Stefaan Verhulst

Blog by Amen Ra Mashariki: “Governments should protect the data and privacy rights of their communities even during emergencies. It is a false trade-off to require more data without protection. We can and should do both — collect the appropriate data and protect it. Establishing and protecting the data rights and privacy of our communities’ underserved, underrepresented, disabled, and vulnerable residents is the only way we can combat the negative impact of COVID-19 or any other crisis.

Building trust is critical. Governments can strengthen data privacy protocols, beef up transparency mechanisms, and protect the public’s data rights in the name of building trust — especially with the most vulnerable populations. Otherwise, residents will opt out of engaging with government, and without their information, leaders like first responders will be blind to their existence when making decisions and responding to emergencies, as we are seeing with COVID-19.

As Chief Analytics Officer of New York City, I often remembered the words of Defense Secretary Donald Rumsfeld, especially with regards to using data during emergencies, that there are “known knowns, known unknowns, and unknown unknowns, and we will always get hurt by the unknown unknowns.” Meaning the things we didn’t know — the data that we didn’t have — was always going to be what hurt us during times of emergencies….

There are three key steps that governments can do right now to use data most effectively to respond to emergencies — both for COVID-19 and in the future.

Seek Open Data First

In times of crisis and emergencies, many believe that government and private entities, either purposefully or inadvertently, are willing to trample on the data rights of the public in the name of appropriate crisis response. This should not be a trade-off. We can respond to crises while keeping data privacy and data rights in the forefront of our minds. Rather than dismissing data rights, governments can start using data that is already openly available. This seems like a simple step, but it does two very important things. First, it forces you to understand the data that is already available in your jurisdiction. Second, it grows your ability to fill the gaps with respect to what you know about the city by looking outside of city government. …(More)”.

Report by the Ada Lovelace Institute and DataKind UK: “As algorithmic systems become more critical to decision making across many parts of society, there is increasing interest in how they can be scrutinised and assessed for societal impact, and regulatory and normative compliance.

This report is primarily aimed at policymakers, to inform more accurate and focused policy conversations. It may also be helpful to anyone who creates, commissions or interacts with an algorithmic system and wants to know what methods or approaches exist to assess and evaluate that system…

Clarifying terms and approaches

Through literature review and conversations with experts from a range of disciplines, we’ve identified four prominent approaches to assessing algorithms that are often referred to by just two terms: algorithm audit and algorithmic impact assessment. But there is not always agreement on what these terms mean among different communities: social scientists, computer scientists, policymakers and the general public have different interpretations and frames of reference.

While there is broad enthusiasm among policymakers for algorithm audits and impact assessments, there is often lack of detail about the approaches being discussed. This stems both from the confusion of terms, but also from the different maturity of the approaches the terms describe.

Clarifying which approach we’re referring to, as well as where further research is needed, will help policymakers and practitioners to do the more vital work of building evidence and methodology to take these approaches forward.

We focus on algorithm audit and algorithmic impact assessment. For each, we identify two key approaches the terms can be interpreted as:

• Algorithm audit
  • Bias audit: a targeted, non-comprehensive approach focused on assessing algorithmic systems for bias
  • Regulatory inspection: a broad approach, focused on an algorithmic system’s compliance with regulation or norms, necessitating a number of different tools and methods; typically performed by regulators or auditing professionals
• Algorithmic impact assessment
  • Algorithmic risk assessment: assessing possible societal impacts of an algorithmic system before the system is in use (with ongoing monitoring often advised)
  • Algorithmic impact evaluation: assessing possible societal impacts of an algorithmic system on the users or population it affects after it is in use…(More)”.

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Book edited by Simon Deakin and Christopher Markou: “What does computable law mean for the autonomy, authority, and legitimacy of the legal system? Are we witnessing a shift from Rule of Law to a new Rule of Technology? Should we even build these things in the first place?

This unique volume collects original papers by a group of leading international scholars to address some of the fascinating questions raised by the encroachment of Artificial Intelligence (AI) into more aspects of legal process, administration, and culture. Weighing near-term benefits against the longer-term, and potentially path-dependent, implications of replacing human legal authority with computational systems, this volume pushes back against the more uncritical accounts of AI in law and the eagerness of scholars, governments, and LegalTech developers, to overlook the more fundamental – and perhaps ‘bigger picture’ – ramifications of computable law…(More)”

Paper by Tomoya Igarashi, Masanori Koizumi and Michael Widdersheim: “The Japanese government has initiated lifelong learning policies to promote lifelong learning to a super-aging society. It is said that lifelong learning contributes to a richer and more fulfilling life. It is within this context that public libraries have been identified as ideal facilities for promoting lifelong learning. To support lifelong learning successfully, libraries must accurately grasp citizens’ needs, all while working within limited budgets. To understand citizens’ learning needs, this study uses public library circulation data. This study is significant because such data use is often unavailable in Japan. This data was used to clarify citizens’ learning interests. Circulation data was compared from two libraries in Japan: Koto District Library in Tokyo and Tahara City Library in Aichi Prefecture. The data was used to identify general learning needs while also accounting for regional differences. The methodology and results of this research are significant for the development of lifelong learning policy and programming….(More)”.

Andrew Young at The GovLab: “The GovLab and UNICEF, as part of the Responsible Data for Children initiative (RD4C), are pleased to share a set of user-friendly tools to support organizations and practitioners seeking to operationalize the RD4C Principles. These principles—Purpose-Driven, People-Centric, Participatory, Protective of Children’s Rights, Proportional, Professionally Accountable, and Prevention of Harms Across the Data Lifecycle—are especially important in the current moment, as actors around the world are taking a data-driven approach to the fight against COVID-19.

The initial components of the RD4C Toolkit are:

The RD4C Data Ecosystem Mapping Tool intends to help users to identify the systems generating data about children and the key components of those systems. After using this tool, users will be positioned to understand the breadth of data they generate and hold about children; assess data systems’ redundancies or gaps; identify opportunities for responsible data use; and achieve other insights.

The RD4C Decision Provenance Mapping methodology provides a way for actors designing or assessing data investments for children to identify key decision points and determine which internal and external parties influence those decision points. This distillation can help users to pinpoint any gaps and develop strategies for improving decision-making processes and advancing more professionally accountable data practices.

The RD4C Opportunity and Risk Diagnostic provides organizations with a way to take stock of the RD4C principles and how they might be realized as an organization reviews a data project or system. The high-level questions and prompts below are intended to help users identify areas in need of attention and to strategize next steps for ensuring more responsible handling of data for and about children across their organization.

Finally, the Data for Children Collaborative with UNICEF developed an Ethical Assessment that “forms part of [their] safe data ecosystem, alongside data management and data protection policies and practices.” The tool reflects the RD4C Principles and aims to “provide an opportunity for project teams to reflect on the material consequences of their actions, and how their work will have real impacts on children’s lives.

RD4C launched in October 2019 with the release of the RD4C Synthesis Report, Selected Readings, and the RD4C Principles. Last month we published the The RD4C Case Studies, which analyze data systems deployed in diverse country environments, with a focus on their alignment with the RD4C Principles. The case studies are: Romania’s The Aurora Project, Childline Kenya, and Afghanistan’s Nutrition Online Database.

To learn more about Responsible Data for Children, visit rd4c.org or contact rd4c [at] thegovlab.org. To join the RD4C conversation and be alerted to future releases, subscribe at this link.”

Blog by Sam DeJohn, Anirudh Dinesh, and Dane Gambrell: “As COVID-19 changes how we work, governments everywhere are experimenting with new ways to adapt and continue legislative operations under current physical restrictions. From city councils to state legislatures and national parliaments, more public servants are embracing and advocating for the use of new technologies to convene, deliberate, and vote.

On April 20th, GovLab published an initial overview of such efforts in the latest edition of the CrowdLaw Communique. As the United States Congress wrestles with the question of whether to allow remote voting, the GovLab has compiled an update on those international and state legislatures that are the furthest ahead with the use of new technology to continue operations.

NORTH AMERICA

In the US, On April 16, over 60 former members of Congress participated in a “Mock Remote Hearing” exercise to test the viability of online proceedings during the COVID-19 pandemic.

In Kentucky, when they last met on April 1, that State’s House of Representatives adopted new rules allowing lawmakers to vote remotely by sending in photos of a ballot to designated managers on the House Floor.” (WFPL). Lawmakers have also altered voting procedures to limit the number of lawmakers on the House floor. Members will vote in groups of 25 and may vote by paper ballot (NCSL).

New Jersey lawmakers made history on March 25 when members of the General Assembly called into a conference line to cast their votes remotely on several bills related to the coronavirus pandemic. NJ lawmakers moved 12 bills that day via remote voting.

On the west coast of the United States, the city council of Kirkland, Washington, recently held its first virtual city council meeting. Many cities and counties in California have also begun holding their meetings via Zoom.

As compiled by the National Council of State Legislatures, states that have changed rules — many just in the past few weeks — to allow full committee action and/or remote voting include: Iowa, Kentucky, Minnesota, New Jersey, North Carolina, Utah, and Vermont. Other states have specifically said they are seriously considering allowing remote action, including New Hampshire, New Mexico, New York, and Wyoming.

EUROPE

In the European Union, Parliament is temporarily allowing remote participation to avoid spreading COVID-19 (Library of Congress). With regard to voting, all members, even those participating in person, will receive a ballot sent by email to their official email address. The ballot, which must contain the name and vote of the MP in a readable form and the MP’s signature, must be returned from their official email address to the committee or plenary services in order to be counted. The ballot must be received in the dedicated official European Parliament mailbox by the time the vote is closed.

In Spain, MPs have been casting votes using the Congress’s intranet system, which has been in place since 2012. Rather than voting in real time, voting is typically open for a two-hour period before the session to vote for the alternative or amendment proposals and for a two-hour period following the session in which the proposals are debated to vote the final text….(More)”.

Ruth Michaelson at the Smithsonian Magazine: “…Even as tongue-in-cheek phrases like “avoiding the Rona” abound on American social media, to say nothing of the rapper Cardi B’s enunciation of “coronavirus,” other terms like “social distancing,” or “lockdown,” have quickly entered our daily vocabulary.

But what these terms mean in different countries (or regions or cities within regions, in Wuhan’s case) is a question of translation as well as interpretation. Communities around the world remain under government-enforced lockdown to prevent the spread of COVID-19, but few have understood “stay at home,” or liu-zai-jia-li in Mandarin, to mean precisely the same thing. The concept of social distancing, normally indicating a need to avoid contact with others, can mean anything from avoiding public transport to the World Health Organization’s recommendation to “maintain at least one metre distance,” from those who are coughing or sneezing. In one Florida county, officials explained the guideline by suggesting to residents they stay “one alligator” away from each other.

The way that terms like “social distancing,” are adopted across languages provides a way to understand how countries across the globe are coping with the COVID-19 threat. For instance, the Mandarin Chinese translation of “social distancing”, or ju-li-yuan-dian, is interpreted differently in Wuhan dialect, explains Jin. “Instead of ‘keep a distance,’ Wuhan dialect literally translates this as ‘send far away.’”

Through these small shifts in language, says Jin, “people in Wuhan expose their feelings about their own suffering.”

In Sweden, meanwhile, has currently registered more than 16,000 cases of COVID-19, the highest incidence rate in Scandinavia. The government has taken an unusually lax approach to enforcing its pandemic mitigation policies, placing the emphasis on citizens to self-police, perhaps to ill effect. While Swedes do use terms like social distancing, or rather the noun socialt avstånd, these are accompanied by other ideas that are more popular in Sweden. “Herd immunity or flockimmunitet is a very big word around here,” says Jan Pedersen, director of the Institute for Interpreting and Translation Studies at Stockholm University.

“Sweden is famous for being a very consensus driven society, and this applies here as well,” he says. “There’s a great deal of talk about trust.” In this case, he explained, citizens have trust – tillit – in the authorities to make good choices and so choose to take personligt ansvar, or personal responsibility.

Pedersen has also noticed some new language developing as a result. “The word recommendation, rekommendationer, in Sweden has taken on much stronger force,” he said. “Recommendation used to be a recommendation, what you could do or not. Now it’s slightly stronger … We would use words like obey with laws, but now here you obey a recommendation, lyda rekommendationer.”…(More)”.

Nigam Shah and Jacob Steinhardt at Brookings: “Social distancing and stay-at-home orders in the United States have slowed the infection rate of SARS-CoV-2, the pathogen that causes COVID-19. This has halted the immediate threat to the U.S. healthcare system, but consensus on a long-term plan or solution to the crisis remains unclear.  As the reality settles in that there are no quick fixes and that therapies and vaccines will take several months if not years to invent, validate, and mass produce, this is a good time to consider another question: How can data science and technology help us endure the pandemic while we develop therapies and vaccines?

Before policymakers reopen their economies, they must be sure that the resulting new COVID-19 cases will not force local healthcare systems to resort to crisis standards of care. Doing so requires not just prevention and suppression of the virus, but ongoing measurement of virus activity, assessment of the efficacy of suppression measures, and forecasting of near-term demand on local health systems. This demand is highly variable given community demographics, the prevalence of pre-existing conditions, and population density and socioeconomics.

Data science can already provide ongoing, accurate estimates of health system demand, which is a requirement in almost all reopening plans. We need to go beyond that to a dynamic approach of data collection, analysis, and forecasting to inform policy decisions in real time and iteratively optimize public health recommendations for re-opening. While most reopening plans propose extensive testing, contact tracing, and monitoring of population mobility, almost none consider setting up such a dynamic feedback loop. Having such feedback could determine what level of virus activity can be tolerated in an area, given regional health system capacity, and adjust population distancing accordingly.

We propose that by using existing technology and some nifty data science, it is possible to set up that feedback loop, which would maintain healthcare demand under the threshold of what is available in a region. Just as the maker community stepped up to cover for the failures of the government to provide adequate protective gear to health workers, this is an opportunity for the data and tech community to partner with healthcare experts and provide a measure of public health planning that governments are unable to do. Therefore, the question we invite the data science community to focus on is: How can data science help forecast regional health system resource needs given measurements of virus activity and suppression measures such as population distancing?…

Concretely, then, the crucial “data science” task is to learn the counterfactual function linking last week’s population mobility and today’s transmission rates to project hospital demand two weeks later. Imagine taking past measurements of mobility around April 10 in a region (such as the Santa Clara County’s report from COVID-19 Community Mobility Reports), the April 20 virus transmission rate estimate for the region (such as from http://rt.live), and the April 25 burden on the health system (such as from the Santa Clara County Hospitalization dashboard), to learn a function that uses today’s mobility and transmission rates to anticipate needed hospital resources two weeks later. It is unclear how many days of data of each proxy measurement we need to reliably learn such a function, what mathematical form this function might take, and how we do this correctly with the observational data on hand and avoid the trap of mere function-fitting. However, this is the data science problem that needs to be tackled as a priority. 

Adopting such technology and data science to keep anticipated healthcare needs under the threshold of availability in a region requires multiple privacy trade-offs, which will require thoughtful legislation so that the solutions invented for enduring the current pandemic do not lead to loss of privacy in perpetuity. However, given the immense economic as well as hidden medical toll of the shutdown, we urgently need to construct an early warning system that tells us to enhance suppression measures if the next COVID-19 outbreak peak might overwhelm our regional healthcare system. It is imperative that we focus our attention on using data science to anticipate, and manage, regional health system resource needs based on local measurements of virus activity and effects of population distancing….(More)”.

Rosalyn Old at Nesta: “In the midst of the COVID-19 global pandemic, governments at all levels are having to make decisions to postpone elections and parliamentary sessions, all while working remotely and being under pressure to deliver fast-paced and effective decision-making.

In times of crisis, there can be a tension between the instinct to centralise decision-making for efficiency, sacrificing consultation in the process, and the need to get citizens on board with plans for large-scale changes to everyday life. While such initial reactions are understandable, in the current and next phases we need a different approach – democracy must go on.

Effective use of digital tools can provide a way to keep parliamentary and government processes going in a way that enhances rather than threatens democracy. This is a unique opportunity to experiment with digital methods to address a number of business-as-usual pain points in order to support institutions and citizen engagement in the long term.

Digital tools can help with the spectrum of decision-making

While digital tools can’t give the answers, they can support the practicalities of remote decision-making. Our typology of digital democracy shows how digital tools can be used to harness the wisdom of the crowd in different stages of a process:

A typology of digital democracy

Digital tools can collect information from different sources to provide an overview of the options. To weigh up pros and cons, platforms such as Your Priorities and Consul enable people to contribute arguments. If you need a sense of what is important and to try to find consensus, Pol.is and Loomio may help. To quickly gauge support for different options from stakeholders, platforms such as All Our Ideas enable ranking of a live bank of ideas. If you need to gather questions and needs of citizens, head to platforms like Sli.do or online forms or task management tools like Trello or Asana….(More)”.

Paper by Urs Gasser et al: “Data collection and processing via digital public health technologies are being promoted worldwide by governments and private companies as strategic remedies for mitigating the COVID-19 pandemic and loosening lockdown measures. However, the ethical and legal boundaries of deploying digital tools for disease surveillance and control purposes are unclear, and a rapidly evolving debate has emerged globally around the promises and risks of mobilizing digital tools for public health. To help scientists and policymakers navigate technological and ethical uncertainty, we present a typology of the primary digital public health applications currently in use. Namely: proximity and contact tracing, symptom monitoring, quarantine control, and flow modeling. For each, we discuss context-specific risks, cross-sectional issues, and ethical concerns. Finally, in recognition of the need for practical guidance, we propose a navigation aid for policymakers made up of ten steps for the ethical use of digital public health tools….(More)”.