What we see when we see transparency


Matthew Taylor at the RSA: “…social coordination theory…. is one of the most powerful ways to analyse complex social problems and to develop effective solutions. I spoke this morning to the Transparency Task Force and it gave me an opportunity to apply the theory to the issue of corporate openness.

First, a very brief recap of the theory:

My own approach focusses on the four modes as approaches to the challenge of social coordination. Human beings are complex social beings who have to work together to survive and flourish. The hierarchical perspective puts emphasis on leadership, strategy and expertise as the way to coordinate human activity. The solidaristic view emphasises the glue of belonging and shared values. The individualistic view sees coordination as emerging largely spontaneously and its goal being to provide a platform of individual ambition and competitive endeavour. The fatalistic view sees effective coordination, variously, as intractable, unlikely to deliver intended outcomes or irrelevant to the things that make it hardest to be human.

Each mode has a substrate in human evolution and psychology – these competing theories have emerged from who we are as a species. Each mode or combination of modes has been dominant at different times in our history. Also, each mode generates behavioural and ideological predispositions: Solidaristic views – which emphasise membership and values – are often associated with rigid ideologies (on both the left and right); individualism goes with liberal attitudes (again of both left and right varieties).

In a kind of fractal which stretches from individual preferences to global problem solving, each mode is available as a perspective on complex social problems. Crucially, for the kind of problems which the modern world increasingly generates, the best solutions will combine aspects of each method. But there is a problem: each mode is, in part, a critique of the others. Each has both benign and malign aspects; hierarchy can be strategic and overbearing, individualism can be enterprising and selfish, solidarity can be altruistic and tribal, fatalism can be stoical and defeatist. The theory explains why success can so quickly turn to failure. Even when the modes are successfully combined – what I call a ‘fully engaged’ solution – internal dynamics or external shocks will sooner or later upset the balance.

This is all rather theoretical so let me be more concrete. If we are trying to solve a problem like encouraging and enabling a corporation to be more transparent we need to understand the arguments both in favour and against such a move from each of the perspectives. If we don’t many people, many ideas and many approaches will be ignored. In short, we will be much more likely to fail.

Here is a simple guide to what might be seen as the pros and cons of greater transparency from the four standpoints:

perspectives on transparency Matthew Taylor

People in authority and those who see things from a hierarchical perspective (we all see things from different perspectives at different times and in different places) will worry that transparency will make decision making more difficult and that, by opening up things like the underlying business model to scrutiny by customers and competitors, it would threaten the interests of the organisation. Conversely, the hierarchical case for transparency is that it can increase trust and understanding towards leaders and the challenges they face and it can aid alignment, clarity and commitment by exposing practices that don’t fit with corporate strategy.

Those who approach things from a solidaristic perspective are often the most outspoken champions of transparency. They see it as increasing integrity as companies have to live up to their stated values and fairness as unfair practices are exposed.  However, there are also solidaristic concerns; what if transparency exposes vulnerable people or if transparency makes life harder for the team to which I belong (the company or my part of the company)?

From an individualistic starting point transparency can be viewed suspiciously as promoting a focus on process rather than outcomes and also being adverse to risk and reward (you can justify the means by the ends only if you have been able to achieve the ends without someone looking over your shoulder). On the other hand, the individualistic case for transparency can cite its contribution to innovation (by looking under the bonnet and seeing all the working parts we have better insights into what can be improved) and the promotion of rewards based on fair competition instead of covert rent-seeking or organisational nepotism.

Finally, those in a fatalistic mind set will tend to see transparency as either irrelevant or – and this is a more forensic critique – illusory (the secret stuff will just get hidden better). However there is also an appeal to be made to fatalists that transparency can help reveal warning signs of future dangers and make it easier to mount a defence when things go wrong (‘even if we failed, we can show that we tried’).

To win the case for transparency and also to implement it effectively its advocates need to stress the positives from the different perspectives and also address the legitimate concerns; both of which should make it easier to confront objections that are not reasonable. …(More)”

Living in the World of Both/And


Essay by Adene Sacks & Heather McLeod Grant  in SSIR: “In 2011, New York Times data scientist Jake Porway wrote a blog post lamenting the fact that most data scientists spend their days creating apps to help users find restaurants, TV shows, or parking spots, rather than addressing complicated social issues like helping identify which teens are at risk of suicide or creating a poverty index of Africa using satellite data.

That post hit a nerve. Data scientists around the world began clamoring for opportunities to “do good with data.” Porway—at the center of this storm—began to convene these scientists and connect them to nonprofits via hackathon-style events called DataDives, designed to solve big social and environmental problems. There was so much interest, he eventually quit his day job at the Times and created the organization DataKind to steward this growing global network of data science do-gooders.

At the same time, in the same city, another movement was taking shape—#GivingTuesday, an annual global giving event fueled by social media. In just five years, #GivingTuesday has reshaped how nonprofits think about fundraising and how donors give. And yet, many don’t know that 92nd Street Y (92Y)—a 140-year-old Jewish community and cultural center in Manhattan, better known for its star-studded speaker series, summer camps, and water aerobics classes—launched it.

What do these two examples have in common? One started as a loose global network that engaged data scientists in solving problems, and then became an organization to help support the larger movement. The other started with a legacy organization, based at a single site, and catalyzed a global movement that has reshaped how we think about philanthropy. In both cases, the founding groups have incorporated the best of both organizations and networks.

Much has been written about the virtues of thinking and acting collectively to solve seemingly intractable challenges. Nonprofit leaders are being implored to put mission above brand, build networks not just programs, and prioritize collaboration over individual interests. And yet, these strategies are often in direct contradiction to the conventional wisdom of organization-building: differentiating your brand, developing unique expertise, and growing a loyal donor base.

A similar tension is emerging among network and movement leaders. These leaders spend their days steering the messy process required to connect, align, and channel the collective efforts of diverse stakeholders. It’s not always easy: Those searching to sustain movements often cite the lost momentum of the Occupy movement as a cautionary note. Increasingly, network leaders are looking at how to adapt the process, structure, and operational expertise more traditionally associated with organizations to their needs—but without co-opting or diminishing the energy and momentum of their self-organizing networks…

Welcome to the World of “Both/And”

Today’s social change leaders—be they from business, government, or nonprofits—must learn to straddle the leadership mindsets and practices of both networks and organizations, and know when to use which approach. Leaders like Porway, and Henry Timms and Asha Curran of 92Y can help show us the way.

How do these leaders work with the “both/and” mindset?

First, they understand and leverage the strengths of both organizations and networks—and anticipate their limitations. As Timms describes it, leaders need to be “bilingual” and embrace what he has called “new power.” Networks can be powerful generators of new talent or innovation around complex multi-sector challenges. It’s useful to take a network approach when innovating new ideas, mobilizing and engaging others in the work, or wanting to expand reach and scale quickly. However, networks can dissipate easily without specific “handrails,” or some structure to guide and support their work. This is where they need some help from the organizational mindset and approach.

On the flip side, organizations are good at creating centralized structures to deliver products or services, manage risk, oversee quality control, and coordinate concrete functions like communications or fundraising. However, often that efficiency and effectiveness can calcify over time, becoming a barrier to new ideas and growth opportunities. When organizational boundaries are too rigid, it is difficult to engage the outside world in ideating or mobilizing on an issue. This is when organizations need an infusion of the “network mindset.”

 

…(More)

Responsible Data in Agriculture


Report by Lindsay Ferris and Zara Rahman for GODAN: “The agriculture sector is creating increasing amounts of data, from many different sources. From tractors equipped with GPS tracking, to open data released by government ministries, data is becoming ever more valuable, as agricultural business development and global food policy decisions are being made based upon data. But the sector is also home to severe resource inequality. The largest agricultural companies make billions of dollars per year, in comparison with subsistence farmers growing just enough to feed themselves, or smallholder farmers who grow enough to sell on a year-by-year basis. When it comes to data and technology, these differences in resources translate to stark power imbalances in data access and use. The most well resourced actors are able to delve into new technologies and make the most of those insights, whereas others are unable to take any such risks or divert any of their limited resources. Access to and use of data has radically changed the business models and behaviour of some of those well resourced actors, but in contrast, those with fewer resources are receiving the same, limited access to information that they always have.

In this paper, we have approached these issues from a responsible data perspective, drawing upon the experience of the Responsible Data community1 who over the past three years have created tools, questions and resources to deal with the ethical, legal, privacy and security challenges that come from new uses of data in various sectors. This piece aims to provide a broad overview of some of the responsible data challenges facing these actors, with a focus on the power imbalance between actors, and looking into how that inequality affects behaviour when it comes to the agricultural data ecosystem. What are the concerns of those with limited resources, when it comes to this new and rapidly changing data environment? In addition, what are the ethical grey areas or uncertainties that we need to address in the future? As a first attempt to answer these questions, we spoke to 14 individuals with various perspectives on the sector to understand what the challenges are for them and for the people they work with. We also carried out desk research to dive deeper into these issues, and we provide here an analysis of our findings and responsible data challenges….(More)”

The government technology pitch


 at TechCrunch: “Crisis has a history of dictating government technology disruption. We’ve seen this with the anticipation of Soviet Union aerospace and military dominance that sparked the emergence of DARPA, as well as with the response to 9/11 and subsequent establishment of the U.S. Department of Homeland Security.

And, of course, there’s the ongoing, seemingly invisible crisis around security that’s expediting an infusion of public sector funding, particularly in the wake of the U.S. Office of Personnel Management breach that exposed the personal records of millions of federal employees and government contractors.

The Healthcare.gov launch debacle is the most recent and referenced example of crisis spawning government technology progress. The federal government woke to the issues surrounding outdated digital practices — from procurement to technical — and quickly launched two startups of its own: 18F and the U.S. Digital Service (USDS).

The failings of Healthcare.gov and subsequent creation of 18F and USDS has inspired others — such as the state of California, large cities and local governments — to fund a surge in attention to digital — from web to data to security — to address outdated technologies powering the technological infrastructure that runs our governments.

But innovators don’t wait for crises.

They imagine a different path, whether it’s a new approach to solving an old problem or a moonshot that leapfrogs business as usual. They observe the world, realize potential and fund and build engines of change — and forward-thinking, optimistic entrepreneurs and investors are starting to do this with government technology….(More)”

How to advance open data research: Towards an understanding of demand, users, and key data


Danny Lämmerhirt and Stefaan Verhulst at IODC blog: “…Lord Kelvin’s famous quote “If you can not measure it, you can not improve it” equally applies to open data. Without more evidence of how open data contributes to meeting users’ needs and addressing societal challenges, efforts and policies toward releasing and using more data may be misinformed and based upon untested assumptions.

When done well, assessments, metrics, and audits can guide both (local) data providers and users to understand, reflect upon, and change how open data is designed. What we measure and how we measure is therefore decisive to advance open data.

Back in 2014, the Web Foundation and the GovLab at NYU brought together open data assessment experts from Open Knowledge, Organisation for Economic Co-operation and Development, United Nations, Canada’s International Development Research Centre, and elsewhere to explore the development of common methods and frameworks for the study of open data. It resulted in a draft template or framework for measuring open data. Despite the increased awareness for more evidence-based open data approaches, since 2014 open data assessment methods have only advanced slowly. At the same time, governments publish more of their data openly, and more civil society groups, civil servants, and entrepreneurs employ open data to manifold ends: the broader public may detect environmental issues and advocate for policy changes, neighbourhood projects employ data to enable marginalized communities to participate in urban planning, public institutions may enhance their information exchange, and entrepreneurs embed open data in new business models.

In 2015, the International Open Data Conference roadmap made the following recommendations on how to improve the way we assess and measure open data.

  1. Reviewing and refining the Common Assessment Methods for Open Data framework. This framework lays out four areas of inquiry: context of open data, the data published, use practices and users, as well as the impact of opening data.
  2. Developing a catalogue of assessment methods to monitor progress against the International Open Data Charter (based on the Common Assessment Methods for Open Data).
  3. Networking researchers to exchange common methods and metrics. This helps to build methodologies that are reproducible and increase credibility and impact of research.
  4. Developing sectoral assessments.

In short, the IODC called for refining our assessment criteria and metrics by connecting researchers, and applying the assessments to specific areas. It is hard to tell how much progress has been made in answering these recommendations, but there is a sense among researchers and practitioners that the first two goals are yet to be fully addressed.

Instead we have seen various disparate, yet well meaning, efforts to enhance the understanding of the release and impact of open data. A working group was created to measure progress on the International Open Data Charter, which provides governments with principles for implementing open data policies. While this working group compiled a list of studies and their methodologies, it did not (yet) deepen the common framework of definitions and criteria to assess and measure the implementation of the Charter.

In addition, there is an increase of sector- and case-specific studies that are often more descriptive and context specific in nature, yet do contribute to the need for examples that illustrate the value proposition for open data.

As such, there seems to be a disconnect between top-level frameworks and on-the-ground research, preventing the sharing of common methods and distilling replicable experiences about what works and what does not….(More)”

Research Handbook on Digital Transformations


Book edited by F. Xavier Olleros and Majlinda Zhegu: “The digital transition of the world economy is now entering a phase of broad and deep societal impact. While there is one overall transition, there are many different sectoral transformations, from health and legal services to tax reports and taxi rides, as well as a rising number of transversal trends and policy issues, from widespread precarious employment and privacy concerns to market monopoly and cybercrime. This Research Handbook offers a rich and interdisciplinary synthesis of some of the recent research on the digital transformations currently under way.

This comprehensive study contains chapters covering sectoral and transversal analyses, all of which are specially commissioned and include cutting-edge research. The contributions featured are global, spanning four continents and seven different countries, as well as interdisciplinary, including experts in economics, sociology, law, finance, urban planning and innovation management. The digital transformations discussed are fertile ground for researchers, as established laws and regulations, organizational structures, business models, value networks and workflow routines are contested and displaced by newer alternatives….(More)”

What is being done with open government data?


An exploratory analysis of public uses of New York City open data by Karen Okamoto in Webology: “In 2012, New York City Council passed legislation to make government data open and freely available to the public. By approving this legislation, City Council was attempting to make local government more transparent, accountable, and streamlined in its operations. It was also attempting to create economic opportunities and to encourage the public to identify ways in which to improve government and local communities. The purpose of this study is to explore public uses of New York City open data. Currently, more than 1300 datasets covering broad areas such as health, education, transportation, public safety, housing and business are available on the City’s Open Data Portal. This study found a plethora of maps, visualizations, tools, apps and analyses made by the public using New York City open data. Indeed, open data is inspiring a productive range of creative reuses yet questions remain concerning how useable the data is for users without technical skills and resources….(More)”

Can Direct Democracy Be Revived Through New Voting Apps?


Adele Peters at FastCo-Exist: “…a new app and proposed political party called MiVote—aims to rethink how citizens participate in governance. Instead of voting only in elections, people using the app can share their views on every issue the government considers. The idea is that parliamentary representatives of the “MiVote party” would commit to support legislation only when it’s in line with the will of the app’s members—regardless of the representative’s own opinion….

Like Democracy Earth, a nonprofit that started in Argentina, MiVote uses the blockchain to make digital voting and identity fully secure. Democracy Earth also plans to use a similar model of representation, running candidates who promise to adhere to the results of online votes rather than a particular ideology.

But MiVote takes a somewhat different approach to gathering opinions. The app will give users a notification when a new issue is addressed in the Australian parliament. Then, voters get access to a digital “information packet,” compiled by independent researchers, that lets them dive into four different approaches.

“We don’t talk about the bill or the legislation at all,” says Jacoby. “If you put it into a business context, the bill or the legislation is the contract. In no business would you write the contract before you know what the deal looks like. If we’re looking for genuine democracy, the bill has to be determined by the people . . . Once we know where the people want to go, then we focus on making sure the bill gets us there.”

If the parliament is going to vote about immigration, for example, you might get details about a humanitarian approach, a border security approach, a financially pragmatic approach, and an approach that focuses on international relations. For each frame of reference, the app lets you dive into as much information as you need to decide. If you don’t read anything, it won’t let you cast a vote.

“We’re much more interested in a solutions-oriented approach rather than an ideological approach,” he says. “Ideology basically says I have the answer for you before you’ve even asked the question. There is no ideology, no worldview, that has the solution to everything that ails us.”

Representatives of this hypothetical new party won’t have to worry about staying on message, because there is no message; the only goal is to vote after the people speak. That might free politicians to focus on solutions rather than their image…(More)”

Situation vacant: technology triathletes wanted


Anne-Marie Slaughter in the Financial Times: “It is time to celebrate a new breed of triathletes, who work in technology. When I was dean in the public affairs school at Princeton, I would tell students to aim to work in the public, private and civic sectors over the course of their careers.

Solving public problems requires collaboration among government, business and civil society. Aspiring problem solvers need the culture and language of all three sectors and to develop a network of contacts in each.

The public problems we face, in the US and globally, require lawyers, economists and issue experts but also technologists. A lack of technologists capable of setting up HealthCare.gov, a website designed to implement the Affordable Care act, led President Barack Obama to create the US Digital Service, which deploys Swat tech teams to address specific problems in government agencies.

But functioning websites that deliver government services effectively are only the most obvious technological need for the public sector.

Government can reinvent how it engages with citizens entirely, for example by personalising public education with digital feedback or training jobseekers. But where to find the talent? The market for engineers, designers and project managers sees big tech companies competing for graduates from the world’s best universities.

Governments can offer only a fraction of those salaries, combined with a rigid work environment, ingrained resistance to innovation and none of the amenities and perks so dear to Silicon Valley .

Government’s comparative advantage, however, is mission and impact, which is precisely what Todd Park sells…Still, demand outstrips supply. ….The goal is to create an ecosystem for public interest technology comparable to that in public interest law. In the latter, a number of American philanthropists created role models, educational opportunities and career paths for aspiring lawyers who want to change the world.

That process began in the 1960s, and today every great law school has a public interest programme with scholarships for the most promising students. Many branches of government take on top law school graduates. Public interest lawyers coming out of government find jobs with think-tanks and advocacy organisations and take up research fellowships, often at the law schools that educated them. When they need to pay the mortgage or send their kids to college, they can work at large law firms with pro bono programmes….We need much more. Every public policy school at a university with a computer science, data science or technology design programme should follow suit. Every think-tank should also become a tech tank. Every non-governmental organisation should have at least one technologist on staff. Every tech company should have a pro bono scheme rewarding public interest work….(More)”

How Big Data Analytics is Changing Legal Ethics


Renee Knake at Bloomberg Law: “Big data analytics are changing how lawyers find clients, conduct legal research and discovery, draft contracts and court papers, manage billing and performance, predict the outcome of a matter, select juries, and more. Ninety percent of corporate legal departments, law firms, and government lawyers note that data analytics are applied in their organizations, albeit in limited ways, according to a 2015 survey. The Legal Services Corporation, the largest funder of civil legal aid for low-income individuals in the United States, recommended in 2012 that all states collect and assess data on case progress/outcomes to improve the delivery of legal services. Lawyers across all sectors of the market increasingly recognize how big data tools can enhance their work.

A growing literature advocates for businesses and governmental bodies to adopt data ethics policies, and many have done so. It is not uncommon to find data-use policies prominently displayed on company or government websites, or required a part of a click-through consent before gaining access to a mobile app or webpage. Data ethics guidelines can help avoid controversies, especially when analytics are used in potentially manipulative or exploitive ways. Consider, for example, Target’s data analytics that uncovered a teen’s pregnancy before her father did, or Orbitz’s data analytics offered pricier hotels to Mac users. These are just two of numerous examples in recent years where companies faced criticism for how they used data analytics.

While some law firms and legal services organizations follow data-use policies or codes of conduct, many do not. Perhaps this is because the legal profession was not transformed as early or rapidly as other industries, or because until now, big data in legal was largely limited to e-discovery, where the data use is confined to the litigation and is subject to judicial oversight. Another reason may be that lawyers believe their rules of professional conduct provide sufficient guidance and protection. Unlike other industries, lawyers are governed by a special code of ethical obligations to clients, the justice system, and the public. In most states, this code is based in part upon the American Bar Association (ABA) Model Rules of Professional Conduct, though rules often vary from jurisdiction to jurisdiction. Several of the Model Rules are relevant to big data use. That said, the Model Rules are insufficient for addressing a number of fundamental ethical concerns.

At the moment, legal ethics for big data analytics is at best an incomplete mix of professional conduct rules and informal policies adopted by some, but not all law practices. Given the increasing prevalence of data analytics in legal services, lawyers and law students should be familiar not only with the relevant professional conduct rules, but also the ethical questions left unanswered. Listed below is a brief summary of both, followed by a proposed legal ethics agenda for data analytics. …

Questions Unanswered by Lawyer Ethics Rules 

Access/Ownership. Who owns the original data — the individual source or the holder of the pooled information? Who owns the insights drawn from its analysis? Who should receive access to the data compilation and the results?

Anonymity/Identity. Should all personally identifiable or sensitive information be removed from the data? What protections are necessary to respect individual autonomy? How should individuals be able to control and shape their electronic identity?

Consent. Should individuals affirmatively consent to use of their personal data? Or is it sufficient to provide notice, perhaps with an opt-out provision?

Privacy/Security. Should privacy be protected beyond the professional obligation of client confidentiality? How should data be secured? The ABA called upon private and public sector lawyers to implement cyber-security policies, including data use, in a 2012resolution and produced a cyber-security handbook in 2013.

Process. How involved should lawyers be in the process of data collection and analysis? In the context of e-discovery, for example, a lawyer is expected to understand how documents are collected, produced, and preserved, or to work with a specialist. Should a similar level of knowledge be required for all forms of data analytics use?

Purpose. Why was the data first collected from individuals? What is the purpose for the current use? Is there a significant divergence between the original and secondary purposes? If so, is it necessary for the individuals to consent to the secondary purpose? How will unintended consequences be addressed?

Source. What is the source of the data? Did the lawyer collect it directly from clients, or is the lawyer relying upon a third-party source? Client-based data is, of course, subject to the lawyer’s professional conduct rules. Data from any source should be trustworthy, reasonable, timely, complete, and verifiable….(More)”