Book by Stephen Few: “In this age of so-called Big Data, organizations are scrambling to implement new software and hardware to increase the amount of data they collect and store. However, in doing so they are unwittingly making it harder to find the needles of useful information in the rapidly growing mounds of hay. If you don’t know how to differentiate signals from noise, adding more noise only makes things worse. When we rely on data for making decisions, how do we tell what qualifies as a signal and what is merely noise? In and of itself, data is neither. Assuming that data is accurate, it is merely a collection of facts. When a fact is true and useful, only then is it a signal. When it’s not, it’s noise. It’s that simple. In Signal, Stephen Few provides the straightforward, practical instruction in everyday signal detection that has been lacking until now. Using data visualization methods, he teaches how to apply statistics to gain a comprehensive understanding of one’s data and adapts the techniques of Statistical Process Control in new ways to detect not just changes in the metrics but also changes in the patterns that characterize data…(More)”
Measuring ‘governance’ to improve lives
Robert Rotberg at the Conversation: “…Citizens everywhere desire “good governance” – to be governed well within their nation-states, their provinces, their states and their cities.
Governance is more useful than “democracy” if we wish to understand how different political rulers and ruling elites satisfy the aspirations of their citizens.
But to make the notion of “governance” useful, we need both a practical definition and a method of measuring the gradations between good and bad governance.
What’s more, if we can measure well, we can diagnose weak areas of governance and, hence, seek ways to make the weak actors strong.
Governance, defined as “the performance of governments and the delivery of services by governments,” tells us if and when governments are in fact meeting the expectations of their constituents and providing for them effectively and responsibly.
Democracy outcomes, by contrast, are much harder to measure because the meaning of the very word itself is contested and impossible to measure accurately.
For the purposes of making policy decisions, if we seek to learn how citizens are faring under regime X or regime Y, we need to compare governance (not democracy) in those respective places.
In other words, governance is a construct that enables us to discern exactly whether citizens are progressing in meeting life’s goals.
Measuring governance: five bundles and 57 subcategories
Are citizens of a given country better off economically, socially and politically than they were in an earlier decade? Are their various human causes, such as being secure or being free, advancing? Are their governments treating them well, and attempting to respond to their various needs and aspirations and relieving them of anxiety?
Just comparing national gross domestic products (GDPs), life expectancies or literacy rates provides helpful distinguishing data, but governance data are more comprehensive, more telling and much more useful.
Assessing governance tells us far more about life in different developing societies than we would learn by weighing the varieties of democracy or “human development” in such places.
Government’s performance, in turn, is according to the scheme advanced in my book On Governance and in my Index of African Governance, the delivery to citizens of five bundles (divided into 57 underlying subcategories) of political goods that citizens within any kind of political jurisdiction demand.
The five major bundles are Security and Safety, Rule of Law and Transparency, Political Participation and Respect for Human Rights, Sustainable Economic Opportunity, and Human Development (education and health)….(More)”
New Technologies and Civic Engagement
Book edited by Homero Gil de Zuniga Navajas: “First, this book pays attention to the overall impact of the Internet and people’s use of digital media and new technologies to analyze civic life at large, reconceptualizing what citizenship is today. Secondly, and more specifically, participants shed light over the intersection of a number of current new agendas of research in regards to some of the most rapidly growing technological advances (i.e., new publics and citizenship), and the emergence of sprouting structures of citizenship. The volume shows the implications that new technological advances carry with respect the possibilities, patterns and mechanisms for citizen communication, citizen deliberation, public sphere and civic engagement….(More)”
Protecting Privacy in Data Release
Book by Giovanni Livraga: “This book presents a comprehensive approach to protecting sensitive information when large data collections are released by their owners. It addresses three key requirements of data privacy: the protection of data explicitly released, the protection of information not explicitly released but potentially vulnerable due to a release of other data, and the enforcement of owner-defined access restrictions to the released data. It is also the first book with a complete examination of how to enforce dynamic read and write access authorizations on released data, applicable to the emerging data outsourcing and cloud computing situations. Private companies, public organizations and final users are releasing, sharing, and disseminating their data to take reciprocal advantage of the great benefits of making their data available to others. This book weighs these benefits against the potential privacy risks. A detailed analysis of recent techniques for privacy protection in data release and case studies illustrate crucial scenarios. Protecting Privacy in Data Release targets researchers, professionals and government employees working in security and privacy. Advanced-level students in computer science and electrical engineering will also find this book useful as a secondary text or reference….(More)”
Navigating the Health Data Ecosystem
New book on O’Reilly Media on “The “Six C’s”: Understanding the Health Data Terrain in the Era of Precision Medicine”: “Data-driven technologies are now being adopted, developed, funded, and deployed throughout the health care market at an unprecedented scale. But, as this O’Reilly report reveals, health care innovation contains more hurdles and requires more finesse than many tech startups expect. By paying attention to the lessons from the report’s findings, innovation teams can better anticipate what they’ll face, and plan accordingly.
Simply put, teams looking to apply collective intelligence and “big data” platforms to health and health care problems often don’t appreciate the messy details of using and making sense of data in the heavily regulated hospital IT environment. Download this report today and learn how it helps prepare startups in six areas:
- Complexity: An enormous domain with noisy data not designed for machine consumption
- Computing: Lack of standard, interoperable schema for documenting human health in a digital format
- Context: Lack of critical contextual metadata for interpreting health data
- Culture: Startup difficulties in hospital ecosystems: why innovation can be a two-edged sword
- Contracts: Navigating the IRB, HIPAA, and EULA frameworks
- Commerce: The problem of how digital health startups get paid
This report represents the initial findings of a study funded by a grant from the Robert Wood Johnson Foundation. Subsequent reports will explore the results of three deep-dive projects the team pursued during the study. (More)”
The Art of Insight in Science and Engineering: Mastering Complexity
Book by Sanjoy Mahajan: “…shows us that the way to master complexity is through insight rather than precision. Precision can overwhelm us with information, whereas insight connects seemingly disparate pieces of information into a simple picture. Unlike computers, humans depend on insight. Based on the author’s fifteen years of teaching at MIT, Cambridge University, and Olin College, The Art of Insight in Science and Engineering shows us how to build insight and find understanding, giving readers tools to help them solve any problem in science and engineering.
To master complexity, we can organize it or discard it. The Art of Insight in Science and Engineeringfirst teaches the tools for organizing complexity, then distinguishes the two paths for discarding complexity: with and without loss of information. Questions and problems throughout the text help readers master and apply these groups of tools. Armed with this three-part toolchest, and without complicated mathematics, readers can estimate the flight range of birds and planes and the strength of chemical bonds, understand the physics of pianos and xylophones, and explain why skies are blue and sunsets are red. (Public access version of the book).
Participatory Governance
Book chapter by Stephanie L. McNulty and Brian Wample in “Emerging Trends in the Social and Behavioral Sciences: An Interdisciplinary, Searchable, and Linkable Resource”: “Efforts to engage new actors in political decision-making through innovative participatory programs have exploded around the world in the past 25 years. This trend, called participatory governance, involves state-sanctioned institutional processes that allow citizens to exercise voice and vote in public policy decisions that produce real changes in citizens’ lives. Billions of dollars are spent supporting these efforts around the world. The concept, which harks back to theorists such as Jean-Jacques Rousseau and John Stuart Mill, has only recently become prominent in theories about democracy. After presenting the foundational research on participatory governance, the essay notes that newer research on this issues falls into three areas: (i) the broader impact of these experiments; (ii) new forms of engagement, with a focus on representation, deliberation, and intermediation; and (iii) scaling up and diffusion. The essay concludes with a research agenda for future work on this topic….(More)”
Behavioural Approaches: How Nudges Lead to More Intelligent Policy Design
Paper by Peter John, Forthcoming in Contemporary Approaches to Public Policy, edited by Philippe Zittoun and B. Guy Peters : “This paper reviews the use of behavioural ideas to improve public policy. There needs to be a behavioural take on decision-making itself so that policies are designed in more effective ways. it recounts the beginnings of behavioural sciences as currently conceived and then setting out the massive expansion of interest that has come about since that time. It reports on how such ideas have had a large impact on governments at all levels across the world, but also noting how decision-making itself has been influenced by more policy-relevant ideas. The paper discusses the paradox that the very decision-makers themselves are subject to the same biases as the objects of behavioural economics, which might imply limitations in the choices of such interventions. Here the text of the chapter reengages with the classics of decision-making theory. The chapter notes how behavioural sciences need not depend on a top down approach but can incorporate citizen voice. The paper reviews how citizens and other groups can use behavioural cues to alter the behaviour of policy-makers in socially beneficial ways. The paper discusses how behaviourally informed measures could be integrated within the policy making process in ways that advance the effective use of evidence and nudge decision to make better policies….(More)“
Selected Readings on Data Governance
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)
- Better Place Lab – Privacy, Transparency and Trust – a report looking specifically at the main risks development organizations should focus on to develop a responsible data use practice.
- The Brookings Institution – Enabling Humanitarian Use of Mobile Phone Data – this paper explores ways of mitigating privacy harms involved in using call detail records for social good.
- Centre for Democracy and Technology – Health Big Data in the Commercial Context – a publication treating some of the risks involved in using new sources of health related data, and how to mitigate those risks.
- Center for Information Policy Leadership – A Risk-based Approach to Privacy: Improving Effectiveness in Practice – a whitepaper on the elements of a risk-based approach to privacy.
- Centre for Information Policy and Leadership – Data Governance for the Evolving Digital Market Place – a paper describing the necessary organizational reforms to effectively promote accountability within organizational structures.
- Crawford and Schulz – Big Data and Due Process: Toward a Framework to Redress Predictive Privacy Harm – a paper considering a rigorous ‘procedural data due process’.
- DataPop Alliance – The Ethics and Politics of Call Data Analytics – a paper exploring the risks involved in using call detail records for social good, and possible ways of mitigating those risks.
- Data for Development External Ethics Panel – Report of the External Review Panel – a report presenting the findings of the external expert panel overseeing the Data for Development Challenge.
- Federal Trade Commission – Mobile Privacy Disclosures: Building Trust Through Transparency – a report by the FTC looking at the privacy risks involved in mobile data sharing, and ways to mitigate these risks.
- Leo Mirani – How to use mobile phone data for good without invading any ones privacy – a paper on the use of data produced by mobile phone use, and the steps that need to be taken to ensure that user privacy is not intruded upon.
- Lucy Bernholz – Several Examples of Digital Ethics and Proposed Practices – a literature review listing multiple sources compiled for the Stanford Ethics of Data conference, 2014.
- Martin Abrams – A Unified Ethical Frame for Big Data Analysis – a paper from the Information Accountability Foundation on developing a unified ethical frame for data analysis that goes beyond privacy.
- NYU Centre for Urban Science and Progress – Privacy, Big Data and the Public Good – a book on the privacy issues surrounding the use of big data for promoting the public good.
- Neil M. Richards and Jonathan H. King – Big Data Ethics – a research paper arguing that the growing impact of big data on society calls for a set of ethical principles to guide big data use.
- OECD Revised Privacy Guidelines – a set of principles accompanied by explanatory text used globally to inform the governance and policy structures around data handling.
- Whitehouse Big Data and Privacy Working Group – Big Data: Seizing Opportunities, Preserving Values – a whitepaper documenting the findings of the Whitehouse big data and privacy working group.
- World Economic Forum – Pathways for Progress – a whitepaper considering the global data ecosystem and the constraints preventing data from flowing to those who need it most. A lack of well-defined and balanced governance mechanisms is considered one of the key obstacles.
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.
Ways to practice responsible development data
Responsible Data Forum Primer: “This book is offered as a first attempt to understand what responsible data means in the context of international development programming. We have taken a broad view of development, opting not to be prescriptive about who the perfect “target audience” for this effort is within the space. We also anticipate that some of the methods and lessons here may have resonance for related fields and practitioners.
We suggest a number of questions and issues to consider, but specific responsible data challenges will always be identified through individual project contexts. As such, this book is not authoritative, but is intended to support thoughtful and responsible thinking as the development community grapples with relatively new social and ethical challenges stemming from data use.
This book builds on a number of resources and strategies developed in academia, human rights and advocacy, but aims to focus on international development practitioners. As such, we touch upon issues specifically relevant to development practitioners and intermediaries working to improve the lives and livelihoods of people.
The group of contributors working on this book brings together decades of experience in the sector of international development; our first hand experiences of horrific misuse of data within the sector, combined with anecdotal stories of (mis)treatment and usage of data having catastrophic effects within some of the world’s most vulnerable communities, has highlighted for us the need for a book tackling issues of how we can all deal with data in a responsible and respectful way….(More)”