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Denialism is not skepticism

Resolutely refusing to accept a conventional understanding is a statement of certainty.

That’s different from honest skepticism. The skeptic offers an open mind and is clear about what would be necessary to earn enthusiastic support.

The denialist, on the other hand, is sure. Now and forever. This certainty probably doesn’t come from the matter being discussed. Instead, it’s based on external factors, a story, a cultural connection, something that is fueled by the feeling that comes from refusing to examine the issue, not by honest inquiry.

Skepticism is gutsy, denialism is based on fear.

Magic, persistence, imagination and more

Magic first: Acar and the folks at Penguin are offering a limited-edition deck of special cards to go with The Practice. It launched today.

Persistence: Today is the 200th episode of my podcast Akimbo. I don’t blog about it here often, but wanted to thank my producer Alex DiPalma and thank you for listening as well. It’s a labor of love, and it’s also among the top 1% of all podcasts. You can check out episodes here and transcripts here and subscribe here. That’s years and years of weekly audio, via the magic of podcasting.

Imagination: Jacqueline Novogratz and Tim Ferriss talk about her new book on Tim’s podcast this week. Hearing two of my friends so thoroughly talk about work that truly matters is a wonder, and I encourage you to check it out.

And more: Erica Dhawan’s book on digital body language just arrived, and it’s a salve for exhausted Zoom users (all of us). Steve Wexler’s new book on data visualizations, charts and graphs is worth checking out when it ships next week. And the blog and book and podcast that will change your life the most is the one you create.

Go make something.

Selling hours

This might be the workplace question of the decade.

Does the boss buy your time or your productivity?

In the pre-industrial age, when we worked from home (“cottage industries”) workers got paid by the piece.

As we moved to factories, it shifted. Many workers preferred a reliable regular paycheck, and owners decided to profit by investing in productivity and keeping the upside. When new machines show up, the workers don’t get paid more, but the boss makes more.

Now, as work-from-home promises/threatens to become a norm for many knowledge workers, the question is back.

Some bosses are demanding workers return to the office, and some managers have spent the last year forcing people to endure endless zoom meetings. The mindset seems to be that if your time is what got purchased, the boss wants to be sure you’re spending all of that time at work on work, not, who knows, tending for an ill family member or something.

But as it gets easier to measure productivity and contribution, and as it gets easier to outsource any task that can be described clearly, there’s a fork in the road:

If we’re not buying or selling hours, what, exactly do we measure and how are we compensated for it? Are workers ready or open to getting a commission, a profit-share or a per-piece price? And if we’re not selling our time but our contribution, does that further self-center the culture?

And if we are buying and selling hours, how does that work when surveillance capitalism bumps into workers needing flexible schedules and the trust that it takes to develop leadership and creative contribution?

Is it okay with you, the boss, if one of your workers dramatically increases productivity through some outsourcing or tech shortcuts on their own nickel and then goes home at 2 pm every day?

Is it okay if you have another worker who works until midnight every night but doesn’t get nearly as much done?

What about a team of five deciding to skip most of their meetings, coordinate through a shared doc and put the time they save into going for a walk or thinking about the next breakthrough?

If it’s truly about what we produce, how many people on the team are aware of how much they produce? What would happen if they were?

The theory of the firm was based on two key assumptions: That workers needed to be in physical proximity to each other, and that communicating with and measuring outsiders was simply too expensive to scale. For a lot of knowledge work, neither is completely true any more, and so we have to reckon with what the right size of a ‘firm’ even is.

The very nature of the factory and employment is completely up in the air. Instead of bragging about how many employees a company has, how big the office is, how many folks are in any given meeting… some leaders may start optimizing for how few they need to get the work done.

Faster! Faster?

This simple free tool lets you speed up just about any video you watch in Chrome.

And it’s not difficult at all to speed up audiobooks or podcasts, just look for the button in your favorite player.

If the topic lends itself to you absorbing the information faster than the person is presenting it, this simple hack increases the amount you can learn by 30%, which is huge.

On the other hand, if you’re simply speeding things up because you are in a hurry to get through it, it might be better to not do it at all.

Why the blockchain matters

But first, let’s understand some words…

Bitcoin is not the blockchain. If the blockchain is a printing press, Bitcoin is a kind of paper money. There are countless things that one can do with a printing press, in fact, it changed the world, but the invention of paper money isn’t even one of the top 100 most important outputs the printed press created.

Cryptocurrency has a terrible name. Most people associate “crypto” with spies and secrets. And a currency is generally backed by a nation, with a treasury, an exchequer and banks.

It’s more accurately thought of as a token.

If you went to an amusement park, you might buy a bunch of tokens or tickets to go on the rides. And if you run one of the rides, you collect the tokens, which at some point, you can trade in for a different sort of value, probably currency.

If people need tokens and they’re scarce, they go up in value. If people think that tokens are going to go up in value, they might buy them in anticipation of that. And the things that people do to get tokens can range from simply buying them with paper money (!) to performing various tasks (like the ride operators in the example above).

And, if a lot of people own tokens, they’re likely to do things that make tokens go up in value. Thus, an ecosystem is born.

Okay, so what’s the blockchain?

It’s a database.

Unlike most databases, it’s not controlled by one entity and it’s not easily rewritten. Instead, it’s a ledger, a permanent, examinable, public database. One can use it to record transactions of various sorts.

It would be a really good way to keep track of property records, for example. Instead, we have title insurance, unsearchable folders of deeds in City Hall and often dusty tax records.

There are databases everywhere around us (Facebook, for example, is mostly a database–who are the users, who do they know, what do they do?). Because the internet rewards people who own networks so handsomely, these organizations continue to gain in power. Google began by building a database on top of the open internet, and they’ve spent the last twenty years relentlessly making the internet less open so they can fortify the power of their databases and the attention they influence or control.

And that’s the first reason that the blockchain matters—because there’s a chance that it might lead to more open, resilient, market-focused networks and databases. It’s only a chance, though, because all the hype around the tokens sometimes makes it seem more likely that financial operators will simply seek to manipulate unregulated markets for their own benefit.

The second reason might support positive change. The existence of tokens and decentralization means that it’s possible to build resilient open source communities where early contributors and supporters benefit handsomely over time. No one owns these communities, and we can hope that these communities will work hard to serve themselves and their users, not the capital markets or other short-term players.

Consider a project like Wikipedia. Tens of thousands of people have devoted millions of hours to working to build it. 5,000 active editors are responsible for most of the work that we benefit from every day. This is unpaid work, done for the community and for the satisfaction and status that comes with it.

But of the top 100 websites, there are very few that are built on this model.

Now imagine a blockchain/token project in which contributors earned tokens as they built it and supported it.

Over time, the decentralized project would go up in value. As the ecosystem and the market delivered more and more utility to more and more people, the users would need to buy tokens to use it. And the holders of tokens would receive either a dividend or have the ability to sell their tokens if they chose.

Early speculators would attract more attention, and people with more skill than capital could invest by contributing early and often.

As the project reached a steady state, the stakeholders would shift, from innovators and speculators to people who treat their daily contributions as a job without a boss. Innovators could build on top of this network without permission, creating more and more variations and choice using the same underlying database.

One way to consider this: The open web led to a huge leap in the number of useful databases that we all use (things like Zillow, Instagram and even Tinder). They were fairly cheap to launch and run, and once the network effect kicked in, the profits were significant. Investors were eager to fund the next one, because the odds of a big win dwarfed most of what they could choose from in traditional businesses.

But dominant players are now working to make the openness of the web (the thing that allowed them to grow in the first place) less open. Google and Facebook and others push to make their stock price go up, not to serve users and others who now understand they have little choice in the matter.

The distributed nature of the blockchain, combined with this novel way of funding early contributions means that the network effect may very well bring powerful new databases to the fore, creating new ways for us to interact.

It’s hardly going to be perfect. There’s the issue of how the blockchain itself is run. If it’s run on the original method—proof of work—it’s likely to be a carbon disaster, getting worse as it succeeds. Fortunately, there are new approaches on the horizon (with great names like ‘proof of stake’ and ‘sharding’) that might address these problems.

For the typical user, the existence of the blockchain itself won’t matter, just as you don’t need to know how many volunteer editors Wikipedia has to benefit from using it.

The reason the blockchain matters is that it is an agent of change. Just like the transistor and yes, the printing press, when an agent of change shows up, it often leads to shifts that we probably didn’t expect.

Understanding it now is more productive than simply being forced to deal with it later.

Jargon vs. lingo

Jargon is intentionally offputting, and lingo reminds us how connected we are.

They might look similar, but the intent is what matters. Jargon is a place to hide, a chance to show off, a way to disconnect. Lingo, on the other hand, allows us to feel included.

Mouth to mouth resuscitation

It might be the best way to save someone in distress.

But it doesn’t scale.

You can only offer this sort of lifesaving intervention to one person at a time.

Often, we get stuck because we try to take our useful local magic and somehow make it for everyone. Perhaps we’ll need a different approach when it comes to serving more people.

Not because it doesn’t work. It does. Because it doesn’t work at scale.

Shortages, momentum and the search for meaning

A general malaise is not new. Sociologists have been writing about it since the Second World War. Today, of course, the malaise isn’t simply general, it’s also specific.

There’s too much pain and disconnection and uncertainty in the world. And yet, there are technological marvels, new opportunities and many people who have enough resources to meet their needs. For someone with enough, two things can get in the way of a life filled with meaning:

Affluence and stasis.

When we don’t have enough to eat, don’t have a roof over our heads, don’t have something that we need and can imagine getting, it’s not a general malaise, it’s a specific one. If you’re in this position, life is hard indeed.

On the other hand, spoiled kids are spoiled by parents who have already figured out how to cover their basic needs. When people stop focusing on making a contribution or wrestling with urgency, it’s easy for them to feel a sense of ennui.

And stasis is the feeling that nothing much is going to improve.

In wartime London, under attack eighty years ago, food was scarce and life was dangerous. But those that survived recall it as being a great moment (even if it was something that they’d very much like to avoid repeating).

Compare this to the widespread dissatisfaction described by people who grew up expecting things to get better (momentum) who are now coming to the conclusion that it might not happen.

“Compared to what,” is the question that gets asked at work and home every day, and if the ‘what’ is yesterday, it’s difficult to keep a positive promise forever. Day trading on better is a rough ride.

As we enter a post-industrial economy where good jobs are going to continue to get more scarce, creating a positive cultural dynamic-one in which the social contract can deliver meaning-is more urgent than ever.

The constant awareness that’s pumped in via the media rarely matches the experiences (positive or negative, exciting or not) that many people choose to experience every day. That mismatch often translates into unhappiness.

The benefit of the doubt

Rarely talked about, and the heart of marketing and more than that, of culture.

We can’t possibly know precisely what’s inside the book or the box or the bottle before we buy it for the first time. We take meds or go to the movies in anticipation of an outcome, and we give the producer the benefit of the doubt (or we don’t go, because the doubt is too much for us to handle.)

And we do the same thing with people. Who we hire, who we are afraid of, who we marry. We can’t know, not for sure, not until our experience with them is complete.

And we make all of these decisions without a conscious thought.

When we persistently and consistently do it incorrectly, we suffer. We create injustice, we miss out on opportunities, we fall prey to scams. The more we generalize our benefit of the doubt (and worse, the amplification of the doubt) the more damage we do.

The internet has overwhelmed us with data, and some of it (but not much) is actually turned into useful information. Some of that useful information is helping us see how long we’ve been mistaken about the benefit of the doubt in so many of the biases and actions we take (and don’t take).

Examining how we instinctually make these choices is a powerful first step in making better ones.

The weather problem

Meteorologists on TV spend most of their time talking about how the weather is right now, right outside. And progress for TV weather often looks like more accurate reporting of the current precipitation, temperature and windspeed, along with nicer graphics.

That’s not the same as actually predicting what the weather will be tomorrow. We can probably agree that more granularity in how the weather is right now isn’t particularly interesting.

It’s an easy trap to fall into, because spending time on what’s provably true is way less risky than deciding what’s important and using it to predict the future.

Our best work involves sorting the important from the rest, along with bringing a point of view and experience to complicated problems. Problems that are interesting because there isn’t a proven, correct answer.

The wind chill factor is best left to an automated device.

We don’t need a weatherman to know which way the wind blows, but figuring out how it’s going to blow tomorrow is a great skill.

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