Stefaan Verhulst
Paper by Dirk Bergemann and Alessandro Bonatti: “Large internet platforms collect data from individual users in almost every interaction on the internet. Whenever an individual browses a news website, searches for a medical term or for a travel recommendation, or simply checks the weather forecast on an app, that individual generates data. A central feature of the data collected from the individuals is its social aspect. Namely, the data captured from an individual user is not only informative about this specific individual, but also about users in some metric similar to the individual. Thus, the individual data is really social data. The social nature of the data generates an informational externality that we investigate in this note….(More)”.
Olivia Biermann et al at PLOS Blog Speaking of Medicine: “Citizen engagement is important to make health and social policies more inclusive and equitable, and to contribute to learning and responsive health and social systems. It is also valuable in understanding the complexities of the social structure and how to adequately respond to them with policies. By engaging citizens, we ensure that their tacit knowledge feeds into the policy-making process. What citizens know can be valuable in identifying feasible policy options, understanding contextual factors, and putting policies into practice. In addition, the benefit of citizen engagement extends much beyond improving health policy-making processes by making them more participatory and inclusive; being engaged in policy-making processes can build patients’ capacity and empower them to speak up for their own and their families’ health and social needs, and to hold policy-makers accountable. Moreover, apart from being involved in their own care, citizen-patients can contribute to quality improvement, research and education.
Most studies on citizen engagement to date originate from high-income countries. The engagement methods used are not necessarily applicable in low- and middle-income countries, and even the political support, the culture of engagement and established citizen engagement processes might be different. Still, published processes of engaging citizens can be helpful in identifying key components across different settings, e.g. in terms of levels of engagement, communication channels and methods of recruitment. Contextualizing the modes of engagement between and within countries is a must.
Examples of citizen engagement
There are many examples of ad hoc citizen engagement initiatives at local, national and international levels. Participedia, a repository of public participation initiatives around the globe, showcases that the field of citizen engagement is extremely vibrant. In the United Kingdom, the Citizens’ Council of the National Institute for Health and Clinical Excellence (NICE) provides NICE with a public perspective on overarching moral and ethical issues that NICE has to take into account when producing guidance. In the United States of America, the National Issues Forum supports the implementation of deliberative forums on pressing national policy issues. Yet, there are few examples that have long-standing programs of engagement and that engage citizens in evidence-informed policymaking.
A pioneer in engaging citizens in health policy-making processes is the McMaster Health Forum in Hamilton, Canada. The citizens who are invited to engage in a “citizen panel” first receive a pre-circulated, plain-language briefing document to spark deliberation about a pressing health and social-system issue. During the panels, citizens then discuss the problem and its causes, options to address it and implementation considerations. The values that they believe should underpin action to address the issue are captured in a panel summary which is used to inform a policy dialogue on the same topic, also organized by the McMaster Health Forum….(More)”.
Book edited by Scott Hawken, Hoon Han and Chris Pettit: “Today the world’s largest economies and corporations trade in data and its products to generate value in new disruptive markets. Within these markets vast streams of data are often inaccessible or untapped and controlled by powerful monopolies. Counter to this exclusive use of data is a promising world-wide “open-data” movement, promoting freely accessible information to share, reuse and redistribute. The provision and application of open data has enormous potential to transform exclusive, technocratic “smart cities” into inclusive and responsive “open-cities”.
This book argues that those who contribute urban data should benefit from its production. Like the city itself, the information landscape is a public asset produced through collective effort, attention, and resources. People produce data through their engagement with the city, creating digital footprints through social medial, mobility applications, and city sensors. By opening up data there is potential to generate greater value by supporting unforeseen collaborations, spontaneous urban innovations and solutions, and improved decision-making insights. Yet achieving more open cities is made challenging by conflicting desires for urban anonymity, sociability, privacy and transparency. This book engages with these issues through a variety of critical perspectives, and presents strategies, tools and case studies that enable this transformation….(More)”.
Mark Coatney at the New York Times: “Social media is an opportunity wrapped in a problem. YouTube spreads propaganda and is toxic to children. Twitter spreads propaganda and is toxic to racial relations. Facebook spreads propaganda and is toxic to democracy itself.
Such problems aren’t surprising when you consider that all these companies operate on the same basic model: Create a product that maximizes the attention you can command from a person, collect as much data as you can about that person, and sell it.
Proposed solutions like breaking up companies and imposing regulation have been met with resistance: The platforms, understandably, worry that their profits might be reduced from staggering to merely amazing. And this may not be the best course of action anyway.
What if the problem is something that can’t be solved by existing for-profit media platforms? Maybe the answer to fixing social media isn’t trying to change companies with business models built around products that hijack our attention, and instead work to create a less toxic alternative.
Nonprofit public media is part of the answer. More than 50 years ago, President Lyndon Johnson signed the Public Broadcasting Act, committing federal funds to create public television and radio that would “be responsive to the interests of people.”
It isn’t a big leap to expand “public media” to include not just television and radio but also social media. In 2019, the definition of “media” is considerably larger than it was in 1967. Commentary on Twitter, memes on Instagram and performances on TikTok are all as much a part of the media landscape today as newspapers and television news.
Public media came out of a recognition that the broadcasting spectrum is a finite resource. TV broadcasters given licenses to use the spectrum were expected to provide programming like news and educational shows in return. But that was not enough. To make sure that some of that finite resource would always be used in the public interest, Congress established public media.
Today, the limited resource isn’t the spectrum — it’s our attention….(More)”.
Paper by Mollie D’Agostino, Paige Pellaton, and Austin Brown: “Dynamic and responsive transportation systems are a core pillar of equitable and sustainable communities. Achieving such systems requires comprehensive mobility data, or data that reports the movement of individuals and vehicles. Such data enable planners and policymakers to make informed decisions and enable researchers to model the effects of various transportation solutions. However, collecting mobility data also raises concerns about privacy and proprietary interests.
This issue paper provides an overview of the top needs and challenges surrounding mobility data sharing and presents four relevant policy strategies: (1) Foster voluntary agreement among mobility providers for a set of standardized data specifications; (2) Develop clear data-sharing requirements designed for transportation network companies and other mobility providers; (3) Establish publicly held big-data repositories, managed by third parties, to securely hold mobility data and provide structured access by states, cities, and researchers; (4) Leverage innovative land-use and transportation-planning tools….(More)”.
Report by the Center for Data Innovation: “From screening chemical compounds to optimizing clinical trials to improving post-market surveillance of drugs, the increased use of data and better analytical tools such as artificial intelligence (AI) hold the potential to transform drug development, leading to new treatments, improved patient outcomes, and lower costs. However, achieving the full promise of data-driven drug development will require the U.S. federal government to address a number of obstacles. This should be a priority for policymakers for two main reasons. First, enabling data-driven drug development will accelerate access to more effective and affordable treatments. Second, the competitiveness of the U.S. biopharmaceutical industry is at risk so long as these obstacles exist. As other nations, particularly China, pursue data-driven innovation, especially greater use of AI, foreign life sciences firms could become more competitive at drug development….(More)”.
GovTech: “The New York state comptroller tasked his staff with analyzing the deployment of new technologies at the municipal level while cautioning local leaders and the public about cyberthreats.
New York Comptroller Thomas DiNapoli announced the report, Smart Solutions Across the State: Advanced Technology in Local Governments, during a press conference last week in Schenectady, which was featured in the 25-page document for its deployment of an advanced streetlight network.
“New technologies are reshaping how local government services are delivered,” DiNapoli said during the announcement. “Local officials are stepping up to meet the evolving expectations of residents who want their interactions with government to be easy and convenient.”
The report showcases online bill payment for people to resolve parking tickets, utilities and property taxes; bike-share programs using mobile apps to access bicycles in downtown areas; public Wi-Fi through partnerships with telecommunication companies; and more….The modernization of communities across New York could create possibilities for partnerships between municipalities, counties and the state, she said. The report details how a city might attempt to emulate some of the projects included. Martinez said local government leaders should collaborate and share best practices if they decide to innovate their jurisdictions in similar ways….(More)”.
Jacqueline Hicks at the Conversation: “There is a global standoff going on about who stores your data. At the close of June’s G20 summit in Japan, a number of developing countries refused to sign an international declaration on data flows – the so-called Osaka Track. Part of the reason why countries such as India, Indonesia and South Africa boycotted the declaration was because they had no opportunity to put their own interests about data into the document.
With 50 other signatories, the declaration still stands as a statement of future intent to negotiate further, but the boycott represents an ongoing struggle by some countries to assert their claim over the data generated by their own citizens.
Back in the dark ages of 2016, data was touted as the new oil. Although the metaphor was quickly debunked it’s still a helpful way to understand the global digital economy. Now, as international negotiations over data flows intensify, the oil comparison helps explain the economics of what’s called “data localisation” – the bid to keep citizens’ data within their own country.
Just as oil-producing nations pushed for oil refineries to add value to crude oil, so governments today want the world’s Big Tech companies to build data centres on their own soil. The cloud that powers much of the world’s tech industry is grounded in vast data centres located mainly around northern Europe and the US coasts. Yet, at the same time, US Big Tech companies are increasingly turning to markets in the global south for expansion as enormous numbers of young tech savvy populations come online….(More)”.
Book by Megh R. Goyal and Emmanuel Eilu: “… explores how digital media and wireless communication, especially mobile phones and social media platforms, offer concrete opportunities for developing countries to transform different sectors of their economies. The volume focuses on the agricultural, economic, and education sectors. The chapter authors, mostly from Africa and India, provide a wealth of information on recent innovations, the opportunities they provide, challenges faced, and the direction of future research in digital media and wireless communication to leverage transformation in developing countries….(More)”.
Linda Nordling at Nature: “When data scientists in Chicago, Illinois, set out to test whether a machine-learning algorithm could predict how long people would stay in hospital, they thought that they were doing everyone a favour. Keeping people in hospital is expensive, and if managers knew which patients were most likely to be eligible for discharge, they could move them to the top of doctors’ priority lists to avoid unnecessary delays. It would be a win–win situation: the hospital would save money and people could leave as soon as possible.
Starting their work at the end of 2017, the scientists trained their algorithm on patient data from the University of Chicago academic hospital system. Taking data from the previous three years, they crunched the numbers to see what combination of factors best predicted length of stay. At first they only looked at clinical data. But when they expanded their analysis to other patient information, they discovered that one of the best predictors for length of stay was the person’s postal code. This was puzzling. What did the duration of a person’s stay in hospital have to do with where they lived?
As the researchers dug deeper, they became increasingly concerned. The postal codes that correlated to longer hospital stays were in poor and predominantly African American neighbourhoods. People from these areas stayed in hospitals longer than did those from more affluent, predominantly white areas. The reason for this disparity evaded the team. Perhaps people from the poorer areas were admitted with more severe conditions. Or perhaps they were less likely to be prescribed the drugs they needed.
The finding threw up an ethical conundrum. If optimizing hospital resources was the sole aim of their programme, people’s postal codes would clearly be a powerful predictor for length of hospital stay. But using them would, in practice, divert hospital resources away from poor, black people towards wealthy white people, exacerbating existing biases in the system.
“The initial goal was efficiency, which in isolation is a worthy goal,” says Marshall Chin, who studies health-care ethics at University of Chicago Medicine and was one of the scientists who worked on the project. But fairness is also important, he says, and this was not explicitly considered in the algorithm’s design….(More)”.