Stefaan Verhulst

Chapter by Artur Rot, Małgorzata Sobińska, Marcin Hernes, and Bogdan Franczyk: “Proper understanding of blockchain technology is one of key importance for decision-makers and staff in public administration sectors, as it helps them decide whether this approach can be of practical use in the realisation of their statutory mission. Blockchain technology is often perceived as a failsafe and unbreakable system with potential to transform many segments of the economy. Blockchain solutions have already been employed with success as basis for digital transactions in such areas as electricity market, trade, cryptocurrencies, stock trading, etc. Their application potential is also actively explored in other sectors of the economy, such as banking, insurance, and public administration.

Blockchain technology can be approached not only as an innovative solution, but also as a tool for effective creation of novel management practices and models of operation in various types of organizations and institutions. The contribution of the chapter is an evaluation of potential uses and conditions for the effective application of the blockchain technology in the public administration sector. The study is constructed on the fundament of literature studies, empirical observations, case study analyses and synthetic evaluations, with the aim of revealing the potential applications of the blockchain technology and highlighting the challenges and possible directions of blockchain research in the public sector….(More)”.

Article by Kathy Peach: “Tackling the emergence of a new global pandemic is a complex task. But collective intelligence is now being used around the world by communities and governments to respond.

At its simplest, collective intelligence is the enhanced capacity created when distributed groups of people work together, often with the help of technology, to mobilise more information, ideas and insights to solve a problem.

Advances in digital technologies have transformed what can be achieved through collective intelligence in recent years – connecting more of us, augmenting human intelligence with machine intelligence, and helping us to generate new insights from novel sources of data. It is particularly suited to addressing fast-evolving, complex global problems such as disease outbreaks.

Here are seven ways it is tackling the coronavirus pandemic:

1. Predicting and modelling outbreaks

On the December 31, 2019, health monitoring platform Blue Dot alerted its clients to the outbreak of a flu-like virus in Wuhan, China – nine days before the World Health Organization (WHO) released a statement about it. It then correctly predicted that the virus would jump from Wuhan to Bangkok, Seoul, Taipei and Tokyo.

Blue Dot combines existing data sets to create new insights. Natural language processing, the AI methods that understand and translate human-generated text, and machine learning techniques that learn from large volumes of data, sift through reports of disease outbreaks in animals, news reports in 65 languages, and airline passenger information. It supplements the machine-generated model with human intelligence, drawing on diverse expertise from epidemiologists to veterinarians and ecologists to ensure that its conclusions are valid.

2. Citizen science

The BBC carried out a citizen science project in 2018, which involved members of the public in generating new scientific data about how infections spread. People downloaded an app that monitored their GPS position every hour, and asked them to report who they had encountered or had contact with that day….(More).

Michael Hallsworth at Behavioral Scientist: “Why don’t we wash our hands as much as we should?

Behavioral science can help identify some of the key barriers. It may also suggest what might make a difference for COVID-19 in the absence of a vaccine, recognizing that there is much we still do not know about this virus.

The first barrier may be a lack of awareness about the effectiveness of soap, water, and scrubbing. People may simply not realize how well specific handwashing actions can prevent the spread of infectious disease. This is why many public health agencies run educational campaigns, which may have varying effects based on how far they take evidence about behavior into account.

For example, last weekend the Behavioural Insights Team (BIT), the organization for which I work, ran a set of online trials with 3,500 U.K. adults to test the impact of various posters on people’s intended handwashing behavior. We found that posters seemed to have stronger effects on people who were already washing their hands more frequently. In other words, the more compliant people got more compliant. Obviously, this is a real problem for infection control.

One specific issue with COVID-19 may be that people’s attention is being drawn to something else instead: face masks. In many countries, face masks in public are uncommon. Therefore, people in these places are more likely to notice when others are wearing masks, since doing so is visible and novel—unlike washing of hands! This may create the perception that wearing a face mask is the priority for preventing infection.

There are benefits from face masks, but we still lack evidence about how they are used or whether they work if worn by people who are not yet infected. At least one study suggests that on their own they may be less effective than handwashing at preventing transmission. And given that there’s a limited supply, face masks need to be reserved for the people and situations where they can do the most good.

Perhaps the main concern is that people may have a risk thermostat, whereby taking protective measures in one area means that they feel greater license to take risks in another. Obtaining a face mask may make people feel more protected and could mean they make less of an effort to wash their hands adequately.

Awareness is unlikely to be enough on its own. We also need to consider availability. In some instances, there are practical barriers to handwashing—water, soap, and drying materials may not be available. People may be aware of what they should do but be unable to follow through. One obvious solution is to increase the provision of alcohol-based hand sanitizer dispensers at locations where handwashing is infeasible. Doing this has been shown to improve hand hygiene on its own.

However, behavioral science shows that not all “availability” is equal: even small increases in required effort may result in a hand sanitizer going unused. Therefore, those providing hand sanitizer should also consider whether they’ve made usage as convenient as possible. How can dispensers be located so people do not have to make detours to use them? How can the dispensers be made more prominent—like the use of color? Where do people normally have to pause, thus making them more open to usage—like waiting for an elevator?…(More)”.

Book by Dan Heath: “So often in life, we get stuck in a cycle of response. We put out fires. We deal with emergencies. We stay downstream, handling one problem after another, but we never make our way upstream to fix the systems that caused the problems. Cops chase robbers, doctors treat patients with chronic illnesses, and call-center reps address customer complaints. But many crimes, chronic illnesses, and customer complaints are preventable. So why do our efforts skew so heavily toward reaction rather than prevention?

Upstream probes the psychological forces that push us downstream—including “problem blindness,” which can leave us oblivious to serious problems in our midst. And Heath introduces us to the thinkers who have overcome these obstacles and scored massive victories by switching to an upstream mindset. One online travel website prevented twenty million customer service calls every year by making some simple tweaks to its booking system. A major urban school district cut its dropout rate in half after it figured out that it could predict which students would drop out—as early as the ninth grade. A European nation almost eliminated teenage alcohol and drug abuse by deliberately changing the nation’s culture. And one EMS system accelerated the emergency-response time of its ambulances by using data to predict where 911 calls would emerge—and forward-deploying its ambulances to stand by in those areas.

Upstream delivers practical solutions for preventing problems rather than reacting to them. How many problems in our lives and in society are we tolerating simply because we’ve forgotten that we can fix them?…(More)”.

Press Release: “…the 2019 INRIX Global Traffic Scorecard… identified, analyzed and ranked congestion and mobility trends in more than 900 cities, across 43 countries. To reflect an increasingly diverse mobility landscape, the 2019 Global Traffic Scorecard includes both public transport and biking metrics for the first time….

At the global level, Bogota topped the list of the cities most impacted by traffic congestion with drivers losing 191 hours a year to congestion, followed by Rio de Janeiro (190 hours), Mexico City (158 hours) and Istanbul (150 hours). Latin American and European cities again dominated the Top 10, highlighting the rapid urbanisation occurring in Latin America and historic European cities that took shape long before the age of automobile….

INRIX fuses anonymous data from diverse datasets – such as phones, cars, trucks and cities – that leads to robust and accurate insights. The data used in the 2019 Global Traffic Scorecard is the congested or uncongested status of every segment of road for every minute of the day, as used by millions of drivers around the world that rely on INRIX-based traffic services….(More)”

Press Release: “Just a few years ago, Americans were overwhelmingly optimistic about the power of new technologies to foster an informed and engaged society. More recently, however, that confidence has been challenged by emerging concerns over the role that internet and technology companies — especially social media — now play in our democracy.

A new Knight Foundation and Gallup study explores how much the landscape has shifted. This wide-ranging study confirms that, for Americans, the techlash is real, widespread, and bipartisan. From concerns about the spread of misinformation to election interference and data privacy, we’ve documented the deep pessimism of folks across the political spectrum who believe tech companies have too much power — and that they do more harm than good. 

Despite their shared misgivings, Americans are deeply divided on how best to address these challenges. This report explores the contours of the techlash in the context of the issues currently animating policy debates in Washington and Silicon Valley. Below are the main findings from the executive summary….

• 77% of Americans say major internet and technology companies like Facebook, Google, Amazon and Apple have too muchpower.
• Americans are equally divided among those who favor (50%) and oppose (49%) government intervention that would require internet and technology companies to break into smaller companies. 
• Americans do not trust social media companies much (44%) or at all (40%) to make the right decisions about what content should or should not be allowed on online platforms.
• However, they would still prefer the companies (55%) to make those decisions rather than the government (44%). …(More)“

Article by Cathy Cosgrove: “Managing the COVID-19 outbreak and stopping its spread is now a global challenge. In addition to the significant health and medical responses underway around the world, governments and public health officials are focused on how to monitor, understand and prevent the spread of the virus. Data protection and privacy laws, including the EU General Data Protection Regulation and various U.S. laws, are informing these responses.

One major response to limiting the spread of infection is contact tracing, which is the practice of identifying and monitoring anyone who may have come into contact with an infected person. Employers and educational institutions are also imposing travel restrictions, instituting self-quarantine policies, limiting visitors, and considering whether to require medical examinations. These responses necessarily involve obtaining and potentially sharing personal information, including data about an individual’s health, travel, personal contacts, and employment. For example, in the U.S., the Centers for Disease Control and Prevention has asked airlines for the name, date of birth, address, phone number and email address for passengers on certain flights. 

As IAPP Editorial Director Jedidiah Bracy, CIPP, explored in his piece on balancing personal privacy with public interest last week, this collection and processing of personal data is creating substantial discussion about what data protection limitations may be required or appropriate. Even China — which is using AI and big data to manage the outbreak — has issued guidance recognizing the need to limit the collection of data and its use during this public health crisis….(More)”.

Paper by Ilona M. Otto et al: “…In this paper, we examine a number of potential “social tipping elements” (STEs) for decarbonization that represent specific subdomains of the planetary social-economic system. Tipping of these subsystems could be triggered by “social tipping interventions” (STIs) that could contribute to rapid transition of the world system into a state of net zero anthropogenic greenhouse gas emissions. The results reported in this study are based on an online expert survey, an expert workshop, and an extensive literature review (SI Appendix).

Our results complement the existing shared socioeconomic pathways (SSPs) that are used alongside the representative concentration pathways (RCPs) to analyze the feedbacks between climate change and socioeconomic factors, such as world population growth, economic development, and technological progress. Our results could be useful for exploring possible transformative pathways leading to scenarios that reach net zero emissions by 2050.

…Various types of tipping processes can be differentiated in the literature. Many authors refer to critical thresholds , a notion closely related to the metaphor of a “butterfly effect”. Other processes related to tipping dynamics include metamorphosis, where a rapid loss of structures of one sort occurs simultaneously with the development of new structures, as well as cascades driven by positive feedbacks in processes occurring simultaneously at smaller scales.

The social tipping dynamics of interest for this study are typically manifested as spreading processes in complex social networks of behaviors, opinions, knowledge, technologies, and social norms, including spreading processes of structural change and reorganization. These spreading processes resemble contagious dynamics observed in epidemiology that spread through social networks. Once triggered, such processes can be irreversible and difficult to stop. Similar contagious dynamics have been observed in human behavior, for example in assaultive violence, participation in social movements, or health-related behaviors and traits, such as smoking or obesity..(More)”.

An interview with Malka Older: “…Nisa: There’s a line in your first book, “Democracy is of limited usefulness when there are no good choices, or when all the information access in the world can’t make people use it.” So imagine this world you’ve imagined has a much higher demand for free and accurate information access than we have now, in exchange for a fairly high amount of state surveillance. I’m curious what else we give up when we allow that amount of surveillance into our communities and whether that trade-off is necessary.

Malka: The amount of surveillance in the books is a very gentle extrapolation from where we are now. I don’t know if they need to be that connected but I do feel like privacy is a very relative concept. The way that we think of privacy now is very different than the way that it’s been thought of in the past, or the way it’s thought of in different places, and it’s very hard to put that back in the box. I was thinking more in terms of, since we are giving up our privacy anyway, what would I like to see done with all this information? Most of the types of surveillance that I mentioned are already very much in place. It’s hard to walk down the street without seeing surveillance cameras — they’re in private businesses, outside of apartment buildings, in lobbies, and buses and trains and pretty much everywhere.  We already know that whatever we do online is recorded and tracked in some way. If we have smartphones—which I don’t, I’m trying to resist, although it’s getting harder and harder—pretty much all of our movements are being tracked that way. The difference from the book is that the current situation of surveillance is very fragmented, and a combination of private sector and public sector, as opposed to one monolithic organization. Although, it’s not clear how different it really is from our present when governments are able to subpoena information from the private sector. The other part is that we give away a lot of this information, if not all of it, whenever we accept the terms of service agreements. We’re basically saying, in exchange for having this cool phone, I will let you use my data. But we’re learning that companies are often going far beyond what we legally agreed to, and even what we legally agree to is done in such convoluted terms and there’s an imbalance of information to begin with. That’s really problematic. Rather than thinking in terms of privacy as a kind of absolute or in terms of surveillance, I tend to think more about who owns the data, who has access to the data. The real problem is not just that there are cameras everywhere, but that we don’t know who is watching those cameras or who is able to access those cameras at any given time. Similarly, the fact that all of our online data is being recorded is not necessarily a huge problem, except when we have no way of knowing what the data is contributing to when it’s amalgamated and no recourse or control over how it’s eventually used. All this data that we create in our online trails being in the hands of a corporation that does not need to share it or reveal it, and is using it to make money, or all of that data being available to everybody or held under some sort of very clear and equitable terms where we have much more choice about what’s it’s used for and where we could access our own data. For me, it’s very much about the power structures involved….(More)”.

Article by Beth Duff-Brown: “…So what steps did Taiwan take to protect its people? And could those steps be replicated here at home?

Stanford Health Policy’s Jason Wang, MD, PhD, an associate professor of pediatrics at Stanford Medicine who also has a PhD in policy analysis, credits his native Taiwan with using new technology and a robust pandemic prevention plan put into place at the 2003 SARS outbreak.

“The Taiwan government established the National Health Command Center (NHCC) after SARS and it’s become part of a disaster management center that focuses on large-outbreak responses and acts as the operational command point for direct communications,” said Wang, a pediatrician and the director of the Center for Policy, Outcomes, and Prevention at Stanford. The NHCC also established the Central Epidemic Command Center, which was activated in early January.

“And Taiwan rapidly produced and implemented a list of at least 124 action items in the past five weeks to protect public health,” Wang said. “The policies and actions go beyond border control because they recognized that that wasn’t enough.”

Wang outlines the measures Taiwan took in the last six weeks in an article published Tuesday in the Journal of the American Medical Association.

“Given the continual spread of COVID-19 around the world, understanding the action items that were implemented quickly in Taiwan, and the effectiveness of these actions in preventing a large-scale epidemic, may be instructive for other countries,” Wang and his co-authors wrote.

Within the last five weeks, Wang said, the Taiwan epidemic command center rapidly implemented those 124 action items, including border control from the air and sea, case identification using new data and technology, quarantine of suspicious cases, educating the public while fighting misinformation, negotiating with other countries — and formulating policies for schools and businesses to follow.

Big Data Analytics

The authors note that Taiwan integrated its national health insurance database with its immigration and customs database to begin the creation of big data for analytics. That allowed them case identification by generating real-time alerts during a clinical visit based on travel history and clinical symptoms.

Taipei also used Quick Response (QR) code scanning and online reporting of travel history and health symptoms to classify travelers’ infectious risks based on flight origin and travel history in the last 14 days. People who had not traveled to high-risk areas were sent a health declaration border pass via SMS for faster immigration clearance; those who had traveled to high-risk areas were quarantined at home and tracked through their mobile phones to ensure that they stayed home during the incubation period.

The country also instituted a toll-free hotline for citizens to report suspicious symptoms in themselves or others. As the disease progressed, the government called on major cities to establish their own hotlines so that the main hotline would not become jammed….(More)”.