Why no one is reading your coronavirus emails

Curated on Posted on by Stefaan Verhulst

Opinion by Todd Rogers: “…As a behavioral scientist, I study how people make decisions and process information, and I develop communications to change behavior for the better. And if there’s one lesson all the coronavirus email writers should take, it’s this: Messages should be as easy to understand as possible. This is difficult in normal times — and is no doubt much more so with facts on the ground changing as rapidly as they are….

As an illustration of how potent simplifying messaging can be, Carly Robinson at Harvard, Jessica Lasky-Fink of the University of California, Berkeley, Hedy Chang of Attendance Works and I conducted an experiment with a large school district, in which we rewrote a state-required notification about attendance.All schools in California are required to send a truancy notification to families after a student is late or absent three times. The state legislature offered recommended language for the notice that was written at a college-reading level and contained 342 words in seven-point font. We rewrote the letter at a 5th grade reading level, in 14-point font and with half as many words. We then randomly assigned 131,312 families to either receive the state-recommended language or a version of our simplified letter.The best version of our simplified letters was an estimated 40% more effective at reducing absences during the subsequent 30 days than the state-recommended language. Writing with an understanding of how humans work turns out to be more effective than writing with the sole goal of complying with the delivery of mandatory written information.So, what can be done to make coronavirus messages, so critical to the functioning of our country right now, easier to understand — and more likely to be read?

  • Write in the most accessible way possible. Use the Flesch-Kincaid readability test (built into Microsoft Word and Google Docs) to test the reading-level complexity of your writing.
  • Use as few words as possible. Shorter messages are more likely to be read (see the long email in your inbox from three months ago that you still have not read).
  • Write in a larger font. This makes long messages look ridiculous and makes it easier to read for recipients with eyesight issues. It also reduces the chance of the accidental — but way too common — occurrence of emails appearing in inboxes with absurdly small font.
  • Eliminate gratuitous borders and images. These can often distract from the message you are trying to send.
  • Use a clear structure. People skim, so help them. As opposed to a multi-paragraph email written in normal prose, consider categorizing information under headings like, “What we want you to know” (or just “KNOW”) and “what we would like you to do” (or, concisely, “DO”). Consider putting content within each category in bullet points….(More)”

Coronavirus, Ray Dalio and forecasting in an age of uncertainty

Curated on Posted on by Stefaan Verhulst

Gillian Tett at the Financial Times: “Predictive models only get you so far. We also need to maintain our peripheral vision…

What is interesting to ponder is what this episode reveals about the nature of forecasting — and our modern attitudes towards time. As anthropologists often point out, the way we think about time is a defining feature of the post-enlightenment world. During much of human history, the future was viewed as a vague and terrifyingly unknowable blur marked by constant bargaining with deities (to ward off disaster) or cyclical seasonal rhythms (of the sort that underscore Buddhist cognitive maps).

In modern, post-enlightenment western cultures, however, a linear vision of time emerged that presumes the past can be extrapolated into the future, with a sense of progression, not just cyclicality.

In the 20th century, this gave birth to the risk management and finance professions, as Peter Bernstein wrote two decades ago in his brilliant book Against the Gods: the Remarkable Story of Risk.

By the turn of the century, innovations such as computing and the internet were turbocharging the forecasting business to an extraordinary degree, as Margaret Heffernan notes in her excellent (and very timely) new book Uncharted. “Human discomfort with uncertainty . . . has fuelled an industry that enriches itself by terrorising us with uncertainty and taunting us with certainty,” she writes.

However, as Heffernan stresses, while the forecasting business has made its “experts” very rich, it is also based on a fallacy: the idea that the future can be neatly extrapolated from the past.

Moreover, the apparent success of some pundits in predicting events (such as the 2008 crash) makes them so overconfident that they get locked into particularly rigid models. “The harder economists try to identify sure-fire methods of predicting markets, the more such insight eludes them,” she writes. Is there a solution? Heffernan’s answer is to embrace uncertainty, build resilience, use “narrative” (or qualitative) analyses instead of rigid models and to respect the wisdom of diverse views to avoid tunnel vision….(More)”.

The Coronavirus Crisis Is Showing Us How to Live Online

Curated on Posted on by Stefaan Verhulst

Kevin Roose at The New York Times:”…There is no use sugarcoating the virus, which has already had devastating consequences for people all over the world, and may get much worse in the months ahead. There will be more lives lost, businesses closed and communities thrown into financial hardship. Nobody is arguing that what is coming will be fun, easy or anything remotely approaching normal for a very long time.

But if there is a silver lining in this crisis, it may be that the virus is forcing us to use the internet as it was always meant to be used — to connect with one another, share information and resources, and come up with collective solutions to urgent problems. It’s the healthy, humane version of digital culture we usually see only in schmaltzy TV commercials, where everyone is constantly using a smartphone to visit far-flung grandparents and read bedtime stories to kids.

Already, social media seems to have improved, with more reliable information than might have been expected from a global pandemic. And while the ways we’re substituting for in-person interaction aren’t perfect — over the next few months in America, there may be no phrase uttered more than “Can someone mute?” — we are seeing an explosion of creativity as people try to use technology as a bridge across physical distances.

Just look at what’s happening in Italy, where homebound adults are posting mini-manifestos on Facebook, while restless kids flock to multiplayer online games like Fortnite. Or see what’s happening in China, where would-be partyers have invented “cloud clubbing,” a new kind of virtual party in which D.J.s perform live sets on apps like TikTok and Douyin while audience members react in real time on their phones. Or observe how we’re coping in the United States, where groups are experimenting with new kinds of socially distanced gatherings: virtual yoga classes, virtual church services, virtual dinner parties.

These are the kinds of creative digital experiments we need, and they are coming at a time when we need them more than ever….(More)”

Personal privacy matters during a pandemic — but less than it might at other times

Curated on Posted on by Stefaan Verhulst

Nicole Wetsman at the Verge: “…The balance between protecting individual privacy and collecting information that is critical to the public good changes over the course of a disease’s spread. The amount of data public health officials need to collect and disclose changes as well. Right now, the COVID-19 pandemic is accelerating, and there is still a lot doctors and scientists don’t know about the disease. Collecting detailed health information is, therefore, more useful and important. That could change as the outbreak progresses, Lee says.

For example, as the virus starts to circulate in the community, it might not be as important to know exactly where a sick person has been. If the virus is everywhere already, that information won’t have as much additional benefit to the community. “It depends a lot on the maturity of an epidemic,” she says.

Digital tracking information is ubiquitous today, and that can make data collection easier. In Singapore, where there’s extensive surveillance, publicly available data details where people with confirmed cases of COVID-19 are and have been. The Iranian government built an app for people to check their symptoms that also included a geo-tracking feature. When deciding to use those types of tools, Lee says, the same public health principles should still apply.

“Should a public health official know where a person has gone, should that be public information — it’s not different. It’s a lot easier to do that now, but it doesn’t make it any more right or less right,” she says. “Tracking where people go and who they interact with is something public health officials have been doing for centuries. It’s just easier with digital information.”

In addition, just because personal information about a person and their health is important to a public health official, it doesn’t mean that information is important for the general public. It’s why, despite questioning from reporters, public health officials only gave out a limited amount of information on the people who had the first few cases of COVID-19 in the US…

Health officials worry about the stigmatization of individuals or communities affected by diseases, which is why they aim to disclose only necessary information to the public. Anti-Asian racism in the US and other countries around the world spiked with the outbreak because the novel coronavirus originated in China. People who were on cruise ships with positive cases reported fielding angry phone calls from strangers when they returned home, and residents of New Rochelle, New York, which is the first containment zone in the US, said that they’re worried about their hometown being forever associated with the virus.

“This kind of group-level harm is concerning,” Lee says. “That’s why we worry about group identity privacy, as well. I’m nervous and sad to see that starting to poke its head out.”

People can’t expect the same level of personal health privacy during public health emergencies involving infectious diseases as they can in other elements of their health. But the actions public health officials can take, like collecting information, aren’t designed to limit privacy, Fairchild says. “It’s to protect the broader population. The principle we embrace is the principle of reciprocity. We recognize that our liberty is limited, but we are doing that for others.”…(More)”.

Coronavirus: seven ways collective intelligence is tackling the pandemic

Curated on Posted on by Stefaan Verhulst

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).

How Taiwan Used Big Data, Transparency and a Central Command to Protect Its People from Coronavirus

Curated on Posted on by Stefaan Verhulst

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)”.

France asks its citizens how to meet its climate-change targets

Curated on Posted on by Stefaan Verhulst

The Economist on “An experiment in consultative democracy”: “A nurse, a roofer, an electrician, a former fireman, a lycée pupil, a photographer, a teacher, a marketing manager, an entrepreneur and a civil servant. Sitting on red velvet benches in a domed art-deco amphitheatre in Paris, they and 140 colleagues are part of an unusual democratic experiment in a famously centralised country. Their mission: to draw up measures to reduce French greenhouse-gas emissions by at least 40% by 2030, in line with an eu target that is otherwise in danger of being missed (and which the European Commission now wants to tighten). Six months ago, none of them had met. Now, they have just one month left to show that they can reinvent the French democratic process—and help save the planet. “It’s our moment,” Sylvain, one of the delegates, tells his colleagues from the podium. “We have the chance to propose something historic.”

On March 6th the “citizens’ climate convention” was due to begin its penultimate three-day sitting, the sixth since it began work last October. The convention is made up of a representative sample of the French population, selected by randomly generated telephone numbers. President Emmanuel Macron devised it in an attempt to calm the country after the gilets jaunes (yellow jackets) crisis of 2018. In response to the demand for less top-down decision-making, he first launched what he grandly called a “great national debate”, which took place a year ago. He also pledged the creation of a citizens’ assembly. It is designed to focus on precisely the conundrum that provoked the original protests against a rise in the carbon tax on motor fuel: how to make green policy palatable, efficient and fair.Already signed up?…(More)”.

Is Your Data Being Collected? These Signs Will Tell You Where

Curated on Posted on by Stefaan Verhulst

Flavie Halais at Wired: “Alphabet’s Sidewalk Labs is testing icons that provide “digital transparency” when information is collected in public spaces….

As cities incorporate digital technologies into their landscapes, they face the challenge of informing people of the many sensors, cameras, and other smart technologies that surround them. Few people have the patience to read through the lengthy privacy notice on a website or smartphone app. So how can a city let them know how they’re being monitored?

Sidewalk Labs, the Google sister company that applies technology to urban problems, is taking a shot. Through a project called Digital Transparency in the Public Realm, or DTPR, the company is demonstrating a set of icons, to be displayed in public spaces, that shows where and what kinds of data are being collected. The icons are being tested as part Sidewalk Labs’ flagship project in Toronto, where it plans to redevelop a 12-acre stretch of the city’s waterfront. The signs would be displayed at each location where data would be collected—streets, parks, businesses, and courtyards.

Data collection is a core feature of the project, called Sidewalk Toronto, and the source of much of the controversy surrounding it. In 2017, Waterfront Toronto, the organization in charge of administering the redevelopment of the city’s eastern waterfront, awarded Sidewalk Labs the contract to develop the waterfront site. The project has ambitious goals: It says it could create 44,000 direct jobs by 2040 and has the potential to be the largest “climate-positive” community—removing more CO2 from the atmosphere than it produces—in North America. It will make use of new urban technology like modular street pavers and underground freight delivery. Sensors, cameras, and Wi-Fi hotspots will monitor and control traffic flows, building temperature, and crosswalk signals.

All that monitoring raises inevitable concerns about privacy, which Sidewalk aims to address—at least partly—by posting signs in the places where data is being collected.

The signs display a set of icons in the form of stackable hexagons, derived in part from a set of design rules developed by Google in 2014. Some describe the purpose for collecting the data (mobility, energy efficiency, or waste management, for example). Others refer to the type of data that’s collected, such as photos, air quality, or sound. When the data is identifiable, meaning it can be associated with a person, the hexagon is yellow. When the information is stripped of personal identifiers, the hexagon is blue…(More)”.

Good process is vital for good government

Curated on Posted on by Stefaan Verhulst

Andrea Siodmok and Matthew Taylor at the RSA: “…‘Bad’ process is time wasting and energy sapping. It can reinforce barriers to collaboration, solidify hierarchies and hamper adaptiveness.

‘Good process’ energises people, creates spaces for different ideas to emerge, builds trust and collective capacity.

The bad and good could be distinguished along several dimensions. Here are some:

Bad process:

  • Routine/happens because it happens            
  • Limited preparation and follow through         
  • Little or no facilitation            
  • Reinforces hierarchies, excludes key voices  
  • Rigid accountability focussed on blame           
  • Always formal and mandated           
  • Low trust/transactional       

Good process:

  • Mission/goal oriented – happens because it makes a difference
  • Sees process as part of a flow of change – clear accountability
  • Facilitated by people with necessary skills and techniques 
  • Inclusive, what matters is the quality of contributions not their source
  • Collective accountability focussed on learning 
  • Mixes formal and informal settings and methods, often voluntary
  • Trust enhancing/collaborative

Why is bad process so prevalent and good process so rare?

Because bad process is often the default. In the short term, bad process is easier, less intensive-resource, and less risky than good process.

Bringing people together in inclusive processes

Bringing key actors together in inclusive processes help us both understand the system that is maintaining the status quo and building a joint sense of mission for a new status quo.

It also helps people start to identify and organise around key opportunities for change. 

One of the most positive developments to have occurred in and around Whitehall in recent years is the emergence of informal, system spanning networks of public officials animated by shared values and goals such as One Team Gov and a whole host of bottom up networks on topics as diverse as wellbeing, inclusion, and climate change….(More)”.

How Singapore sends daily Whatsapp updates on coronavirus

Curated on Posted on by Stefaan Verhulst

Medha Basu at GovInsider: “How do you communicate with citizens as a pandemic stirs fear and spreads false news? Singapore has trialled WhatsApp to give daily updates on the Covid-19 virus.

The World Health Organisation’s chief praised Singapore’s reaction to the outbreak. “We are very impressed with the efforts they are making to find every case, follow up with contacts, and stop transmission,” Tedros Adhanom Ghebreyesus said.

Since late January, the government has been providing two to three daily updates on cases via the messaging app. “Fake news is typically propagated through Whatsapp, so messaging with the same interface can help stem this flow,” Sarah Espaldon, Operations Marketing Manager from Singapore’s Open Government Products unit told GovInsider….

The niche system became newly vital as Covid-19 arrived, with fake news and fear following quickly in a nation that still remembers the fatal SARS outbreak of 2003. The tech had to be upgraded to ensure it could cope with new demand, and get information out rapidly before misinformation could sow discord.

The Open Government Products team used three tools to adapt Whatsapp and create a rapid information sharing system.

1. AI Translation

Singapore has four official languages – Chinese, English, Malay and Tamil. Government used an AI tool to rapidly translate the material from English, so that every community receives the information as quickly as possible.

An algorithm produces the initial draft of the translation, which is then vetted by civil servants before being sent out on WhatsApp. The AI was trained using text from local government communications so is able to translate references and names of Singapore government schemes. This project was built by the Ministry of Communication and Information and Agency for Science, Technology and Research in collaboration with GovTech.

2. Make it easy to sign up

People specify their desired language through an easy sign up form. Singapore used Form.Sg, a tool that allows officials to launch a new mailing list in 30 minutes and connect to other government systems. A government-built form ensures that data is end-to-end encrypted and connected to the government cloud.

3. Fast updates

The updates were initially too slow in reaching people. It took four hours to add new subscribers to the recipient list and the system could send only 10 messages per second. “With 500,000 subscribers, it would take almost 14 hours for the last person to get the message,” Espaldon says….(More)”.