Website design is still more amateur than professional. Most websites would not pass a basic quality control test.

There is nothing more basic on the Web than the speed at which a page downloads. Fast downloading pages have passed the first mark of quality. Slow downloading pages fail.

In 2019, Backlinko, a search engine optimization company analyzed five million desktop and mobile pages to learn which factors impact page speed. Key findings:
• Desktop pages were on average taking 10.3 seconds to load.
• Mobile pages were on average taking 27.3 seconds to load.

It’s hard to actually believe these figures. They don’t seem credible but if you follow the link at the bottom of this page you will see that Backlinko back up their estimates with a lot of hard data and research.

For years best practice has been that it should not take more than two seconds for a page to download on desktop and no more than three seconds for mobile. These are the upper limits. Could it be that millions of people out there using standard smartphones are essentially banned from using millions of websites because they are so slow to load?

“The average connection speed for U.S. mobile users has increased steadily in the past 10 years; meanwhile, the load times for mobile web pages over the same period have more than doubled,” Kathryn Whitenton wrote for Nielsen Norman in May 2020.

In the last ten years, the Internet has gotten roughly twenty times faster. That’s not a typo. It’s got twenty times faster. That doesn’t make sense. If the Internet has gotten twenty times faster how come a great many websites have got slower?

Because of terrible, lazy, bloated design. Digital is a horribly wasteful industry. Digital crap may not smell but it sure does stink. And because the Internet has gotten so much faster we as an industry have been able to hide our bad, lazy, self-obsessed, ego-driven behavior.

I remember back in 1997, I think, sitting in a restaurant in Galway discussing with someone the best way to optimize images. In 2020, I still find images on websites that are over a megabyte in weight. Eight out of ten people I meet in digital could care less about page weight or performance. Why are we such slow learners?

Imagine if people in the digital industry were designing cars. We have all these super-amazing highways that we can drive our cars down. We’d have designed cars that looked like Ferraris. But once you put you foot on the accelerator they’d behave like tractors trundling down the superhighway spewing out fume and toxins on the way.

Because these super-heavy websites come at a great and increasing cost to the environment. I calculated that if you have a webpage that is 4 MB (the current average page weight) and if it is downloaded 600,000 times, you’d need to plant one tree to deal with the resulting pollution. Because one tree can absorb about 10 kg of CO2 per year and that’s the amount of pollution downloading such a page 600,000 times causes.

We are killing the Web and we are killing the planet because of our endlessly wasteful, lazy, ego-driven web design and development. Are we okay with that?

The Need for Speed, 23 Years Later, Nielsen Norman Group

Backlinko page speed study

Here’s the classification we tested in round two:
WHO, Government Guidance, Education, Training
Mental, Physical Wellbeing
Vaccine, Immunity, Treatment
Research, Statistics
Virus Survival, Spread, Mutation
Avoiding Infection
Symptoms, Diagnosis
News
End Date, New Outbreaks
At Risk, Vulnerable

With this classification we got a success rate of 77%, which was 17% higher than for round one. Our target is to get to 80%.

The three transmission-related tasks had an average success rate of 37% in round one. To address this problem, a new class was created: “Virus Survival, Spread, Mutation”. In round two the success rate almost doubled to 68%. There were no major indications that the new class was behaving as a dirty magnet (drawing clicks for tasks it was not supposed to draw clicks for).

The other new class, “At Risk, Vulnerable” worked even better, with a success rate of 82%. Its dirty magnet impact was negligible.

Behavior was very consistent between rounds. For example, in round one, 80% selected “Vaccine, Immunity, Treatment” for the task, “Have any drugs been approved for use on COVID-19?” In round two, it was 81%. In round one, 79% selected “Research, Statistics” for the task, “Find a chart that shows the trend / curve of coronavirus cases over time in Brazil.” In round two, it was 81%.

If you test 30 or so task instructions, you are always going to have one or two that will perform badly and that there’s nothing much you can do about. “What lessons have been learned about using ventilators?” was an instruction to test the task “Treatment lessons learned, emerging best practice, failed treatments”. We expected people would select the “Vaccine, Immunity, Treatment” class. In round one, it had a success rate of 35%, with 31% selecting “Research, Statistics” and 19% selecting “WHO, Government Guidance, Education, Training”. An argument could be made that an answer could be found under research, but this is a slippery slope. You could argue that practically anything might be found under research. You could argue that WHO guidance might address ventilators. However, ventilators are a part of the treatment process and if lessons have been learned then you should definitely be able to find that sort of information under the “Vaccine, Immunity, Treatment” class.

Specific changes we made in round two included:
• The task “Likely course of illness, outcomes, prognosis” had the instruction, “What is a typical prognosis, likely course for COVID-19?”. “Symptoms, Diagnosis” was designated at the correct path. However, in round one and two, 17% of people selected “Vaccine, Immunity, Treatment”. Seeing that prognosis is part of the treatment cycle, it was decided to make this path also correct.
• The task “Transmission, spread, epidemiology” had the instruction, “Can you get infected by COVID-19 through the air?”. “Virus Survival, Spread, Mutation” was designated as the correct path. The class “Avoiding Infection” was selected 27% of the time in round one and 33% of the time in round two. It was decided that it was logical to also make it a correct path.
• The task “Virus survival / viability / persistence on surfaces, in air” had the instruction, “How long can COVID-19 last on cardboard?”. “Virus Survival, Spread, Mutation” was designated as the correct path. (In round one it was “Symptoms, Diagnosis, Spread”.) The class “Avoiding Infection” was selected 41% of the time in round one and 22% of the time in round two. It was decided that it was logical to also make it a correct path.

When we implemented these changes the success rate moved up to 80%, our target. We also got results from a Top Tasks COVID-19 survey carried out in Canada with almost 7,000 respondents. We had a 70% overlap with the top 20 tasks, which was very positive. However, the overwhelming top task in Canada was “Financial support”, which was not a top task at all in the WHO environment. Looking at other data from countries and wanting to create a universal classification for COVID-19, we decided to add Financial Support to the top-level classification.

Here is the final classification for COVID-19:
At Risk, Vulnerable
Avoiding Infection
End Date, New Outbreaks
Financial Support
Mental, Physical Wellbeing
News
Research, Statistics
Symptoms, Diagnosis
Vaccine, Immunity, Treatment
Virus Survival, Spread, Mutation
WHO / Government Guidance, Education, Training

Over 800 healthcare providers, academics, and members of the public sorted COVID-19 top tasks into groups. We analyzed the groups and came up with the following hypothetical classification:

Symptoms, Diagnosis, Spread
Mental & Physical Wellbeing
WHO, Government Guidance, Education, Training
Research, Statistics
Vaccine, Immunity, Treatment
Avoiding Infection
News
End Date, New Outbreaks

What is important to understand here is that this is a hypothesis. The results from a sort rarely give definitive data. Lots of interpretation is required. Through experience we have found that we need to test over three rounds in order to design a robust classification.

How do we measure success? By giving people instructions to see how they would use the classification to solve top tasks such as:
• When is a vaccine likely to be available?
• Find the latest updates for COVID-19.
• Can you get infected by COVID-19 through the air?
• If someone has had COVID-19 are they safe from getting it again?
• Find what the WHO recommends in relation to testing.

We recommend having a minimum of 20 instructions and not more than 35. We need at least 20 instructions because otherwise the classification will not get a robust testing. It’s easy to get high success rates if we only test a few tasks. Using lots of instructions allows the classification to be tested from multiple angles.

Over 2,000 people completed the first round. (Normally, we need about 50 for reliable results.) We had an overall success rate of 60%. In other words, the classes we expected to be selected for the instructions were selected 60% of the time. Typically, we find success rates between 40% and 60% for round one, so our hypothesis was working well.

Our target is a minimum of 80% and ideally 90%. It is impossible to achieve a 100% success rate for a complex classification. There will always be around 10% of people or tasks that behave in unusual and unpredictable ways.

To get it over 80% we need to make some adjustments. The classification causing most issues was “Symptoms, Diagnosis, Spread.” This was somewhat expected. The sorting data showed strong connections between symptoms and diagnosis-type tasks. There were some—though weaker—connections between tasks connected with transmission and spread, and symptoms and diagnosis.

There were three tasks in the Transmission cluster:
• Transmission, spread, epidemiology: 62% success
• Virus survival / viability / persistence on surfaces, in air: 30% success
• Virus mutation, new strains: 19% success

It was decided that for round two we would break this class into two:
• Symptoms, Diagnosis
• Spread, Mutation, Survival

Testing-related tasks were strongly connected to the “Symptoms, Diagnosis, Spread” class and the “Vaccine, Immunity, Treatment” class. It was decided that there should be links to testing from both these classes.

The task “At risk, vulnerable” was performing poorly. This, again, was expected. It was the most orphaned task in the sort, meaning that it was the least connected with any other tasks. The reason it was not placed at the top level as its own class was because it was a tiny task, coming 29th. However, data we received from a COVID-19 top tasks survey in Norway indicates it is a top task there. On the national Irish health COVID-19 website and on the UK NHS website, it is at the top level of the classification. It was decided to make “At Risk, Vulnerable” a top-level classification.

Here is the classification that will go into round two and will be tested using the exact same list of task instructions:
WHO, Government Guidance, Education, Training
Mental, Physical Wellbeing
Vaccine, Immunity, Treatment
Research, Statistics
Virus Survival, Spread, Mutation
Avoiding Infection
Symptoms, Diagnosis
News
End Date, New Outbreaks
At Risk, Vulnerable

Design with people. Not for people. Before we are German, Irish or Canadian, we are human. And humans think the same way. Dream the same way. Organize the same way. There are mental maps out there in humanity. We just need to discover them. With the Web, we have the platform and the tools to understand these mental maps.

Here’s the initial hypothesis on how humans think COVID-19 should be organized into classes:
• Symptoms, Diagnosis, Spread
• Mental & Physical Wellbeing
• WHO, Government Guidance, Education, Training
• Research, Statistics
• Vaccine, Immunity, Treatment
• Avoiding Infection
• News
• End Date, New Outbreaks

This came about as a result of over 800 people sorting the top tasks that had emerged from a WHO survey of almost 3,000 individuals, families, academics, students, healthcare providers. We discovered what mattered most to people and then we asked them to sort and organize these things. The more people sorted, the more consistent the classes became. We found tremendous consistency between the mental models of healthcare providers, academics and the general public. They organized things in the same way.

Professionals and the public consistently grouped symptoms with diagnosis. Tasks such as likely course of the illness, incubation period and infectiousness were tightly bound in this group.

Transmission-type tasks like virus survival and mutation were less tightly bound but there was enough evidence of grouping for us to create this class: “Symptoms, Diagnosis, Spread.” Maybe Transmission should be a separate class. We need to test.

We also found that while “Myths, Fake News” was grouped with “News”, it was not strong. There were issues with “Infection hotpots” and “At risk vulnerable”; they didn’t clearly fit anywhere. These are what we call “orphan” tasks. There will always be orphan tasks and there will never be a perfect classification. How you deal with exceptions, orphans and tiny tasks is really important. In too many classifications, the tiny task exceptions have far too much influence on the classification design because tiny tasks are often pet projects of senior managers.

Links and classifications are the absolute foundations of the Web. Too often they are designed in a rapid, ad hoc manner. If there’s one thing you can’t design well and quickly it’s a classification. Unfortunately, too often they are designed by ‘five smart people in a room drinking lattes’ over a couple of workshops with lots of Post-its, with the occasional interjection from a hippo or a seagull that flies in, poops an idea and flies off again.

Good classification design comes from slow cooking. It is evidence-based and rigorously tested. It takes time to do well.

From the sorting of tasks we get a hypothesis that must be tested. There are a couple of reasons. Firstly, you need to test how you have named the classes. Over years of doing this we have found that while people are genius at grouping things, they are often idiot at naming the groups. We got suggested class name like: “Other, A, B, C, D”. We need to use judgement to come up with the names and then test.

There are grey lines between where one group ends and where another begins, whether in fact we have one group or should have two. We need to test, test, test. The hypothetical classification above will go through at least three rounds of testing.

We will do this by creating task instructions such as:
• Can you get infected by COVID-19 through the air?
• If someone has had COVID-19 are they safe from getting it again?

We will have a hypothesis about where we expect people to go and then we will ask them to select which class they would click on to find the answer.

Join Gerry McGovern, WHO, and a worldwide team in discussing the results from Round 1 testing of the WHO COVID-19 top level classification. We will then prepare for the Round 2 test.

A link is a promise. A menu is a selection of promises. Without the link there is no Web. Links make the Web. From links we build the Web. Links. So often forgotten in the design process. So often neglected.

Why? Because the rewards always go to the “creatives”. Those who create things. To innovate has come to mean creating things with the latest technology. Right now, you’re quite simply not creative if you’re not using some sort of AI or machine learning. Funny, I think, as I watch disastrous after truly disastrous chat bot implementation, what sort of management does this organization have? Is the board room a bunch of shiny boy toys? When you open the door are the only words you hear “gee whiz”, “wow”, “cool”, “we need an app”?

The vast majority of websites and apps do not need AI to help people find things. They instead need to create a classification and navigation that have been carefully thought about and designed. Something that wasn’t put together by five smart people in a room drinking lattes in an afternoon using lots of Post-its.

Words. Digital is still the design of words. Words. Should we use “infection hotspots”, “clusters”, or “exposures”? Or should we use all of those words in a link? Would it be important to add “near me”? Trivial? Some people think these are trivial, inconsequential questions. They’re not. They’re at the absolute core of designing a great digital experience.

I’ve been doing this digital work for more than 25 years. I have watched thousands of people try to use websites. Year in, year out, the number one reason for failure is confusing menus and links. 99 out of 100 organizations do not want to hear this. 99 out of 100 organizations will never make a serious attempt to design truly clear menus and links.

Because that requires a lot of intense effort over a prolonged period. It requires a deep and intense involvement in the design process by the people who are supposed to use these menus and links. It requires judging success based on whether people are successful or not in using the links to help them find what they are looking for.

“Improve your menus and links and you will get a 10 times greater return than implementing an AI system.”

“We’re going with the AI system.”

“Why?”

“Because it’s more important to be seen to be doing something innovative than to actually do something useful.”

Right now, we’re in the process of supporting WHO in creating an information architecture for COVID-19. We’re working with words. We’re working intensely with the people who will use the system. We’re building the evidence of what the top tasks are so that we can design these tasks to be easiest to find and complete. We’re testing, testing, testing. It’s a collaborative, multidisciplinary approach, with input from health experts from many countries, from individuals, families, from young and old.

Right now, we’re in the process of getting people to sort the tasks into groups that will inform the design of the classification system.

It’s never been more important for people to have speedy access to the right information. Until we have a vaccine, information is our vaccine. Until we have a vaccine, testing is our vaccine. Even when we have a vaccine, we will still need to provide lots of quality information. We will always have to address fake news, antivaxxers, and those dark state actors waging misinformation wars.

The Web is a powerful way to quickly deliver information to a large audience. Yet it is the Web’s strengths that are also its weaknesses. The Web makes it easy and fast to publish, but that doesn’t mean that it’s easy and fast to find and understand. The Web has created a culture of speed publishing, where the imperative is to get as much as possible published as quickly as possible.

Organization, structure, editorial decision making, often basic editing are neglected. The format, the tool, the latest gizmo dominates thinking and decision making. In much web management it is more important to launch an app or dashboard, website, video or podcast, than to ask why, what and how. Why do we need this? What is it going to do? How is it going to be organized in a way that is usable? Basic questions. Rarely asked.

In 25 years working on websites, one problem dominates year in, year out. A problem nearly nobody wants to address, except in the most trivial of ways. Why? Because it’s not seen as cool, as innovative. Because there’s no bonuses for doing it well, no career progression because of it. It’s a thankless, really hard job. It’s a vital job.

Confusing menus and links cause untold problems to people trying to use websites. Yet, in 9 out of 10 web projects I work on, the menus and links are thrown together in a haphazard and wholly unprofessional manner. It’s sad how bad we are at organizing content. It’s sad how little management cares about information structure, about classification, about metadata. The Web suffers—we all suffer—because of it.

WHO have decided to do a deep analysis of what sort of information truly matters to the public and professionals when it comes to COVID-19. A multidisciplinary, cross-national effort was set in train involving collaboration from health agencies and experts in Ireland, Norway, Canada, UK, Belgium and New Zealand. We gathered data on searches, supports calls, requests, feedback. With representatives from these agencies and individual experts from other countries, we sifted through this research using the Top Tasks method.

Hundreds of people were involved. It was a continuous improvement, rapid, iterative refinement effort. We never lost sight of the people who need this information and the language that they use.

Below you will find our coronavirus tasklist / checklist, our attempt at mapping the information genome for COVID-19. We will now go out to the public and professionals and ask them to help prioritize this list. We will then work with them to co-design a structure, an information architecture (IA) for COVID-19. We will test, test, test our way to a great IA. The plan is to create an IA pandemic template that will work for COVID-19 and future pandemics.

Everything will be made freely available. Every step in the process will be transparent and open. The public and professionals will be core participants in the design process. We will define “easy” based on evidence of ease-of-use, not on someone’s opinion.

Feel free to use what we have done so far. And if you’d like to be part of the process, get in touch.

About WHO (mission, members, funding, donors)

Animals and virus (get it from, give it to, walking)

At-risk, vulnerable (age, pre-existing conditions, disabilities, ethnic minorities)

Avoiding physical contact (social / physical distancing, self-isolation)

Business participation, new products, ideas

Caring for a vulnerable, at risk person

Caring for someone with virus at home, yourself with virus

Cleaning, disinfecting, waste disposal (hands, deliveries, home, workplace)

Community-based support groups, local networks

Compare statistics (country, local, tests, cases, recoveries, deaths, demographics)

Compare symptoms with cold, flu, allergies

Confined living, dealing with being inside (activities, entertainment)

Confirmed cases, deaths, recoveries (daily, total)

Contact WHO (media, experts)

Deliveries, online shopping, post

Diagnosis

Diet, food, nutrition, supplements

Digital democracy (participation, feedback, policy development, reform)

Domestic, sexual abuse, violence

Drugs (preventative, treatment, development, approved)

Dying alone, funeral rites, mourning, grief

Emergency contacts (ambulance, medical)

End date, new normal, safe again

Essential services, key / critical workers

Explaining pandemic to children (guides, resources, advice)

Explaining pandemic to those with learning difficulties (guides, resources, advice)

Financial support, assistance, benefits (eligibility, availability)

Food, medicines, essential products (stocks, hoarding, availability, disruptions)

Government guidance, regulations (national, local)

Government roles, responsibilities, who’s in charge of what?

Government strategy (long-term control, lockdown exit, transition, economy reboot)

Health services unrelated to pandemic (appointments, prescriptions, treatments)

High risk transmission environments, (care homes, restaurants, supermarkets)

Home schooling, remote teaching, learning (tips, how-to, advice)

Immunity, antibody testing (criteria, availability, accuracy)

Incubation period, time from infection to symptoms

Industry / sector specific advice (airlines, funeral homes, supermarkets)

Infection hotspots, clusters, exposures (near me, identifying, tracking)

Infectiousness (when most infectious, super spreader, symptom-free but infectious)

Latest news, latest research (alerts, directives, updates)

Likely course of illness, outcomes, prognosis

Mental health, wellbeing

Modelling, forecasting, trends (flattening curve, economic impact)

Money issues, personal finances, savings, pensions

Movements, interactions of infected people (tracking, contact tracing)

Myths, fake news, misinformation, out of date information

New outbreak, second wave (response, containment)

No longer infectious (criteria, time required in self-isolation)

Number of tests (tests performed, individuals tested)

Original outbreak source, patient zero (global, national)

Personal protective equipment (PPE: masks, shields, gowns)

Physical wellbeing, exercise, breathing exercises

Post recovery complications (neurological, cardiac, respiratory)

Pregnancy, birth, infants (precautions, advice, breast feeding)

Privacy rights, data protection, anonymity (apps, personal health data)

Professional medical training, courses

Public health campaign material, posters, communications, educational resources

Raw data, open data, datasets, metadata

Relationships (family, friends, colleagues)

Research ideas, submissions, funding, grants

Research papers, studies

Scams, cybersecurity threats

Sexual, reproductive health, rights

Symptoms, signs

Technology support for less experienced, vulnerable, reduced income

Testing for live / active virus infection (eligibility criteria, availability, accuracy)

Transmission, spread, epidemiology

Travel restrictions (quarantine, lockdown)

Treatment lessons learned, emerging best practice, failed treatments

Vaccine (development, availability, safety)

Ventilators (availability, approved, impact on recovery, decision to use)

Virus family, definition, names, acronyms

Virus mutation, new strains

Virus survival / viability / persistence on surfaces, in air

Volunteering opportunities

WHO guidelines, standards, decisions

WHO’s position, opinion, response to

Working from home (guidelines, tips, advice)

Workplaces (preventing spread, rights, reopening criteria, guidance)

“Democracy improves as more people participate,” Audrey Tang, the digital minister of Taiwan, wrote for The New York Times in 2019. “And digital technology remains one of the best ways to improve participation—as long as the focus is on finding common ground and creating consensus, not division.”

Back in 1994 when I first came across the Web I was struck by its tremendous democratic potential, of how it opened up society. Little did I realize that the Web would ultimately open up society to attack from malign hatemongers like Trump and Bolsonaro.

Little did I think that the “free” advertising-based model pursued by the likes of Facebook would be such a cesspit of waste and social poison. Little did I think that the Web would allow for the concentration of economic power in the hands of the Amazon and Google tech elite. And to crown it all, that this tech elite would relentlessly pursue tax evasion which would hollow out society, leaving little money for basic services, making things brittle and fragile.

The pandemic is good for the tech industry. They will be able to concentrate more power and wealth because of it, while avoiding even more taxes. While Bolsonaro devastates Brazil and the Amazon, Bezos can gleefully devastate small business, making societies serfs to the great lord, while paying his workers the absolute, absolute minimum. Tech and the return to slavery. That’s a story.

Our public spaces have been hollowed out by the elite. The Web and technology have been primary tools in this process. There is no sense of the fair society in the tech bro mindset, just a relentless pursuit of growth, profit and tax evasion.

Hate sells better than hope. Want is easier to advertise than need. To build a fair society is not to build one where the greedy tech elite accumulate vast wealth, but one where ordinary people can lead decent, honorable lives by getting paid decent wages and having decent healthcare. This is not an impossible dream. There is more than enough wealth and capacity to do this. We simply lack the will, the courage.

In Taiwan, we see a light of hope shining. They have used technology to help nurture consensus not division. The people genuinely participate in the policy space and they are listened to. Any Taiwanese citizen “can post a comment about the topic or policy being discussed,” Audrey Tang explains. “Crucially, other users cannot directly reply to these statements, which reduces the likelihood of trolling and abuse. Instead, they can click ‘agree,’ ‘disagree’ or ‘pass/unsure’ on each comment.”

The system then uses real-time machine learning to analyze all the votes and “produce an interactive map that groups like-minded participants together in relation to other, differently minded users,” Tang explains. “The map lays bare the gaps between various groups—as well as any areas of agreement. Ideally, this incentivizes people to post comments that attract more supporters, creating a path toward consensus.”

Coronavirus has shown us how fragile and interconnected our world is. Since 1970, there has been an explosion in wealth and technology, and an equally great explosion in inequality. Investment in the public space has been sucked dry by obscenely overpaid, tax-dodging vampires, leaving brittle shells that crack when the hard winds of a pandemic blow.

Before Bezos and Zuckerberg unleash their robot army, we should act. It’s not too late, though it’s getting there.

A Strong Democracy Is a Digital Democracy, Audrey Tang

Countries like South Korea, Taiwan, Vietnam, Germany have been successful at containing COVID-19 because they test relentlessly, get results back quickly, and use the data from the testing to trace and isolate.

Until we have a vaccine, data is our vaccine. We need the right data about who has it, who they were in touch with. Right now, data is medicine. The right data will help save lives, and will get the economy back from the brink.

The “testing, testing, testing” mantra should also be the mantra of Web management. Unfortunately, it rarely is. Instead, in Web management, we so often use the wrong data, vanity data, Cult of Volume data, data focused on stuff being done rather than the right stuff being done.

In Web management, it’s much more prized to do the wrong thing quickly than to do testing and research and do the right thing a little more slowly. Speed is everything. You need to be sprinting, even if you’re sprinting in the wrong direction. You need to reach those artificial, made-up deadlines to show that you are a deadline maker.

When are we going to mature? We’ve become addicted to Cult of Volume metrics, to the Cult of Busyness. How are we going to wean ourselves off our obsession with quantity, volume and fake deadlines?

Content professionals are still primarily judged on the content they produce rather than the knowledge they communicate. We choose the metrics of volume and production because these are easier to collect and easier to communicate to senior management.

Developers and designers are judged on the code and designs they produce, not on whether they helped people figure out whether they had symptoms of COVID-19 or not. To test whether your Symptoms Checker actually works or not is crucial.

In Canada, they’re doing it differently. Practically every day they’re running tests on the COVID-19 content, Lisa Fast, optimization lead at Canada’s digital transformation office told me. They’re running these tests on mobile because at least 70% of the access to the content is from smartphones. They’re consistently asking citizens to attempt such tasks as:
“You’ve been asked to self-isolate. Find specific advice about what you should do if you live in a house with other people.”

It’s not enough to produce content or to launch an app. You must measure whether what you’ve done is working and the best way to do that is to measure if it’s working for the intended audience. If someone needs to self-isolate can they:

1. Find the right information.
2. Understand and follow properly.

Every day they’re testing their Web content in Canada. They’re learning what is working and what isn’t. They’re making changes based on what they’ve learned and testing again to see if they made the right changes. If they didn’t, then they’ll make more changes and then test again in order to keep learning.

We don’t have time to do it right. We just have time to do it wrong. The Web teams that don’t regularly test are like the countries that don’t test enough for COVID-19. They are running blind. It’s time for Web management to mature, to move away from the primitive Cult of Volume metrics, and to embrace metrics based on outcomes, on task completions and time on task.

In digital, I’m forever copying and pasting, and saving as. In digital, it’s so easy to create copies. Sometimes, when I’m writing and I’m not happy with a sentence, I’ll delete the whole sentence and start again, even though it might have been better to work on the original sentence. It just seems more convenient to select and delete or to put my finger down on the Back button.

I know I’m not alone. I remember years ago talking to some people in the Microsoft Excel team and they telling me about how they tested hiding the big Copy and Paste buttons behind a dropdown because they thought that everyone would by now know where to go. Wow! Did people in the test get frustrated. They wanted that big button, and to this day you still see that big Copy and Paste buttons take pride of place in the top left of Microsoft Word and Excel.

I’m afraid to cut and paste. Just this morning I needed to move a file. I copied instead of cutting. “What if something goes wrong,” my mind said. “You need to be able to get back to the original.” What if something doesn’t go wrong? What if everything works out fine and I get done exactly what I need to do? Will I go back and delete one of the redundant files? Probably not.

Digital makes us copiers. Digital makes us duplicators. We copy because we can. We copy because there is no obvious cost and we are risk averse. We don’t want to lose something. We know that digital is inherently unstable and transient, that in the blink of an eye, months of work can disappear. So, we take out insurance by making copies.

What’s the cost of copies? Very little it seems. Except that we created more data in the last two years than in all of previous history. That we are now creating zettabytes of data every year and storing much of it in the Cloud, and cloud storage is so much more polluting than storing locally. Storage is like global warming. In our everyday lives, the growth of storage is imperceptible. It’s like the rising sea levels. Its impact and consequences will be felt in future generations. Digital storage is exploding and it will do tremendous damage to our planet if we don’t radically change our behaviors and stop saving and copying everything.

What happens to the copies when we change the original? Will we go back and update the older copies with the new version? What happens to the copies when we decide to delete the original? Will we go back and delete the copies? What happens when someone takes a copy and makes a small change?

Copies create simplicities for the present and complexities for the future. Digital makes things easy for the now and stores up problems for the future. We have become copyists. Every copy we create has a weight. It consumes energy and creates pollution. What we need more than ever today is a philosophy of not copying or not duplicating, of using what we have. If we do copy we must remember to delete, and we must become just as good a pruner as producer. Otherwise, we’re just contributing to the enormous ocean of both digital and physical waste that humans have been mass-producing these last fifty years.

The coronavirus is indicative of a sick Earth, a stressed and stretched Nature. In our pockets, in our hands, beside our ears, lie devices that contain the stories of how and why the Earth is so sick, of how we have in the last forty years, partaken of a mad and frenzied party of over-consumption, resource depletion and crap production.

Coronavirus is not Armageddon. We will recover from this one. Armageddon is in our hands. We plan for Armageddon every day with our wanton waste lifestyles, with our voracious appetites for the trivial and the transient. We have become so bored. We demand distractions, non-stop entertainment, we snack endlessly on junk food and fake news with gadgets we can’t wait to throw away.

We are not simply living beyond our own means, we are living beyond the Earth’s means. We are living beyond its capacities. And when I say ‘we’, I do not mean poor people in poor countries with large families. Their pollution footprint is quite small. The prime wreckers on this Earth live in North America and Europe. We are the uber-wasters and destroyers.

A typical smartphone will contain up to 60 materials and elements, including tin, iron, plastic, lithium, silicon, copper, nickel, alumina, silica, potassium, graphite, manganese, aluminum, tantalum, gold, silver, lead, magnesium, bromine. Producing these materials results in lots of solid and liquid waste. This waste builds up onsite in enormous dumps, sometimes several square kilometers in area. Often, these materials are mined in countries that have poor or nonexistent safety standards.

16 out of the 17 rare earth materials can be found in a typical smartphone. These materials are by definition rare. To get them often requires going to places humans have rarely gone before.

“We’ve penetrated deeper into ecozones we’ve not occupied before,” Dennis Carroll, an expert in global pandemics states. “In Africa, we see a lot of incursion driven by oil or mineral extraction in areas that typically had few human populations. The problem is not only moving workers and establishing camps in these domains, but building roads that allow for even more movement of populations. Roads also allow for the movement of wildlife animals, which may be part of a food trade, to make their way into urban settlements. All these dramatic changes increase the potential spread of infection.”

Since the first smartphones were launched in 2007, some 10 billion have been manufactured. Less than 20% of these are recycled and when they are, the process is usually to dump them in poor countries where they will be smelted in open pits.

Smartphones can, of course, be truly useful. The WHO website went from 55% mobile visitors pre-coronavirus to 70% now. Yet, too much of the smartphone’s story is one of abuse of the Earth and its poorest people in the cause of willful overconsumption and planned obsolescence.

The Earth cannot cope with us Europeans and North Americans. Our appetites are far too voracious. We must slow down. We must stop consuming the Earth like it was a Big Mac or a Coca Cola. We must stop the waste.

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