Shutdown-Cozy, Hygienic-Possessive, Locally-Remote: 3 Coronavirus Megatrends

While we eventually are going to beat Sars-CoV-2, it is likely that many of the changes the pandemic has brought and will bring about may be more long-lived.

Most of these will be continuations  – or completions – of pre-existing trends: the virus and the response to it merely enhance developments that have been brewing beneath the surface for some time. And while some effects will be direct and rational, others happen due to not-always-so-rational shifts in our cultural values. Think of how even terrible advertising manages to shape ideas by means of repeating the same message over and over again – and then consider how we are currently subjected to endlessly streamed corona-content.

The following is a summary of three such megatrends I see emerging in the context of the current crisis. These are observational, and I don’t intend to back the up with data for now.


Like Domestic-Cozy, but more conservative and with a dash of anxiety.

blumetee-1512934Shutdown-Cozy is the not-so-secret embracement of a simpler life at home. Free of FOMO and grindy commutes, quarantined millenials and Gen-Xers have begun to refine their sourdough and cooking techniques, and re-discovered the joys of physical books – and, the simple family life.

While the official line remains that we all ‘miss bars’, the immediate ‘but’ that follows is one about how ‘surprisingly’ pleasant life in quarantine can be (at least for knowledge workers and other non-essential, but well paid members of the economy).

This is an uncanny continuation of a aesthetical stance observed and described by Venkatesh Rao in 2019, which he labeled Domestic Cozy:

[Domestic Cozy] finds its best expression in privacy, among friends, rather than in public, among strangers. It prioritizes the needs of the actor rather than the expectations of the spectator. It seeks to predictably control a small, closed environment rather than gamble in a large, open one. It presents a WYSIWYG facade to those granted access rather than performing in a theater of optics.

Shutdown-Cozy narrows this even further. It results in a forced re-appraisal of our homes, our immediate surroundings and our domestic practices and values. Take a look at your desk. Maybe you ought to move it, or buy some flowers to place on top of it? Isn’t it nice to listen to vinyl records while playing with your kids, or kneading your sourdough? Do you have enough Vitamin D tablets in your drawer, and enough paracetamol just in case? Should you buy a gun? If there’s entrecote left at the market, maybe you could cook some steak for dinner after home-schooling your kids. Shutdown-cozy tickels out the Tradwife in each of us.

Of course, once the shutdowns are relaxed, bars will be packed again. Or will they? And if so, will they continue to be as packed as they were before this all happened? Just like that?

Economically, Shutdown-Cozy is likely bad news for all ‘frivolous’ indoor urban activities – think restaurants (except the ones that manage to reinvent the restaurant), concerts, bars and movie theatres. On the other hand, there is a bullish long-term case to be made for anything that improves our domestic surroundings and psyche: furniture, streaming, homecooking, delivery, taking long walks outdoors and teleyoga.


Sharing – isn’t caring anymore

Screenshot 2020-04-29 at 21.11.02
Faux German in Tokyo

AirBnB was about to be the biggest IPO of 2020. Today, the thought of flying to another country and staying in a stranger’s house seems flat-out bizarre.

Of course, once the shutdown ends, borders re-open and airlines have been bailed out people will continue to fly around the world and stay in each other’s houses just as much as they used to. Or will they not? How about using someone else’s car? Or a bike used by hundreds of different people every day?

Hygienic-Possessive prefers clean to dirty (neurotically so), and mine (personal ownership) to ours (sharing partnerships). Not everyone will feel this way, but I’d wager that many more people will be like this than before the crisis. 

It’s thus short on everything related to the sharing economy: AirBnB, Uber, WeWork are prime examples of products that incompatible with the hygienic-possessive stance.

The bullish case is with car makers (traditional and new: cars are in this context also extensions of our domestic environment), insurance (of all kind) and cosmetics that look like medical products.


If remote work works, why would anyone go back to forcing people into an overpriced and smelly office? The answer is of course to not underestimate managerial distrust and the desire to control, which for traditional organizations is difficult to achieve outside of the panoptical context of an office. office-space-coffee1

That said, a secular remote work trend has been around and building for years, and many have rightfully noted that the Coronavirus crisis is its perfect accelerator.

And while some majority will eventually go back to work in their offices, quite a few will continue to work remotely, and many more will at least “wfh” for one or two days a week. Then, one day, one of the best, unfireable employees demands to be wfh full time because they decided that Shutdown-Cozy was going to be cozier in a nice’n’affordable house in the countryside…

Long term, this seems to favor rural over urban living: most of the advantages of urban live are now ‘risky’ to the Hygienic mindset, and assuming you can work from anywhere and don’t have to live near an office, and restaurants and bars aren’t what they used to be, and you’ve learned to make your own sourdough…etc. To live in a house, very big house in the country suddenly seems like a much better idea than a year ago, or not?

hall-1509273How about vacations? Flight shame was real before the Coronavirus crisis, but it didn’t move the needle in terms of actual bookings. Coronavirus broke the needle and threw it out of the window, grounding over 99% of all air traffic.

I believe that due to the combination of climate and corona, exotic vacations will seem like a somewhat problematic idea to many for a long time, and we will see a trend towards local recreational activities, a parallel development to Shutdown-Cozy. 

So an interesting result may be that you work remotely, while vacationing locally.

Feedback loops

Trends rarely happen in isolation, but are intertwined with each other. I’ve mapped out a few interactions between these 3 below.

Screenshot 2020-04-29 at 22.11.28

If you can think of a great label for the “?”, please do get in touch via Twitter!

Trouble in the workplace: Intuitive Machines vs Rational Humans?

Human knowledge workers have been compelled to be increasingly rational, data-driven and transparent about their decision-making. How does the emergence of intuitive and intransparent AI colleagues fit into this?

Masagia Universalis, Athanasius Kircher (1650)

New team members may occasionally cause new conflicts, but especially so when they’re from another species and treated differently to the rest.

Consider the case of machine learning based software systems that are being deployed to help knowledge workers make better decisions. It doesn’t really matter whether we call this “AI” or not, or whether we believe in the possibility of “General AI”.

As a baseline understanding, let’s assume that McKinsey is right in predicting that “30 percent of the activities in 60 percent of all occupations could be automated“, which would mean that “most workers—from welders to mortgage brokers to CEOs—will work alongside rapidly evolving machines.”

Now, for a knowledge-working hu-man, there are by and large two ways to make a decision:

  1. one is slow, clean, step-by-step, deliberate, data-driven and ultimately explainable. In its ideal form, the very way in which the decision has been formed is, by virtue of its logical and empirical foundation, actually identical to its explanation.
  2. The other is fast, messy, intuition based, experience driven and often not easy (or even impossible) to explain, at least right away – i.e. the decision-maker isn’t in a position to immediately understand, explain or justify how and why their decision is indeed right and rational.

In the history of “making corporate workers successful” ideas, Malcolm Gladwell’s 2005 hit book “Blink” was probably the last defense of any merits of the latter, intuition-based approach.

Today, the ideal of corporate and managerial decision making is anything but ‘blink’-based (at least outside of the C-level, where exceptions apply  – it is generally more possible to operate on intuition-based decision-making in the upper echolons of management). That said, the vast majority of knowledge workers have to base their decisions strictly on a transparent compound of data and logic (often with an unfortunate emphasis on the former alone), and since about a decade, entire organisations devote themselves to “become more data-driven“.

In practice this means that a human decision-maker, say Sally from Marketing, will not only be required to base her decision on data, but she also must be able to demonstrate and explain how exactly her decision was made and what data she used in support of her conclusion. “Trust my training and experience, this just feels right” isn’t what Sally’s bosses or their board want to hear, even if they may occassionally operate on hunch alone.

Interestingly, the opposite is also true for Sally’s new “AI” colleague, which for now may provide business recommendations without the burden of having to explain how it came to its conclusions.

This isn’t because it wouldn’t be useful to have AI systems explain their output (see the note on “Explainable AI” below), but rather because they currently simply can’t: the best performing breed of machine learning systems is incapable of providing proper insight into how exactly a specific conclusion came about. This is especially true for systems based on convolutional neural networks (“Deep Learning”), which aren’t designed (and possibly undesignable) to provide discrete specifics into how exactly their decision-making-output has been computed.

Instead, they are purely judged on past statistical performance, as in: we have extensively evaluated the system’s output against empirical data and found its performance to be good enough (aka: better or as good as Sally) to be deployed in producing predictions on yet unseen outcomes.

To be clear, there are laudable efforts to look into “Explainable AI“, which aims to investigate methods to have machine learning based systems explain or justify their outputs in more detail. However, it’s far from clear whether these efforts will be met with success, all the while the utilization of the affected machine learning methods across industry and government is in full force.

Assuming that we’ll see more and more of these opaque, yet performant machine learning systems deployed alongside human workers, we should perhaps be prepared for a new type of workplace conflict to arise out of this “discriminatory” practice – especially if the collaborative human-machine frontier will turn out to be as crucial as predicted (see again the above linked report by the World Economic Forum).

Given that many knowledge workers know this type of decision-making discrepancy from their superiors, the emergence of similarly exempted AI colleagues may well be experienced as an unfortunate power grab, acting to the detriment of widespread and successful AI adoption.