process to an amateur fisherman using a fish finder device to help identify where fish are in a lake. An experienced fisherman would probably know where to look simply by the fish species, time of day, and so on. “Similarly, a really good officer would be able to go out and find these boxes. This kind of makes the average guys’ ability to find the crime a little bit better.”
Predictive policing is just one tool in this new, tech-enhanced and data-fortified era of fighting and preventing crime. As the ability to collect, store and analyse data becomes cheaper and easier, law enforcement agencies all over the world are adopting techniques that harness the potential of technology to provide more and better information. But while these new tools have been welcomed by law enforcement agencies, they’re raising concerns about privacy, surveillance and how much power should be given over to computer algorithms.
P Jeffrey Brantingham is a professor of anthropology at UCLA who helped develop the predictive policing system that is now licensed to dozens of police departments under the brand name PredPol. “This is not Minority Report,” he’s quick to say, referring to the science-fiction story often associated with PredPol’s technique and proprietary algorithm. “Minority Report is about predicting who will commit a crime before they commit it. This is about predicting where and when crime is most likely to occur, not who will commit it.”…”

The Impact of Open: Keeping you healthy

Curated on Posted on by Stefaan Verhulst

of Sunlight: “In healthcare, the goal-set shared widely throughout the field is known as “the Triple Aim”: improving individual experience of care, improving population health, and reducing the cost of care. Across the wide array of initiatives undertaken by health care data users, the great majority seem to fall within the scope of at least one aspect of the Triple Aim. Below is a set of examples that reveal how data — both open and not — is being used to achieve its elements.

The use of open data to reduce costs:

The use of open data to improve quality of care:

  • Using open data on a substantial series of individual hospital quality measures, CMS created a hospital comparison tool that allows consumers to compare average quality of care outcomes across their local hospitals.

  • Non-profit organizations survey hospitals and have used this data to provide another national measure of hospital quality that consumers can use to select a high-quality hospital.

  • In New York state, widely-shared data on cardiac surgery outcomes associated with individual providers has led to improved outcomes and better understanding of successful techniques.

  • In the UK, the National Health Service is actively working towards defining concrete metrics to evaluate how the system as a whole is moving towards improved quality. …

  • The broad cultural shift towards data-sharing in healthcare appears to have facilitated additional secured sharing in order to achieve the joint goal of improving healthcare quality and effectiveness. The current effort to securely network of millions of patient data records through the federal PCORI system has the potential to advance understanding of disease treatment at an unprecedented pace.

  • Through third-party tools, people are able to use the products of aggregated patient data in order to begin diagnosing their own symptoms more accurately, giving them a head start in understanding how to optimize their visit to a provider.

The use of open data to improve population health:

  • Out of the three elements of the triple aim, population health may have the longest and deepest relationship with open data. Public datasets like those collected by the Centers for Disease Control and the US Census have for decades been used to monitor disease prevalence, verify access to health insurance, and track mortality and morbidity statistics.

  • Population health improvement has been a major focus for newer developments as well. Health data has been a regular feature in tech efforts to improve the ways that governments — including local health departments — reach their constituencies. The use of data in new communication tools improves population health by increasing population awareness of local health trends and disease prevention opportunities. Two examples of this work in action include the Chicago Health Atlas, which combines health data and healthcare consumer problem-solving, and Philadelphia’s map interface to city data about available flu vaccines.

One final observation for open data advocates to take from health data concerns the way that the sector encourages the two-way information flow: it embraces the notion that data users can also be data producers. Open data ecosystems are properly characterized by multi-directional relationships among governmental and non-governmental actors, with opportunities for feedback, correction and augmentation of open datasets. That this happens at the scale of health data is important and meaningful for open data advocates who can face push-back when they ask their governments to ingest externally-generated data….”

15 Ways to bring Civic Innovation to your City

Curated on Posted on by Stefaan Verhulst

Chris Moore at AcuitasGov: “In my previous blog post I wrote about a desire to see our Governments transform to be part of the  21st century.  I saw a recent reference to how governments across Canada have lost their global leadership, how government in Canada at all levels is providing analog services to a digital society.  I couldn’t agree more.  I have been thinking lately about some practical ways that Mayors and City Managers could innovate in their communities.  I realize that there are a number of municipal elections happening this fall across Canada, a time when leadership changes and new ideas emerge.  So this blog is also for Mayoral candidates who have a sense that technology and innovation have a role to play in their city and in their administration.
I thought I would identify 15 initiatives that cities could pursue as part of their Civic Innovation Strategy.   For the last 50 years technology in local government in Canada has been viewed as an expense, as a necessary evil, not always understood by elected officials and senior administrators.  Information and Technology is part of every aspect of a city, it is critical in delivering services.  It is time to not just think of this as an expense but as an investment, as a way to innovate, reduce costs, enhance citizen service delivery and transform government operations.
Here are my top 15 ways to bring Civic Innovation to your city:
1. Build 21st Century Digital Infrastructure like the Chattanooga Gig City Project.
2. Build WiFi networks like the City of Edmonton on your own and in partnership with others.
3. Provide technology and internet to children and youth in need like the City of Toronto.
4. Connect to a national Education and Research network like Cybera in Alberta and CANARIE.
5. Create a Mayors Task-force on Innovation and Technology leveraging your city’s resources.
6. Run a hackathon or two or three like the City of Glasgow or maybe host a hacking health event like the City of Vancouver.
7. Launch a Startup incubator like Startup Edmonton or take it to the next level and create a civic lab like the City of Barcelona.
8. Develop an Open Government Strategy, I like to the Open City Strategy from Edmonton.
9. If Open Government is too much then just start with Open Data, Edmonton has one of the best.
10. Build a Citizen Dashboard to showcase your cities services and commitment to the public.
11. Put your Crime data online like the Edmonton Police Service.
12. Consider a pilot project with sensor technology for parking like the City of Nice or for  waste management like the City of Barcelona.
13. Embrace Car2Go, Modo and UBER as ways to move people in your city.
14. Consider turning your IT department into the Innovation and Technology Department like they did at the City of Chicago.
15. Partner with other near by local governments to create a shared Innovation and Technology agency.
Now more than ever before cities need to find ways to innovate, to transform and to create a foundation that is sustainable.  Now is the time for both courage and innovations in government.  What is your city doing to move into the 21st Century?”

Towards a comparative science of cities: using mobile traffic records in New York, London and Hong Kong

Curated on Posted on by Stefaan Verhulst

Book chapter by S. Grauwin, S. Sobolevsky, S. Moritz, I. Gódor, C. Ratti, to be published in “Computational Approaches for Urban Environments” (Springer Ed.), October 2014: “This chapter examines the possibility to analyze and compare human activities in an urban environment based on the detection of mobile phone usage patterns. Thanks to an unprecedented collection of counter data recording the number of calls, SMS, and data transfers resolved both in time and space, we confirm the connection between temporal activity profile and land usage in three global cities: New York, London and Hong Kong. By comparing whole cities typical patterns, we provide insights on how cultural, technological and economical factors shape human dynamics. At a more local scale, we use clustering analysis to identify locations with similar patterns within a city. Our research reveals a universal structure of cities, with core financial centers all sharing similar activity patterns and commercial or residential areas with more city-specific patterns. These findings hint that as the economy becomes more global, common patterns emerge in business areas of different cities across the globe, while the impact of local conditions still remains recognizable on the level of routine people activity.”

Government, Foundations Turn to Cash Prizes to Generate Solutions

Curated on Posted on by Stefaan Verhulst

Megan O’Neil at the Chronicle of Philanthropy: “Government agencies and philanthropic organizations are increasingly staging competitions as a way generate interest in solving difficult technological, social, and environmental problems, according to a new report.
“The Craft of Prize Design: Lessons From the Public Sector” found that well-designed competitions backed by cash incentives can help organizations attract new ideas, mobilize action, and stimulate markets.
“Incentive prizes have transformed from an exotic open innovation to a proven innovation strategy for the public, private, and philanthropic sectors,” the report says.
Produced by Deloitte Consulting’s innovation practice, the report was financially supported by Bloomberg Philanthropies and the Case; Joyce; John S. and James L. Knight; Kresge; and Rockefeller foundations.
The federal government has staged more than 350 prize competitions during the past five years to stimulate innovation and crowdsource solutions, according to the report. And philanthropic organizations are also fronting prizes for competitions promoting innovative responses to questions such as how to strengthen communities and encourage sustainable energy consumption.
One example cited by the report is the Talent Dividend Prize, sponsored by CEOs for Cities and the Kresge Foundation, which awards $1-million to the city that most increases its college graduation rate during a four-year period. A second example is the MIT Clean Energy Prize, co-sponsored by the U.S. Department of Energy, which offered a total of $1 million in prize money. Submissions generated $85 million in capital and research grants, according to the report.
A prize-based project should not be adopted when an established approach to solve a problem already exists or if potential participants don’t have the interest or time to work on solving a problem, the report concludes. Instead, prize designers must gauge the capacity of potential participants before announcing a prize, and make sure that it will spur the discovery of new solutions.”

App pays commuters to take routes that ease congestion

Curated on Posted on by Stefaan Verhulst

Springwise: “Congestion at peak hours is a major problem in the world’s busiest city centres. We’ve recently seen Gothenburg in Sweden offering free bicycles to ease the burden on public transport services, but now a new app is looking to take a different approach to the same problem. Urban Engines uses algorithms to help cities determine key congestion choke points and times, and can then reward commuters for avoiding them.
The Urban Engines system is based on commuters using the smart commuter cards already found in many major cities. The company tracks journeys made with those commuter cards, and uses that data to identify main areas of congestion, and at what times the congestion occurs. The system has already been employed in Washington, D.C, and Sao Paulo, Brazil, helping provide valuable data for work with city planners.
It’s in Singapore, however, where the most interesting work has been achieved so far. There, commuters who have signed up and registered their commuter cards can earn rewards when they travel. They will earn one point for every kilometre travelled during peak hours, or triple that when travelling off-peak. The points earned can then be converted into discounts on future journeys, or put towards an in-app raffle game, where they have the opportunity to win sums of money. Urban Engines claim there’s been a 7 to 13 percent reduction in journeys made during peak hours, with 200,000 commuters taking part.
The company is based on an original experiment carried out in Bangalore. The rewards program there, carried out among 20,000 employees of the Indian company Infosys, lead to 17 percent of traffic shifting to off-peak travel times in six months. A similarly successful experiment has also been carried out on the Stanford University campus, and the plan is to now expand to other major cities…”

In Defense of Transit Apps

Curated on Posted on by Stefaan Verhulst

Mark Headd at Civic Innovations: “The civic technology community has a love-hate relationship with transit apps.
We love to, and often do, use the example of open transit data and the cottage industry of civic app development it has helped spawn as justification for governments releasing open data. Some of the earliest, most enduring and most successful civic applications have been built on transit data and there literally hundreds of different apps available.
The General Transit Feed Specification (GTFS), which has helped to encourage the release of transit data from dozens and dozens of transportation authorities across the country, is used as the model for the development of other open data standards. I once described work being done to develop a data standard for locations dispensing vaccinations as “GTFS for flu shots.”
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But some in the civic technology community chafe at the overuse of transit apps as the example cited for the release of open data and engagement with outside civic hackers. Surely there are other examples we can point to that get at deeper, more fundamental problems with civic engagement and the operation of government. Is the best articulation of the benefits of open data and civic hacking a simple bus stop application?
Last week at Transparency Camp in DC, during a session I ran on open data, I was asked what data governments should focus on releasing as open data. I stated my belief that – at a minimum – governments should concentrate on The 3 B’s: Buses (transit data), Bullets (crime data) and Bucks (budget & expenditure data).
To be clear – transit data and the apps it helps generate are critical to the open data and civic technology movements. I think it is vital to exploring the role that transit apps have played in the development of the civic technology ecosystem and their impact on open data.

Story telling with transit data

Transit data supports more than just “next bus” apps. In fact, characterizing all transit apps this way does a disservice to the talented and creative people working to build things with transit data. Transit data supports a wide range of different visualizations that can tell an intimate, granular story about how a transit system works and how it’s operation impacts a city.
One inspiring example of this kind of app was developed recently by Mike Barry and Brian Card, and looked at the operation of MBTA in Boston. Their motive was simple:

We attempt to present this information to help people in Boston better understand the trains, how people use the trains, and how the people and trains interact with each other.

We’re able to tell nuanced stories about transit systems because the quality of data being released continues to expand and improve in quality. This happens because developers building apps in cities across the country have provided feedback to transit officials on what they want to see and the quality of what is provided.
Developers building the powerful visualizations we see today are standing on the shoulders of the people that built the “next bus” apps a few years ago. Without these humble apps, we don’t get to tell these powerful stories today.

Holding government accountable

Transit apps are about more than just getting to the train on time.
Support for transit system operations can run into the billions of dollars and affect the lives of millions of people in an urban area. With this much investment, it’s important that transit riders and taxpayers are able to hold officials accountable for the efficient operation of transit systems. To help us do this, we now have a new generation of transit apps that can examine things like the scheduled arrival and departure times of trains with their actual arrival and departure time.
Not only does this give citizens transparency into how well their transit system is being run, it offers a pathway for engagement – by knowing which routes are not performing close to scheduled times, transit riders and others can offer suggestions for changes and improvements.

A gateway to more open data

One of the most important things that transit apps can do is provide a pathway for more open data.
In Philadelphia, the city’s formal open data policy and the creation of an open data portal all followed after the efforts of a small group of developers working to obtain transit schedule data from the Southeastern Pennsylvania Transportation Authority (SEPTA). This group eventually built the region’s first transit app.
This small group pushed SEPTA to make their data open, and the Authority eventually embraced open data. This, in turn, raised the profile of open data with other city leaders and directly contributed to the adoption of an open data policy by the City of Philadelphia several years later. Without this simple transit app and the push for more open transit data, I don’t think this would have happened. Certainly not as soon as it did.
And it isn’t just big cities like Philadelphia. In Syracuse, NY – a small city with no tradition of civic hacking and no formal open data program – a group at a local hackathon decided that they wanted to build a platform for government open data.
The first data source they selected to focus on? Transit data. The first app they built? A transit app…”

Crowdsourcing and social search

Curated on Posted on by Stefaan Verhulst

at Techcrunch: “When we think of the sharing economy, what often comes to mind are sites like Airbnb, Lyft, or Feastly — the platforms that allow us to meet people for a specific reason, whether that’s a place to stay, a ride, or a meal.
But what about sharing something much simpler than that, like answers to our questions about the world around us? Sharing knowledge with strangers can offer us insight into a place we are curious about or trying to navigate, and in a more personal, efficient way than using traditional web searches.
“Sharing an answer or response to question, that is true sharing. There’s no financial or monetary exchange based on that. It’s the true meaning of [the word],” said Maxime Leroy, co-founder and CEO of a new app called Enquire.
Enquire is a new question-and-answer app, but it is unlike others in the space. You don’t have to log in via Facebook or Twitter, use SMS messaging like on Quest, or upload an image like you do on Jelly. None of these apps have taken off yet, which could be good or bad for Enquire just entering the space.
With Enquire, simply log in with a username and password and it will unlock the neighborhood you are in (the app only works in San Francisco, New York, and Paris right now). There are lists of answers to other questions, or you can post your own. If 200 people in a city sign up, the app will become available to them, which is an effort to make sure there is a strong community to gather answers from.
Leroy, who recently made a documentary about the sharing economy, realized there was “one tool missing for local communities” in the space, and decided to create this app.
“We want to build a more local-based network, and empower and increase trust without having people share all their identity,” he said.
Different social channels look at search in different ways, but the trend is definitely moving to more social searching or location-based searching, according to according to Altimeter social media analyst Rebecca Lieb. Arguably, she said, Yelp, Groupon, and even Google Maps are vertical search engines. If you want to find a nearby restaurant, pharmacy, or deal, you look to these platforms.
However, she credits Aardvark as one of the first in the space, which was a social search engine founded in 2007 that used instant messaging and email to get answers from your existing contacts. Google bought the company in 2010. It shows the idea of crowdsourcing answers isn’t new, but the engines have become “appified,” she said.
“Now it’s geo-local specific,” she said. “We’re asking a lot more of those geo-local questions because of location-based immediacy [that we want].”
Think Seamless, with which you find the food nearby that most satisfies your appetite. Even Tinder and Grindr are social search engines, Lieb said. You want to meet up with the people that are closest to you, geographically….
His challenge is to offer rewards to incite people to sign up for the app. Eventually, Leroy would like to strengthen the networks and scale Enquire to cities and neighborhoods all over the world. Once that’s in place, people can start creating their own neighborhoods — around a school or workplace, where they hang out regularly — instead of using the existing constraints.
“I may be an expert in one area, and a newbie in another. I want to emphasize the activity and content from users to give them credit to other users and build that trust,” he said.
Usually, our first instinct is to open Yelp to find the best sushi restaurant or Google to search the closest concert venue, and it will probably stay that way for some time. But the idea that the opinions and insights of other human beings, even of strangers, is becoming much more valuable because of the internet is not far-fetched.
Admit it: haven’t you had a fleeting thought of starting a Kickstarter campaign for an idea? Looked for a cheaper place to stay on Airbnb than that hotel you normally book in New York? Or considered financing someone’s business idea across the world using Kiva? If so, then you’ve engaged in social search.
Suddenly, crowdsourcing answers for the things that pique your interest on your morning walk may not seem so strange after all.”

Selected Readings on Crowdsourcing Tasks and Peer Production

Curated on Posted on by Andrew Young

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 crowdsourcing was originally published in 2014.

Technological advances are creating a new paradigm by which institutions and organizations are increasingly outsourcing tasks to an open community, allocating specific needs to a flexible, willing and dispersed workforce. “Microtasking” platforms like Amazon’s Mechanical Turk are a burgeoning source of income for individuals who contribute their time, skills and knowledge on a per-task basis. In parallel, citizen science projects – task-based initiatives in which citizens of any background can help contribute to scientific research – like Galaxy Zoo are demonstrating the ability of lay and expert citizens alike to make small, useful contributions to aid large, complex undertakings. As governing institutions seek to do more with less, looking to the success of citizen science and microtasking initiatives could provide a blueprint for engaging citizens to help accomplish difficult, time-consuming objectives at little cost. Moreover, the incredible success of peer-production projects – best exemplified by Wikipedia – instills optimism regarding the public’s willingness and ability to complete relatively small tasks that feed into a greater whole and benefit the public good. You can learn more about this new wave of “collective intelligence” by following the MIT Center for Collective Intelligence and their annual Collective Intelligence Conference.

Selected Reading List (in alphabetical order)

Annotated Selected Reading List (in alphabetical order)

Benkler, Yochai. The Wealth of Networks: How Social Production Transforms Markets and Freedom. Yale University Press, 2006. http://bit.ly/1aaU7Yb.

  • In this book, Benkler “describes how patterns of information, knowledge, and cultural production are changing – and shows that the way information and knowledge are made available can either limit or enlarge the ways people can create and express themselves.”
  • In his discussion on Wikipedia – one of many paradigmatic examples of people collaborating without financial reward – he calls attention to the notable ongoing cooperation taking place among a diversity of individuals. He argues that, “The important point is that Wikipedia requires not only mechanical cooperation among people, but a commitment to a particular style of writing and describing concepts that is far from intuitive or natural to people. It requires self-discipline. It enforces the behavior it requires primarily through appeal to the common enterprise that the participants are engaged in…”

Brabham, Daren C. Using Crowdsourcing in Government. Collaborating Across Boundaries Series. IBM Center for The Business of Government, 2013. http://bit.ly/17gzBTA.

  • In this report, Brabham categorizes government crowdsourcing cases into a “four-part, problem-based typology, encouraging government leaders and public administrators to consider these open problem-solving techniques as a way to engage the public and tackle difficult policy and administrative tasks more effectively and efficiently using online communities.”
  • The proposed four-part typology describes the following types of crowdsourcing in government:
    • Knowledge Discovery and Management
    • Distributed Human Intelligence Tasking
    • Broadcast Search
    • Peer-Vetted Creative Production
  • In his discussion on Distributed Human Intelligence Tasking, Brabham argues that Amazon’s Mechanical Turk and other microtasking platforms could be useful in a number of governance scenarios, including:
    • Governments and scholars transcribing historical document scans
    • Public health departments translating health campaign materials into foreign languages to benefit constituents who do not speak the native language
    • Governments translating tax documents, school enrollment and immunization brochures, and other important materials into minority languages
    • Helping governments predict citizens’ behavior, “such as for predicting their use of public transit or other services or for predicting behaviors that could inform public health practitioners and environmental policy makers”

Boudreau, Kevin J., Patrick Gaule, Karim Lakhani, Christoph Reidl, Anita Williams Woolley. “From Crowds to Collaborators: Initiating Effort & Catalyzing Interactions Among Online Creative Workers.” Harvard Business School Technology & Operations Mgt. Unit Working Paper No. 14-060. January 23, 2014. https://bit.ly/2QVmGUu.

  • In this working paper, the authors explore the “conditions necessary for eliciting effort from those affecting the quality of interdependent teamwork” and “consider the the role of incentives versus social processes in catalyzing collaboration.”
  • The paper’s findings are based on an experiment involving 260 individuals randomly assigned to 52 teams working toward solutions to a complex problem.
  • The authors determined the level of effort in such collaborative undertakings are sensitive to cash incentives. However, collaboration among teams was driven more by the active participation of teammates, rather than any monetary reward.

Franzoni, Chiara, and Henry Sauermann. “Crowd Science: The Organization of Scientific Research in Open Collaborative Projects.” Research Policy (August 14, 2013). http://bit.ly/HihFyj.

  • In this paper, the authors explore the concept of crowd science, which they define based on two important features: “participation in a project is open to a wide base of potential contributors, and intermediate inputs such as data or problem solving algorithms are made openly available.” The rationale for their study and conceptual framework is the “growing attention from the scientific community, but also policy makers, funding agencies and managers who seek to evaluate its potential benefits and challenges. Based on the experiences of early crowd science projects, the opportunities are considerable.”
  • Based on the study of a number of crowd science projects – including governance-related initiatives like Patients Like Me – the authors identify a number of potential benefits in the following categories:
    • Knowledge-related benefits
    • Benefits from open participation
    • Benefits from the open disclosure of intermediate inputs
    • Motivational benefits
  • The authors also identify a number of challenges:
    • Organizational challenges
    • Matching projects and people
    • Division of labor and integration of contributions
    • Project leadership
    • Motivational challenges
    • Sustaining contributor involvement
    • Supporting a broader set of motivations
    • Reconciling conflicting motivations

Kittur, Aniket, Ed H. Chi, and Bongwon Suh. “Crowdsourcing User Studies with Mechanical Turk.” In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, 453–456. CHI ’08. New York, NY, USA: ACM, 2008. http://bit.ly/1a3Op48.

  • In this paper, the authors examine “[m]icro-task markets, such as Amazon’s Mechanical Turk, [which] offer a potential paradigm for engaging a large number of users for low time and monetary costs. [They] investigate the utility of a micro-task market for collecting user measurements, and discuss design considerations for developing remote micro user evaluation tasks.”
  • The authors conclude that in addition to providing a means for crowdsourcing small, clearly defined, often non-skill-intensive tasks, “Micro-task markets such as Amazon’s Mechanical Turk are promising platforms for conducting a variety of user study tasks, ranging from surveys to rapid prototyping to quantitative measures. Hundreds of users can be recruited for highly interactive tasks for marginal costs within a timeframe of days or even minutes. However, special care must be taken in the design of the task, especially for user measurements that are subjective or qualitative.”

Kittur, Aniket, Jeffrey V. Nickerson, Michael S. Bernstein, Elizabeth M. Gerber, Aaron Shaw, John Zimmerman, Matthew Lease, and John J. Horton. “The Future of Crowd Work.” In 16th ACM Conference on Computer Supported Cooperative Work (CSCW 2013), 2012. http://bit.ly/1c1GJD3.

  • In this paper, the authors discuss paid crowd work, which “offers remarkable opportunities for improving productivity, social mobility, and the global economy by engaging a geographically distributed workforce to complete complex tasks on demand and at scale.” However, they caution that, “it is also possible that crowd work will fail to achieve its potential, focusing on assembly-line piecework.”
  • The authors argue that seven key challenges must be met to ensure that crowd work processes evolve and reach their full potential:
    • Designing workflows
    • Assigning tasks
    • Supporting hierarchical structure
    • Enabling real-time crowd work
    • Supporting synchronous collaboration
    • Controlling quality

Madison, Michael J. “Commons at the Intersection of Peer Production, Citizen Science, and Big Data: Galaxy Zoo.” In Convening Cultural Commons, 2013. http://bit.ly/1ih9Xzm.

  • This paper explores a “case of commons governance grounded in research in modern astronomy. The case, Galaxy Zoo, is a leading example of at least three different contemporary phenomena. In the first place, Galaxy Zoo is a global citizen science project, in which volunteer non-scientists have been recruited to participate in large-scale data analysis on the Internet. In the second place, Galaxy Zoo is a highly successful example of peer production, some times known as crowdsourcing…In the third place, is a highly visible example of data-intensive science, sometimes referred to as e-science or Big Data science, by which scientific researchers develop methods to grapple with the massive volumes of digital data now available to them via modern sensing and imaging technologies.”
  • Madison concludes that the success of Galaxy Zoo has not been the result of the “character of its information resources (scientific data) and rules regarding their usage,” but rather, the fact that the “community was guided from the outset by a vision of a specific organizational solution to a specific research problem in astronomy, initiated and governed, over time, by professional astronomers in collaboration with their expanding universe of volunteers.”

Malone, Thomas W., Robert Laubacher and Chrysanthos Dellarocas. “Harnessing Crowds: Mapping the Genome of Collective Intelligence.” MIT Sloan Research Paper. February 3, 2009. https://bit.ly/2SPjxTP.

  • In this article, the authors describe and map the phenomenon of collective intelligence – also referred to as “radical decentralization, crowd-sourcing, wisdom of crowds, peer production, and wikinomics – which they broadly define as “groups of individuals doing things collectively that seem intelligent.”
  • The article is derived from the authors’ work at MIT’s Center for Collective Intelligence, where they gathered nearly 250 examples of Web-enabled collective intelligence. To map the building blocks or “genes” of collective intelligence, the authors used two pairs of related questions:
    • Who is performing the task? Why are they doing it?
    • What is being accomplished? How is it being done?
  • The authors concede that much work remains to be done “to identify all the different genes for collective intelligence, the conditions under which these genes are useful, and the constraints governing how they can be combined,” but they believe that their framework provides a useful start and gives managers and other institutional decisionmakers looking to take advantage of collective intelligence activities the ability to “systematically consider many possible combinations of answers to questions about Who, Why, What, and How.”

Mulgan, Geoff. “True Collective Intelligence? A Sketch of a Possible New Field.” Philosophy & Technology 27, no. 1. March 2014. http://bit.ly/1p3YSdd.

  • In this paper, Mulgan explores the concept of a collective intelligence, a “much talked about but…very underdeveloped” field.
  • With a particular focus on health knowledge, Mulgan “sets out some of the potential theoretical building blocks, suggests an experimental and research agenda, shows how it could be analysed within an organisation or business sector and points to possible intellectual barriers to progress.”
  • He concludes that the “central message that comes from observing real intelligence is that intelligence has to be for something,” and that “turning this simple insight – the stuff of so many science fiction stories – into new theories, new technologies and new applications looks set to be one of the most exciting prospects of the next few years and may help give shape to a new discipline that helps us to be collectively intelligent about our own collective intelligence.”

Sauermann, Henry and Chiara Franzoni. “Participation Dynamics in Crowd-Based Knowledge Production: The Scope and Sustainability of Interest-Based Motivation.” SSRN Working Papers Series. November 28, 2013. http://bit.ly/1o6YB7f.

  • In this paper, Sauremann and Franzoni explore the issue of interest-based motivation in crowd-based knowledge production – in particular the use of the crowd science platform Zooniverse – by drawing on “research in psychology to discuss important static and dynamic features of interest and deriv[ing] a number of research questions.”
  • The authors find that interest-based motivation is often tied to a “particular object (e.g., task, project, topic)” not based on a “general trait of the person or a general characteristic of the object.” As such, they find that “most members of the installed base of users on the platform do not sign up for multiple projects, and most of those who try out a project do not return.”
  • They conclude that “interest can be a powerful motivator of individuals’ contributions to crowd-based knowledge production…However, both the scope and sustainability of this interest appear to be rather limited for the large majority of contributors…At the same time, some individuals show a strong and more enduring interest to participate both within and across projects, and these contributors are ultimately responsible for much of what crowd science projects are able to accomplish.”

Schmitt-Sands, Catherine E. and Richard J. Smith. “Prospects for Online Crowdsourcing of Social Science Research Tasks: A Case Study Using Amazon Mechanical Turk.” SSRN Working Papers Series. January 9, 2014. http://bit.ly/1ugaYja.

  • In this paper, the authors describe an experiment involving the nascent use of Amazon’s Mechanical Turk as a social science research tool. “While researchers have used crowdsourcing to find research subjects or classify texts, [they] used Mechanical Turk to conduct a policy scan of local government websites.”
  • Schmitt-Sands and Smith found that “crowdsourcing worked well for conducting an online policy program and scan.” The microtasked workers were helpful in screening out local governments that either did not have websites or did not have the types of policies and services for which the researchers were looking. However, “if the task is complicated such that it requires ongoing supervision, then crowdsourcing is not the best solution.”

Shirky, Clay. Here Comes Everybody: The Power of Organizing Without Organizations. New York: Penguin Press, 2008. https://bit.ly/2QysNif.

  • In this book, Shirky explores our current era in which, “For the first time in history, the tools for cooperating on a global scale are not solely in the hands of governments or institutions. The spread of the Internet and mobile phones are changing how people come together and get things done.”
  • Discussing Wikipedia’s “spontaneous division of labor,” Shirky argues that the process is like, “the process is more like creating a coral reef, the sum of millions of individual actions, than creating a car. And the key to creating those individual actions is to hand as much freedom as possible to the average user.”

Silvertown, Jonathan. “A New Dawn for Citizen Science.” Trends in Ecology & Evolution 24, no. 9 (September 2009): 467–471. http://bit.ly/1iha6CR.

  • This article discusses the move from “Science for the people,” a slogan adopted by activists in the 1970s to “’Science by the people,’ which is “a more inclusive aim, and is becoming a distinctly 21st century phenomenon.”
  • Silvertown identifies three factors that are responsible for the explosion of activity in citizen science, each of which could be similarly related to the crowdsourcing of skills by governing institutions:
    • “First is the existence of easily available technical tools for disseminating information about products and gathering data from the public.
    • A second factor driving the growth of citizen science is the increasing realisation among professional scientists that the public represent a free source of labour, skills, computational power and even finance.
    • Third, citizen science is likely to benefit from the condition that research funders such as the National Science Foundation in the USA and the Natural Environment Research Council in the UK now impose upon every grantholder to undertake project-related science outreach. This is outreach as a form of public accountability.”

Szkuta, Katarzyna, Roberto Pizzicannella, David Osimo. “Collaborative approaches to public sector innovation: A scoping study.” Telecommunications Policy. 2014. http://bit.ly/1oBg9GY.

  • In this article, the authors explore cases where government collaboratively delivers online public services, with a focus on success factors and “incentives for services providers, citizens as users and public administration.”
  • The authors focus on six types of collaborative governance projects:
    • Services initiated by government built on government data;
    • Services initiated by government and making use of citizens’ data;
    • Services initiated by civil society built on open government data;
    • Collaborative e-government services; and
    • Services run by civil society and based on citizen data.
  • The cases explored “are all designed in the way that effectively harnesses the citizens’ potential. Services susceptible to collaboration are those that require computing efforts, i.e. many non-complicated tasks (e.g. citizen science projects – Zooniverse) or citizens’ free time in general (e.g. time banks). Those services also profit from unique citizens’ skills and their propensity to share their competencies.”

Can social media make every civil servant an innovator?

Curated on Posted on by Stefaan Verhulst

Steve Kelman at FCW: “Innovation, particularly in government, can be very hard. Lots of signoffs, lots of naysayers. For many, it’s probably not worth the hassle.
Yet all sorts of examples are surfacing about ways civil servants, non-profits, startups and researchers have thought to use social media — or data mining of government information — to get information that can either help citizens directly or help agencies serve citizens. I want to call attention to examples that I’ve seen just in the past few weeks — partly to recognize the creative people who have come up with these ideas, but partly to make a point about the relationship between these ideas and the general issue of innovation in government. I think that these social media and data-driven experiments are often a much simpler way for civil servants to innovate than many of the changes we typically think of under the heading “innovation in government.” They open the possibility to make innovation in government an activity for the civil service masses.
One example that was reported in The New York Times was about a pilot project at the New York City Department of Health and Mental Hygiene to do rapid keyword searches with phrases such as “vomit” and “diarrhea” associated with 294,000 Yelp restaurant reviews in New York City. The city is using a software program developed at Columbia University. They have now expended the monitoring to occur daily, to get quick information on possible problems at specific restaurants or with specific kinds of food.
A second example, reported in BloombergBusinessWeek, involved — perhaps not surprisingly, given the publication — an Israeli startup called Treato that is applying a similar idea to ferretting out adverse drug reactions before they come in through FDA studies and other systems. The founders are cooperating with researchers at Harvard Medical School and FDA officials, among others. Their software looks through Twitter and Facebook, along with a large number of patient forum sites, to cull out from all the reports of illnesses the incidents that may well reflect an unusual presence of adverse drug reactions.
These examples are fascinating in themselves. But one thing that caught my eye about both is that each seems high on the creativity dimension and low on the need-to-overcome-bureaucracy dimension. Both ideas reflect new and improved ways to do what these organizations do anyway, which is gather information to help inform regulatory and health decisions by government. Neither requires any upheaval in an agency’s existing culture, or steps on somebody’s turf in any serious way. Introducing the changes doesn’t require major changes in an agency’s internal procedures. Compared to many innovations in government, these are easy ones to make happen. (They do all need some funds, however.)
What I hope is that the information woven into social media will unlock a new era of innovation inside government. The limits of innovation are much less determined by difficult-to-change bureaucratic processes and can be much more responsive to an individual civil servant’s creativity…”