Stefaan Verhulst
Blog post by Andrew Young, Andrew J. Zahuranec, Stephen Burley Tubman, William Hoffman, and Stefaan Verhulst at Data & Society: “To deal with complex public challenges, organizations increasingly seek to leverage data across sectors in new and innovative ways — from establishing prize-backed challenges around the use of diverse datasets to creating cross-sector federated data systems. These and other forms of data collaboratives are part of a new paradigm in data-driven innovation in which participants from different sectors provide access to data for the creation of public value. It provides an essential new problem-solving approach for our increasingly datafied society. However, the operational challenges associated with creating such partnerships often prevent the transformative potential of data collaboration from being achieved.
One such operational challenge relates to developing data sharing agreements — through contracts and other legal documentation. The current practice suffers from large inefficiencies and transaction costs resulting from (i) the lack of a common understanding of what the core issues are with data exchange; (ii) lack of common language or models; (iii) large heterogeneity in agreements used; (iv) lack of familiarity among lawyers of the technologies involved and (v) a sense that every initiative needs to (re)invent the wheel. Removing these barriers may enable collaborators to partner more systematically and responsibly around the re-use of data assets. Contracts for Data Collaboration (C4DC) is a new initiative seeking to address these barriers to data collaboration…
In the longer term, participants focused on three major themes that, if addressed, could steer contracting for data collaboration toward greater effectiveness and legitimacy.
Data Stewardship and Responsibility: First, much of the discussion centered on the need to promote responsible data practices through data stewardship. Though part of this work involves creating teams and individuals empowered to share, it also means empowering them to operationalize ethical principles.
By developing international standards and moving beyond the bare minimum legal obligation, these actors can build trust between parties, a quality that has often been difficult to foster. Such relationships are key in engaging intermediaries or building complex contractual agreements between multiple organizations. It is also essential to come to an agreement about which practices are legitimate and illegitimate.
Incorporation of the Citizen Perspective: Trust is also needed between the actors in a data collaborative and the general public. In light of many recent stories about the misuse of data, many people are suspicious, if not outright hostile, to data partnerships. Many data subjects don’t understand why organizations want their data or how the information can be valuable in advancing public good.
In data-sharing arrangements, all actors need to explain intended uses and outcomes to data subjects. Attendees spoke about the need to explain the data’s utility in clear and accessible terms. They also noted data collaborative contracts are more legitimate if they incorporate citizen perspectives, especially those of marginalized groups. To take this work a step further, the public could be brought into the contract writing process by creating mechanisms capable of soliciting their views and concerns.
Improving Internal and External Collaboration: Lastly, participants discussed the need for actors across the data ecosystem to strengthen relationships inside and outside their organizations. Part of this work entails securing internal buy-in for data collaboration, ensuring that the different components of an organization understand what assets are being shared and why.
It also entails engaging with intermediaries to fill gaps. Each actor has limitations to their capacities and expertise and, by engaging with start-ups, funders, NGOs, and others, organizations can improve the odds of a successful collaboration. Together, organizations can create norms and shared languages that allow for more effective data flows.
One such operational challenge relates to developing data sharing agreements — through contracts and other legal documentation. The current practice suffers from large inefficiencies and transaction costs resulting from (i) the lack of a common understanding of what the core issues are with data exchange; (ii) lack of common language or models; (iii) large heterogeneity in agreements used; (iv) lack of familiarity among lawyers of the technologies involved and (v) a sense that every initiative needs to (re)invent the wheel. Removing these barriers may enable collaborators to partner more systematically and responsibly around the re-use of data assets. Contracts for Data Collaboration (C4DC) is a new initiative seeking to address these barriers to data collaboration…(More)”.
The Mastercard Center for Inclusive Growth: “… is unveiling a groundbreaking suite of tools that will provide local leaders with timely data-driven insights on the current state of and potential for inclusive growth in their communities. The announcement comes as private and public sector leaders gather in Washington for the inaugural Global Inclusive Growth Summit.
For the first time the new Inclusive Growth Toolkit brings together a clear, simple view of social and economic growth in underserved communities across the U.S., at the census-tract level. This was created in response to growing demand from community leaders for more evidence-based insights, to help them steer impact investment dollars to locally-led economic development initiatives, unlock the potential of neighborhoods, and improve quality of life for all.
The initial design of the toolkit is focused on driving sustainable growth for the 37+ million people living in the 8700+ QOZs throughout the United States. This comprehensive picture reveals that neighborhoods can look very different and may require different types of interventions to achieve successful and sustainable growth.
The Inclusive Growth Toolkit includes:
- The Inclusive Growth Score – an interactive online map where users can view measures of inclusion and growth and then download a PDF Scorecard for any of the QOZs at census tract level.
A deep-dive analytics consultancy service that provides community leaders with customized insights to inform policy decisions, prospectus development, and impact investor discussions….(More)”.
Hearing by the Senate Committee on Banking, Housing and Urban Affairs:”…As a result of an increasingly digital economy, more personal information is available to companies than ever before.
Private companies are collecting, processing, analyzing and sharing considerable data on individuals for all kinds of purposes.
There have been many questions about what personal data is being collected, how it is being collected, with whom it is being shared and how it is being used, including in ways that affect individuals’ financial lives.
Given the vast amount of personal information flowing through the economy, individuals need real control over their personal data. This Committee has held a series of data privacy hearings exploring possible
frameworks for facilitating privacy rights to consumers. Nearly all have included references to data as a new currency or commodity.
The next question, then, is who owns it? There has been much debate about the concept of data ownership, the monetary value of personal information and its potential role in data privacy…..The witnesses will be:
- Mr. Jeffrey Ritter Founding Chair, American Bar Association Committee on Cyberspace Law, External Lecturer
- Mr. Chad Marlow Senior Advocacy And Policy Counsel American Civil Liberties Union
- Mr. Will Rinehart Director Of Technology And Innovation Policy American Action Forum
- Ms. Michelle Dennedy Chief Executive Officer DrumWave Inc.
David Pilling at the Financial Times: “When statisticians decided to track how well African countries were doing in moving towards their 2030 UN sustainable development goals, they discovered a curious thing: no one had the faintest idea. More accurately, on average, African governments keep statistics covering only about a third of the relevant data. To be fair, the goals, which range from eradicating poverty and hunger to creating sustainable cities and communities, are overly complicated and sometimes unquantifiable.
The millennium development goals that they superseded had eight goals with 21 indicators. The SDGs have 17, with 232 indicators. Yet statisticians for the Mo Ibrahim Foundation, which compiled the report, are on to something. African states don’t know enough about their people.
In this age of mass surveillance, that might seem counterintuitive. Surely governments, not to mention private companies, have too much information on their citizenry? In fact, in many African nations with weak states, big informal economies and undocumented communities, the problem is the reverse. How many people are there in Nigeria? What is the unemployment rate in Zimbabwe? How many people in Kibera, a huge informal settlement in Nairobi, have access to healthcare? The answers to such basic questions are: we don’t really know. Nigeria last conducted a census in 2006, when the population — a sensitive topic in which religion, regionalism and budget allocations are messily intertwined — came out at 140m. These days it could be 180m or 200m. Or perhaps more. Or less.
President Muhammadu Buhari recently complained that statistics quoted by international bodies, such as those alleging that Nigeria has more people living in absolute poverty than India, were “wild estimates” bearing “little relation to facts on the ground”. The riposte to that is simple. Work out what is happening and do something about it. Likewise, unemployment is hard to define, let alone quantify, in a broken economy such as Zimbabwe’s where cited jobless statistics range from 5 to 95 per cent. Is a struggling subsistence farmer or a street-side hawker jobless or gainfully employed?
For that matter what is the status of a government employee who receives her salary in a useless electronic currency? According to Seth Berkley, chief executive of the Vaccine Alliance, keeping tabs on unregistered people in the sprawling “slums” of Africa’s increasingly massive megacities, is harder than working out what is going on in isolated villages. If governments do not know whether a person exists it is all too easy to ignore their rights — to healthcare, to education or to the vote. The Mo Ibrahim Foundation found that only eight countries in Africa register more than 90 per cent of births. Tens of millions of people are literally invisible. Mr Ibrahim, a Sudanese billionaire, calls data “the missing SDG”….(More)”
Jim Baker at Lawfare: “…Public safety officials should continue to highlight instances where they find that encryption hinders their ability to effectively and efficiently protect society so that the public and lawmakers understand the trade-offs they are allowing. To do this, the Justice Department should, for example, file an annual public report describing, as best it can, the continuing nature and scope of the going dark problem. If necessary, it can also file a classified annual report with the appropriate congressional committees.
But, for the reasons discussed above, public safety officials should also become among the strongest supporters of widely available strong encryption.
I know full well that this approach will be a bitter pill for some in law enforcement and other public safety fields to swallow, and many people will reject it outright. It may make some of my former colleagues angry at me. I expect that some will say that I’m simply joining others who have left the government and switched sides on encryption to curry favor with the tech sector in order to get a job. That is wrong. My dim views about cybersecurity risks, China and Huawei are essentially the same as those that I held while in government. I also think that my overall approach on encryption today—as well as my frustration with Congress—is generally consistent with the approach I had while I was in government.
I have long said—as I do here—that encryption poses real challenges for public safety officials; that any proposed technical solution must properly balance all of the competing equities; and that (absent an unlikely definitive judicial ruling as a result of litigation) Congress must change the law to resolve the issue. What has changed is my acceptance of, or perhaps resignation to, the fact that Congress is unlikely to act, as well as my assessment that the relevant cybersecurity risks to society have grown disproportionately over the years when compared with other risks….(More)”.
Press Release: “The Lisbon Council launches The Public-Data Opportunity: Why Governments Should Share More, a new discussion paper that looks at the state of play for public-sector data sharing – and calls for better protocols and procedures to deliver data-driven service to all Europeans. The paper analyses the importance of data-sharing between European Union public agencies, identifies the barriers and proposes seven policy recommendations that will help lift them. It builds on the research conducted by the “Understanding Value Co-Creation in Public Services for Transforming European Public Administrations” project, or Co-VAL, a 12-partner research consortium, co-funded by the European Union. And was launched at The 2019 Digital Government Conference convened by the Presidency of the European Council of Finland in Helsinki….(More)”
Shalini Kurapati at the LSE Impact Blog: “In the context of higher education, data stewards are the first point of reference for all data related questions. In my role as a data steward at TU Delft, I was able to advise, support and train researchers on various aspects of data management throughout the life cycle of a research project, from initial planning to post-publication. This included storing, managing and sharing research outputs such as data, images, models and code.
Data stewards also advise researchers on the ethical, policy and legal considerations during data collection, processing and dissemination. In a way, they are general practitioners for research data management and can usually solve most problems faced by academics. In cases that require specialist intervention, they also serve as a key point for referral (eg: IT, patent, legal experts).
Data stewardship is often organised centrally through the university library. (Subject) Data librarians, research data consultants and research data officers, usually perform similar roles to data stewards. However, TU Delft operates a decentralised model, where data stewards are placed within faculties as disciplinary experts with research experience. This allows data stewards to provide discipline specific support to researchers, which is particularly beneficial, as the concept of what data is itself varies across disciplines….(More)”.
Mia Hunt at Global Government Forum: “The New Zealand government has launched a draft ‘algorithm charter’ that sets out how agencies should analyse data in a way that is fair, ethical and transparent.
The charter, which is open for public consultation, sets out 10 points that agencies would have to adhere to. These include pledging to explain how significant decisions are informed by algorithms or, where it cannot – for national security reasons, for example – explain the reason; taking into account the perspectives of communities, such as LGBTQI+, Pacific islanders and people with disabilities; and identifying and consulting with groups or stakeholders with an interest in algorithm development.
Agencies would also have to publish information about how data is collected and stored; use tools and processes to ensure that privacy, ethics, and human rights considerations are integrated as part of algorithm development and procurement; and periodically assess decisions made by algorithms for unintended bias.
They would commit to implementing a “robust” peer-review process, and have to explain clearly who is responsible for automated decisions and what methods exist for challenge or appeal “via a human”….
The charter – which fits on a single page, and is designed to be simple and easily understood – explains that algorithms are a “fundamental element” of data analytics, which supports public services and delivers “new, innovative and well-targeted” policies aims.
The charter begins: “In a world where technology is moving rapidly, and artificial intelligence is on the rise, it’s essential that government has the right safeguards in place when it uses public data for decision-making. The government must ensure that data ethics are embedded in its work, and always keep in mind the people and communities being served by these tools.”
It says Stats NZ, the country’s official data agency, is “committed to transparent and accountable use of operational algorithms and other advanced data analytics techniques that inform decisions significantly impacting on individuals or groups”….(More)”.
Ronald W. Dworkin at National Affairs: “In the modern world, science has become the ultimate guide for describing reality. It’s easy to see the appeal. Science has a beautiful clarity and economy; its laws are straightforward and unchanging. It reveals the workings of the world around us with such calmness and exactness, and with such an appearance of impartiality, that we feel satisfied with its answers and seek nothing more.
Newtonian mechanics represent the nearest approach to this ideal of science ever achieved. Given the masses, positions, and motions of objects, their future positions and motions can be calculated with extraordinary precision. Sir Isaac Newton’s method was a revolution. Before Newton, science was conducted in an altogether different way; investigators speculated rather than experimented. It was Newton who stripped objects of all but their most basic attributes — mass and density — and timed their fall, drawing conclusions from what he observed rather than from what he imagined. By reducing objects to a few measurable characteristics, he was able to discover the universal laws that governed the behavior of all objects.
An analogous revolution occurred in political thought around the same period. While ancient philosophers tried to define virtue, Thomas Hobbes, whose lifetime spanned Newton’s early years, took the opposite approach. Stripping people of all but their most basic (and base) attributes — selfishness and vanity — he claimed to explain mankind’s mechanics, as it were, and the structure of civilization. His rules of the social contract explained how the basic machine of society works, just as Newton’s laws of motion explained how the machine of the universe works.
The scientific revolution has now entered a second phase. It has moved beyond the hard sciences and Hobbesian philosophy and become the unifying principle of many activities in daily life. Through the relatively new disciplines of psychology, neuroscience, human science, and social science, it has inserted itself into how people think and behave at the individual level, affecting everything from interpersonal relationships to psychological health to education. The scientific revolution permeates our lives, shaping our sense of reality and truth. But sometimes it does so in ways that result in sheer absurdity. This is because of flaws within the scientific method itself — in other words, at the scientific revolution’s core. These flaws rarely show up in hard science, but they grow more obvious, and more problematic, as humanity takes the place of inanimate objects as the method’s primary target.
To better understand what has happened, it will help to take a brief look back at the scientific revolution’s first phase….(More)”.
Chapter by Giovanni De Gregorio and Sofia Ranchordas in J. Cannataci, V. Falce & O. Pollicino (Eds), New Legal Challenges of Big Data (Edward Elgar, 2020, Forthcoming): “In the digital society, individuals play different roles depending on the situation they are placed in: they are consumers when they purchase a good, citizens when they vote for elections, content providers when they post information on a platform, and data subjects when their data is collected. Public authorities have thus far regulated citizens and the data collected on their different roles in silos (e.g., bankruptcy registrations, social welfare databases), resulting in inconsistent decisions, redundant paperwork, and delays in processing citizen requests. Data silos are considered to be inefficient both for companies and governments. Big data and data analytics are disrupting these silos allowing the different roles of individuals and the respective data to converge. In practice, this happens in several countries with data sharing arrangements or ad hoc data requests. However, breaking down the existing structure of information silos in the public sector remains problematic. While big data disrupts artificial silos that may not make sense in the digital society and promotes a truly efficient digitalization of data, removing information out of its original context may alter its meaning and violate the privacy of citizens. In addition, silos ensure that citizens are not assessed in one field by information generated in a totally different context. This chapter discusses how big data and data analytics are changing information silos and how digital technology is challenging citizens’ autonomy and right to privacy and data protection. This chapter also explores the need for a more integrated approach to the study of information, particularly in the public sector.