Big Data. Big Obstacles.

Curated on Posted on by Stefaan Verhulst

Dalton Conley et al. in the Chronicle of Higher Education: “After decades of fretting over declining response rates to traditional surveys (the mainstay of 20th-century social research), an exciting new era would appear to be dawning thanks to the rise of big data. Social contagion can be studied by scraping Twitter feeds; peer effects are tested on Facebook; long-term trends in inequality and mobility can be assessed by linking tax records across years and generations; social-psychology experiments can be run on Amazon’s Mechanical Turk service; and cultural change can be mapped by studying the rise and fall of specific Google search terms. In many ways there has been no better time to be a scholar in sociology, political science, economics, or related fields.

However, what should be an opportunity for social science is now threatened by a three-headed monster of privatization, amateurization, and Balkanization. A coordinated public effort is needed to overcome all of these obstacles.

While the availability of social-media data may obviate the problem of declining response rates, it introduces all sorts of problems with the level of access that researchers enjoy. Although some data can be culled from the web—Twitter feeds and Google searches—other data sit behind proprietary firewalls. And as individual users tune up their privacy settings, the typical university or independent researcher is increasingly locked out. Unlike federally funded studies, there is no mandate for Yahoo or Alibaba to make its data publicly available. The result, we fear, is a two-tiered system of research. Scientists working for or with big Internet companies will feast on humongous data sets—and even conduct experiments—and scholars who do not work in Silicon Valley (or Alley) will be left with proverbial scraps….

To address this triple threat of privatization, amateurization, and Balkanization, public social science needs to be bolstered for the 21st century. In the current political and economic climate, social scientists are not waiting for huge government investment like we saw during the Cold War. Instead, researchers have started to knit together disparate data sources by scraping, harmonizing, and geo­coding any and all information they can get their hands on.

Currently, many firms employ some well-trained social and behavioral scientists free to pursue their own research; likewise, some companies have programs by which scholars can apply to be in residence or work with their data extramurally. However, as Facebook states, its program is “by invitation only and requires an internal Facebook champion.” And while Google provides services like Ngram to the public, such limited efforts at data sharing are not enough for truly transparent and replicable science….(More)”

 

World of Labs

Curated on Posted on by Stefaan Verhulst

NESTA: “Governments across the world are creating innovation teams and labs to help them find new ways of tackling the complex challenges of the 21st century. If you want to get a sense of the scale of this global trend then check out this searchable global map of innovation labs worldwide.

There are about 80 in total represented here – colour-coded for the level of government (blue for local, green for regional, red national and yellow international). In this map I’ve concentrated on labs inside government excluding the dozens of public and social innovation labs (#psilabs) like Nesta, MaRS Solutions Lab or The GovLab that work alongside the public sector though they themselves are outside it. I’ve probably left lots of government i-teams and labs out of this list – so please suggest more and I’ll add them in.

Public innovation labs can claim to be a global movement not just in sheer numbers of teams and labs worldwide but also because of the momentum behind the creation of new ones, at a current rate of least one a month. Though some of the most celebrated examples e.g. Denmark’s MindLab are well into their second decade about a third of the labs set out here have been born in the last two years.

The early wave of scenario-based creative “future centres” (like the Netherlands-based De Werf)  was soon followed by the kind of design-based lab that continues to dominate much of the thinking and practice in the field.  But lately this has been complemented by a new wave of teams using other tools (data and technology or behavioural economics) as well as the more hybrid approach often adopted by innovation delivery teams at a municipal level, particularly in the US. At a global level the shift to a lab-based approach in development policy has been particularly marked….(More)”

Selected Readings on Data Governance

Curated on Posted on by Jos Berens

Jos Berens (Centre for Innovation, Leiden University) and Stefaan G. Verhulst (GovLab)

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 governance was originally published in 2015.

Context
The field of Data Collaboratives is premised on the idea that sharing and opening-up private sector datasets has great – and yet untapped – potential for promoting social good. At the same time, the potential of data collaboratives depends on the level of societal trust in the exchange, analysis and use of the data exchanged. Strong data governance frameworks are essential to ensure responsible data use. Without such governance regimes, the emergent data ecosystem will be hampered and the (perceived) risks will dominate the (perceived) benefits. Further, without adopting a human-centered approach to the design of data governance frameworks, including iterative prototyping and careful consideration of the experience, the responses may fail to be flexible and targeted to real needs.

Selected Readings List (in alphabetical order)

Annotated Selected Readings List (in alphabetical order)

Better Place Lab, “Privacy, Transparency and Trust.” Mozilla, 2015. Available from: http://www.betterplace-lab.org/privacy-report.

  • This report looks specifically at the risks involved in the social sector having access to datasets, and the main risks development organizations should focus on to develop a responsible data use practice.
  • Focusing on five specific countries (Brazil, China, Germany, India and Indonesia), the report displays specific country profiles, followed by a comparative analysis centering around the topics of privacy, transparency, online behavior and trust.
  • Some of the key findings mentioned are:
    • A general concern on the importance of privacy, with cultural differences influencing conception of what privacy is.
    • Cultural differences determining how transparency is perceived, and how much value is attached to achieving it.
    • To build trust, individuals need to feel a personal connection or get a personal recommendation – it is hard to build trust regarding automated processes.

Montjoye, Yves Alexandre de; Kendall, Jake and; Kerry, Cameron F. “Enabling Humanitarian Use of Mobile Phone Data.” The Brookings Institution, 2015. Available from: http://www.brookings.edu/research/papers/2014/11/12-enabling-humanitarian-use-mobile-phone-data.

  • Focussing in particular on mobile phone data, this paper explores ways of mitigating privacy harms involved in using call detail records for social good.
  • Key takeaways are the following recommendations for using data for social good:
    • Engaging companies, NGOs, researchers, privacy experts, and governments to agree on a set of best practices for new privacy-conscientious metadata sharing models.
    • Accepting that no framework for maximizing data for the public good will offer perfect protection for privacy, but there must be a balanced application of privacy concerns against the potential for social good.
    • Establishing systems and processes for recognizing trusted third-parties and systems to manage datasets, enable detailed audits, and control the use of data so as to combat the potential for data abuse and re-identification of anonymous data.
    • Simplifying the process among developing governments in regards to the collection and use of mobile phone metadata data for research and public good purposes.

Centre for Democracy and Technology, “Health Big Data in the Commercial Context.” Centre for Democracy and Technology, 2015. Available from: https://cdt.org/insight/health-big-data-in-the-commercial-context/.

  • Focusing particularly on the privacy issues related to using data generated by individuals, this paper explores the overlap in privacy questions this field has with other data uses.
  • The authors note that although the Health Insurance Portability and Accountability Act (HIPAA) has proven a successful approach in ensuring accountability for health data, most of these standards do not apply to developers of the new technologies used to collect these new data sets.
  • For non-HIPAA covered, customer facing technologies, the paper bases an alternative framework for consideration of privacy issues. The framework is based on the Fair Information Practice Principles, and three rounds of stakeholder consultations.

Center for Information Policy Leadership, “A Risk-based Approach to Privacy: Improving Effectiveness in Practice.” Centre for Information Policy Leadership, Hunton & Williams LLP, 2015. Available from: https://www.informationpolicycentre.com/uploads/5/7/1/0/57104281/white_paper_1-a_risk_based_approach_to_privacy_improving_effectiveness_in_practice.pdf.

  • This white paper is part of a project aiming to explain what is often referred to as a new, risk-based approach to privacy, and the development of a privacy risk framework and methodology.
  • With the pace of technological progress often outstripping the capabilities of privacy officers to keep up, this method aims to offer the ability to approach privacy matters in a structured way, assessing privacy implications from the perspective of possible negative impact on individuals.
  • With the intended outcomes of the project being “materials to help policy-makers and legislators to identify desired outcomes and shape rules for the future which are more effective and less burdensome”, insights from this paper might also feed into the development of innovative governance mechanisms aimed specifically at preventing individual harm.

Centre for Information Policy Leadership, “Data Governance for the Evolving Digital Market Place”, Centre for Information Policy Leadership, Hunton & Williams LLP, 2011. Available from: http://www.huntonfiles.com/files/webupload/CIPL_Centre_Accountability_Data_Governance_Paper_2011.pdf.

  • This paper argues that as a result of the proliferation of large scale data analytics, new models governing data inferred from society will shift responsibility to the side of organizations deriving and creating value from that data.
  • It is noted that, with the reality of the challenge corporations face of enabling agile and innovative data use “In exchange for increased corporate responsibility, accountability [and the governance models it mandates, ed.] allows for more flexible use of data.”
  • Proposed as a means to shift responsibility to the side of data-users, the accountability principle has been researched by a worldwide group of policymakers. Tailing the history of the accountability principle, the paper argues that it “(…) requires that companies implement programs that foster compliance with data protection principles, and be able to describe how those programs provide the required protections for individuals.”
  • The following essential elements of accountability are listed:
    • Organisation commitment to accountability and adoption of internal policies consistent with external criteria
    • Mechanisms to put privacy policies into effect, including tools, training and education
    • Systems for internal, ongoing oversight and assurance reviews and external verification
    • Transparency and mechanisms for individual participation
    • Means of remediation and external enforcement

Crawford, Kate; Schulz, Jason. “Big Data and Due Process: Toward a Framework to Redress Predictive Privacy Harm.” NYU School of Law, 2014. Available from: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2325784&download=yes.

  • Considering the privacy implications of large-scale analysis of numerous data sources, this paper proposes the implementation of a ‘procedural data due process’ mechanism to arm data subjects against potential privacy intrusions.
  • The authors acknowledge that some privacy protection structures already know similar mechanisms. However, due to the “inherent analytical assumptions and methodological biases” of big data systems, the authors argue for a more rigorous framework.

Letouze, Emmanuel, and; Vinck, Patrick. “The Ethics and Politics of Call Data Analytics”, DataPop Alliance, 2015. Available from: http://static1.squarespace.com/static/531a2b4be4b009ca7e474c05/t/54b97f82e4b0ff9569874fe9/1421442946517/WhitePaperCDRsEthicFrameworkDec10-2014Draft-2.pdf.

  • Focusing on the use of Call Detail Records (CDRs) for social good in development contexts, this whitepaper explores both the potential of these datasets – in part by detailing recent successful efforts in the space – and political and ethical constraints to their use.
  • Drawing from the Menlo Report Ethical Principles Guiding ICT Research, the paper explores how these principles might be unpacked to inform an ethics framework for the analysis of CDRs.

Data for Development External Ethics Panel, “Report of the External Ethics Review Panel.” Orange, 2015. Available from: http://www.d4d.orange.com/fr/content/download/43823/426571/version/2/file/D4D_Challenge_DEEP_Report_IBE.pdf.

  • This report presents the findings of the external expert panel overseeing the Orange Data for Development Challenge.
  • Several types of issues faced by the panel are described, along with the various ways in which the panel dealt with those issues.

Federal Trade Commission Staff Report, “Mobile Privacy Disclosures: Building Trust Through Transparency.” Federal Trade Commission, 2013. Available from: www.ftc.gov/os/2013/02/130201mobileprivacyreport.pdf.

  • This report looks at ways to address privacy concerns regarding mobile phone data use. Specific advise is provided for the following actors:
    • Platforms, or operating systems providers
    • App developers
    • Advertising networks and other third parties
    • App developer trade associations, along with academics, usability experts and privacy researchers

Mirani, Leo. “How to use mobile phone data for good without invading anyone’s privacy.” Quartz, 2015. Available from: http://qz.com/398257/how-to-use-mobile-phone-data-for-good-without-invading-anyones-privacy/.

  • This paper considers the privacy implications of using call detail records for social good, and ways to mitigate risks of privacy intrusion.
  • Taking example of the Orange D4D challenge and the anonymization strategy that was employed there, the paper describes how classic ‘anonymization’ is often not enough. The paper then lists further measures that can be taken to ensure adequate privacy protection.

Bernholz, Lucy. “Several Examples of Digital Ethics and Proposed Practices” Stanford Ethics of Data conference, 2014, Available from: http://www.scribd.com/doc/237527226/Several-Examples-of-Digital-Ethics-and-Proposed-Practices.

  • This list of readings prepared for Stanford’s Ethics of Data conference lists some of the leading available literature regarding ethical data use.

Abrams, Martin. “A Unified Ethical Frame for Big Data Analysis.” The Information Accountability Foundation, 2014. Available from: http://www.privacyconference2014.org/media/17388/Plenary5-Martin-Abrams-Ethics-Fundamental-Rights-and-BigData.pdf.

  • Going beyond privacy, this paper discusses the following elements as central to developing a broad framework for data analysis:
    • Beneficial
    • Progressive
    • Sustainable
    • Respectful
    • Fair

Lane, Julia; Stodden, Victoria; Bender, Stefan, and; Nissenbaum, Helen, “Privacy, Big Data and the Public Good”, Cambridge University Press, 2014. Available from: http://www.dataprivacybook.org.

  • This book treats the privacy issues surrounding the use of big data for promoting the public good.
  • The questions being asked include the following:
    • What are the ethical and legal requirements for scientists and government officials seeking to serve the public good without harming individual citizens?
    • What are the rules of engagement?
    • What are the best ways to provide access while protecting confidentiality?
    • Are there reasonable mechanisms to compensate citizens for privacy loss?

Richards, Neil M, and; King, Jonathan H. “Big Data Ethics”. Wake Forest Law Review, 2014. Available from: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2384174.

  • This paper describes the growing impact of big data analytics on society, and argues that because of this impact, a set of ethical principles to guide data use is called for.
  • The four proposed themes are: privacy, confidentiality, transparency and identity.
  • Finally, the paper discusses how big data can be integrated into society, going into multiple facets of this integration, including the law, roles of institutions and ethical principles.

OECD, “OECD Guidelines on the Protection of Privacy and Transborder Flows of Personal Data”. Available from: http://www.oecd.org/sti/ieconomy/oecdguidelinesontheprotectionofprivacyandtransborderflowsofpersonaldata.htm.

  • A globally used set of principles to inform thought about handling personal data, the OECD privacy guidelines serve as one the leading standards for informing privacy policies and data governance structures.
  • The basic principles of national application are the following:
    • Collection Limitation Principle
    • Data Quality Principle
    • Purpose Specification Principle
    • Use Limitation Principle
    • Security Safeguards Principle
    • Openness Principle
    • Individual Participation Principle
    • Accountability Principle

The White House Big Data and Privacy Working Group, “Big Data: Seizing Opportunities, Preserving Values”, White House, 2015. Available from: https://www.whitehouse.gov/sites/default/files/docs/big_data_privacy_report_5.1.14_final_print.pdf.

  • Documenting the findings of the White House big data and privacy working group, this report lists i.a. the following key recommendations regarding data governance:
    • Bringing greater transparency to the data services industry
    • Stimulating international conversation on big data, with multiple stakeholders
    • With regard to educational data: ensuring data is used for the purpose it is collected for
    • Paying attention to the potential for big data to facilitate discrimination, and expanding technical understanding to stop discrimination

William Hoffman, “Pathways for Progress” World Economic Forum, 2015. Available from: http://www3.weforum.org/docs/WEFUSA_DataDrivenDevelopment_Report2015.pdf.

  • This paper treats i.a. the lack of well-defined and balanced governance mechanisms as one of the key obstacles preventing particularly corporate sector data from being shared in a controlled space.
  • An approach that balances the benefits against the risks of large scale data usage in a development context, building trust among all stake holders in the data ecosystem, is viewed as key.
  • Furthermore, this whitepaper notes that new governance models are required not just by the growing amount of data and analytical capacity, and more refined methods for analysis. The current “super-structure” of information flows between institutions is also seen as one of the key reasons to develop alternatives to the current – outdated – approaches to data governance.

Launching the Police Data Initiative

Curated on Posted on by Stefaan Verhulst

Megan Smith and Roy L. Austin, Jr.at the White House: “Last December, President Obama launched the Task Force on 21st Century Policing to better understand specific policing challenges and help communities identify actions they can take to improve law enforcement and enhance community engagement. Since that time, we have seen law enforcement agencies around the country working harder than ever to make the promise of community policing real.

Many of the Task Force’s recommendations emphasize the opportunity for departments to better use data and technology to build community trust. As a response, the White House has launched the Police Data Initiative, which has mobilized 21 leading jurisdictions across the country to take fast action on concrete deliverables responding to these Task Force recommendations in the area of data and technology. Camden is one such jurisdiction.

By finding innovative work already underway in these diverse communities and bringing their leaders together with top technologists, researchers, data scientists and design experts, the Police Data Initiative is helping accelerate progress around data transparency and analysis, toward the goal of increased trust and impact. Through the Initiative, key stakeholders are establishing a community of practice that will allow for knowledge sharing, community-sourced problem solving, and the establishment of documented best practices that can serve as examples for police departments nationwide….

Commitment highlights include:

1. Use open data to build transparency and increase community trust.

  • All 21 police departments have committed to release a combined total of 101 data sets that have not been released to the public. The types of data include uses of force, police pedestrian and vehicle stops, officer involved shootings and more, helping the communities gain visibility into key information on police/citizen encounters.
    • Code for America and others are helping on this. For information on how Police Departments can jumpstart their open police data efforts, click here.
  • To make police open data easy to find and use, the Police Foundation and ESRI are building a public safety open data portal to serve, in part, as a central clearinghouse option for police open data, making it easily accessible to law enforcement agencies, community groups and researchers.
  • Code for America and CI Technologies will work together to build an open source software tool to make it easier for the 500+ U.S. law enforcement agencies using IA Pro police integrity software to extract and open up data.
  • To make it easier for agencies to share data with the public about policing, Socrata will provide technical assistance to cities and agencies who are working toward increased transparency.
  • To help this newly released data come alive for communities through mapping, visualizations and other tools, city leaders, non-profit organizations, and private sector partners will host open data hackathons in cities around the country. In New Orleans, Operation Spark, a non-profit organization that teaches at-risk New Orleans youth software development skills, will work with data opened by the New Orleans Police Department at a weeklong code academy.
  • Presidential Innovation Fellows working with the U.S. Chief Technology Officer and Chief Data Scientist will work collaboratively with key stakeholders, such as Code for America and the Sunlight Foundation, to develop and release an Open Data Playbook for police departments that they can use as a reference for open data best practices and case studies.
  • The Charlotte-Mecklenburg Police Department is working with the Southern Coalition for Social Justice to use open data to provide a full picture of key policing activities, including stops, searches and use-of-force trends, information and demographics on neighborhoods patrolled, and more. This partnership will build on a website and tools already developed by the Southern Coalition for Justice which provide visualization and search functions to make this data easily accessible and understandable.
  • The International Association of Chiefs of Police, the Police Foundation, and Code for America have committed to helping grow a community of practice for law enforcement agencies and technologists around open data and transparency in police community interactions.

2. Internal accountability and effective data analysis.

  • While many police departments have systems in place, often called “early warning systems,” to identify officers who may be having challenges in their interactions with the public and link them with training and other assistance, there has been little to no research to determine which indicators are most closely linked to bad outcomes. To tackle this issue, twelve police departments committed to sharing data on police/citizen encounters with data scientists for in-depth data analysis, strengthening the ability of police to intervene early and effectively: Austin, TX; Camden, NJ; Charlotte, NC; Dallas, TX; Indianapolis, IN; Knoxville, TN; LA City; LA County; Louisville, KY; New Orleans, LA; Philadelphia, PA; and Richmond, CA….(More)

From Paint to Pixels

Curated on Posted on by Stefaan Verhulst

Jacoba Urist at the Atlantic: “A growing number of artists are using data from self-tracking apps in their pieces, showing that creative work is as much a product of its technology as of its time….A growing community of “data artists” is creating conceptual works using information collected by mobile apps, GPS trackers, scientists, and more.

Data artists generally fall into two groups: those who work with large bodies of scientific data and those who are influenced by self-tracking. The Boston-based artist Nathalie Miebach falls into the former category: She transforms weather patterns into complex sculptures and musical scores. Similarly, David McCandless, who believes the world suffers from a “data glut,” turns military spending budgets into simple, striking diagrams. On one level, the genre aims to translate large amounts of information into some kind of aesthetic form. But a number of artists, scholars, and curators also believe that working with this data isn’t just a matter of reducing human beings to numbers, but also of achieving greater awareness of complex matters in a modern world….

Current tools make self-tracking more efficient than ever, but data artists are hardly the first to express themselves through their daily activities—or to try to find meaning within life’s monotony. The Italian Mannerist painter Jacopo Pontormo kept records of his daily life from January 1554 to October 1556. In it, he detailed the amount of food he ate, the weather, symptoms of illness, friends he visited, even his bowel movements. In the 1970s, the Japanese conceptualistOn Kawara produced his self-observation series, I Got Up, I Went, and I Met(recently shown at the Guggenheim), in which he painstakingly records the rhythms of his day. Kawara stamped postcards with the time he awoke, traced his daily trips onto photocopied maps, and listed the names of people he encountered for nearly 12 years….(More)

Designing digital democracy: a short guide

Curated on Posted on by Stefaan Verhulst

Geoff Mulgan at NESTA: “I’ve written quite a few blogs and pieces on digital technology and democracy – most recently on the relevance of new-style political parties.

Here I look at the practical question of how parliaments, assemblies and governments should choose the right methods for greater public engagement in decisions.

One prompt is the Nesta-led D-CENT project which is testing out new tools in several countries, and there’s an extraordinary range of engagement experiments underway around the world, from Brazil’s parliament to the Mayor of Paris. Tools like Loomio for smallish groups, and Your Priorities and DemocracyOS for larger ones, are well ahead of their equivalents a few years ago.

A crucial question is whether the same tools work well for different types of issue or context. The short answer is ‘no’. Here I suggest some simple formulae to ensure that the right tools are used for the right issues; I show why hybrid forms of online and offline are the future for parliaments and parties; and why the new tools emphasise conversation rather than only votes.

Clarity on purpose

First, it’s important to be clear what wider engagement is for. Engagement is rarely a good in itself. More passionate engagement in issues can be a powerful force for progress. But it can be the opposite, entrenching conflicts and generating heat rather than light….

Clarity on who you want to reach

Second, who do you want to reach? Even in the most developed nations and cities there are still very practical barriers of reach – despite the huge spread of broadband, mobiles and smart phones…..

Clarity on what tools for what issues – navigating ‘Belief and Knowledge Space’

Third, even if there were strong habits of digital engagement for the whole population it would not follow that all issues should be opened up for the maximum direct participation. A useful approach is to distinguish issues according to two dimensions.

The first dimension differentiates issues where the public has expertise and experience from ones where the knowledge needed to make decisions is very specialised. There are many issues on which crowds simply don’t have much information let alone wisdom, and any political leader who opened up decision making too far would quickly lose the confidence of the public.

The second dimension differentiates issues which are practical and pragmatic from ones where there are strongly held and polarised opinions, mainly determined by underlying moral beliefs rather than argument and evidence. Putting these together gives us a two dimensional space on which to map any public policy issue, which could be described as the ‘Belief and Knowledge Space’…..

 

Clarity on requisite scale

Fourth, engagement looks and feels very different at different scales. …

Clarity on identity and anonymity

…. So any designer of democratic engagement tools has to decide what levels of anonymity should apply at each stage. We might choose to allow anonymity at early stages of consultations, but require people to show and validate identities at later stages (eg. to confirm they actually live in the neighbourhood or city involved), certainly as any issue comes closer to decisions. The diagram below summarises these different steps, and the block chain tools being used in the D-CENT pilots bring these issues to the fore.

The 2010s are turning out to be a golden age of democratic innovation. That’s bringing creativity and excitement but also challenges, in particular around how to relate the new forms to the old ones, online communities to offline ones, the democracy of voice and numbers and the democracy of formal representation….(More)

How to Get People to Pitch In

Curated on Posted on by Stefaan Verhulst

Erez Yoeli, Syon Bhanot, Gordon Kraft-Todd And David Rand in The New York Times: “…The “Pigouvian” approach to encouraging cooperation, named after the economist who first suggested it nearly a century ago, is to change the price — i.e., the personal cost of cooperating: Make water more expensive, tax carbon or pay people to vaccinate their kids.

But Californians are stubbornly unresponsive to higher water prices. Estimates suggest that a 10 percent increase in price would result in reductions in water use of 2 to 4 percent. That’s not nothing, but it implies that huge, politically infeasible price increases would be needed to address the state’s needs.

This problem isn’t unique to Californians and their effort to save water. In a recent review of field experiments that promote cooperation in the journal Current Opinion in Behavioral Sciences, we found that changing the material costs and benefits of cooperation often doesn’t work. Researchers have tried various forms of payments — paying cash, handing out T-shirts — and they’ve tried providing information on how to cooperate, with only limited success.

What does consistently work may be surprising: interventions based not on money, but on leveraging social concerns.

There are two ways to do this, both building on people’s desire for others to think highly of them. One is to make people’s cooperative (or selfish) choices more observable to others, like neighbors or co-workers. The second works in the opposite direction, providing people with information about how others around them are behaving (this is called a “descriptive social norm”).

To see how this might work, consider the California drought. The state could set up a website where homeowners pledge publicly to reduce their water consumption by 15 percent. Those who do would get a lawn sign that would say something like, “My lawn is yellow because I took a pledge to help California. Join me at yellowlawns.ca.gov.”

And what about norms? Innovative companies and public utilities are already on the case. A San Francisco-based firm, WaterSmart Software, sends mailers that allow homeowners to compare their water use to their neighbors’. Estimates suggest that these mailers reduce water use by 2 to 5 percent — the same as a 10 percent price increase.

Why do social interventions work? Research on the evolution of cooperation provides an answer. Beyond helping our families — the people to whom we’re genetically related — making others better off is not our main motivation to give. Instead, we cooperate because it makes us look good. This can be going on consciously or, more often, subconsciously (a gut feeling of guilt when your neighbor sees you turning on your sprinkler).

When your choices are observable by others, it makes it possible for good actions to benefit your reputation. Similarly, norms make you feel you’re expected to cooperate in a given situation, and that people may think poorly of you if they learn you are not doing your part….(More)”

Detroit Revitalizes City with 311 App

Curated on Posted on by Stefaan Verhulst

Jason Shueh at Government Technology: “In the wake of the Detroit bankruptcy, blight sieged parts of the city as its populous exited. The fallouts were typical. There was a run of vandalism, thefts, arson and graffiti. Hard times pushed throngs of looters into scores of homes to scavenge for anything that wasn’t bolted down — and often, even for the things that were…. For solutions, Detroit Mayor Mike Duggan and DWSD’s CIO Dan Rainey partnered with SeeClickFix. The company, based in New Haven, Conn., is known for its mobile platform that’s embedded itself as a conduit between city service departments and citizen non-emergency — or 311 — requests. Duggan saw the platform as an opportune answer to address more than a single issue. Instead, the mayor asked how the app could be integrated throughout the city. Potholes, downed trees, graffiti, missing signage, streetlight outages — the mayor wanted a bundled solution to handle an array of common challenges.

Improve Detroit was his answer. The city app, officially available since April, allows citizens to report problems using photos, location data and by request type. Notifications on progress follow and residents can even pay utility bills through the app. For departments, it’s ingrained into work orders and workflows, while analytics provide data for planning, and filters permit a deep-dive analysis….

improve detroit app

Detroit now sits among many metropolitan cities pioneering such 311 apps. San Francisco, New York, Los Angeles, Philadelphia and Chicago are just a few of them. And there are a host of equally adroit tech providers supplying and supporting the apps — companies like Salesforce, CitySourced, PublicStuff, Fix 311 and others. Some cities have even developed their own apps through their internal IT departments.

What’s unique in Detroit is the city’s ambition to leverage a 311 app against major blight while the city works to demolish more than 20,000 abandoned homes — susceptible to fire, flooding, pest infestations and criminal activity. Beyond this, Lingholm said the initiative doubles as a tool to rejuvenate public trust. Data from the app is fed to the city’s new open data portal, and departments have set goals to ensure responsiveness….(More)

Crowdsourced website flags up sexism in the workplace

Curated on Posted on by Stefaan Verhulst

Springwise: “Female jobseekers can now review the treatment of women in their potential workplace via an online platform called InHerSight. The website collates anonymous reviews from former and current employees — both male and female — so that women can find out more about the company’s policies, office culture and other potential issues before applying for or accepting a job there.

A recent survey by Cosmopolitan magazine found that one in three women are sexually harassed at work and InHerSight enables those women to communicate misconduct and other problematic corporate policies. Importantly, they can do so without fear of recrimination or consequence, since the scorecards are entirely anonymous. Users can complete surveys about their experience at any given company — either adding to an existing score or creating a new profile — by scoring them on 14 categories including their stance on maternity leave, flexible work hours and female representation in top positions. They can also leave a written review of the company. The crowdsourced data is then used to create comprehensive scorecards for other users to view.

Founder Ursula Mead envisions the site as a TripAdvisor for women in the workplace and hopes that by holding companies accountable for their support for women, it will encourage them to review and improve their treatment….(More)”

What Is Community Anyway?

Curated on Posted on by Stefaan Verhulst

David M. Chavis & Kien Lee at Stanford Social Innovation Review: “Community” is so easy to say. The word itself connects us with each other. It describes an experience so common that we never really take time to explain it. It seems so simple, so natural, and so human. In the social sector, we often add it to the names of social innovations as a symbol of good intentions (for example, community mental health, community policing, community-based philanthropy, community economic development).

But the meaning of community is complex. And, unfortunately, insufficient understanding of what a community is and its role in the lives of people in diverse societies has led to the downfall of many well-intended “community” efforts.

Adding precision to our understanding of community can help funders and evaluators identify, understand, and strengthen the communities they work with. There has been a great deal of research in the social sciences about what a human community is (see for example, Chavis and Wandersman, 1990; Nesbit, 1953; Putnam, 2000). Here, we blend that research with our experience as evaluators and implementers of community change initiatives.

It’s about people.

First and foremost, community is not a place, a building, or an organization; nor is it an exchange of information over the Internet. Community is both a feeling and a set of relationships among people. People form and maintain communities to meet common needs….

People live in multiple communities.

Since meeting common needs is the driving force behind the formation of communities, most people identify and participate in several of them, often based on neighborhood, nation, faith, politics, race or ethnicity, age, gender, hobby, or sexual orientation….

Communities are nested within each other.

Just like Russian Matryoshka dolls, communities often sit within other communities. For example, in a neighborhood—a community in and of itself—there may be ethnic or racial communities, communities based on people of different ages and with different needs, and communities based on common economic interests….

Communities have formal and informal institutions.

Communities form institutions—what we usually think of as large organizations and systems such as schools, government, faith, law enforcement, or the nonprofit sector—to more effectively fulfill their needs….

Communities are organized in different ways.

Every community is organized to meet its members’ needs, but they operate differently based on the cultures, religions, and other experiences of their members. For example, while the African American church is generally understood as playing an important role in promoting health education and social justice for that community, not all faith institutions such as the mosque or Buddhist temple are organized and operate in the same way….(More)