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Grievance and possibility

We might be settling scores or we might be opening doors. It’s up to us.

Grievance and possibility have confusing roots.

Grievance isn’t about grieving. In fact, it’s the opposite. Grievance is the narrative of getting even.

Possibility doesn’t itemize everything that’s possible. Instead, it focuses on the side effects that come from acting as though things are possible.

Grievance looks back and possibility looks forward.

Organizations and relationships that are focused on grievance care a lot about their share. About the competition. About maintaining ‘enough’.

Organizations that are focused on possibility care a lot about how big the pie is. About innovation. And about what’s next.

You can build a relationship or a career on grievance or on possibility.

And you can run a justice/penal system that way as well.

Possibility begets more possibility. Opportunities multiply.

And, alas, grievance leads to more grievance. Because it’s the fuel that keeps the narrative going.

Organizations/partnerships/systems that are usefully focused on possibility don’t deny that there are reasons for grievance, that there have been actions and omissions that must be addressed. In fact, they adopt a posture of forward motion as the best way to address the problems that came before.

One challenge is embracing the effective and generative approach of possibility when we’re sure that we’re entitled to grievance.

Toward better.

Ranking the unrankable

Weight is a useful measure. 10 pounds is twice as much as 5 pounds.

Measuring things and then ranking them effectively enables us to make better choices and to scale up our operations.

Sometimes, though, in our rush to standardize and process a complicated world, we begin to measure things that can’t be easily measured, and then, since we’ve measured them, to aggressively rank them.

Smart isn’t easily measurable. Neither is beautiful, good or successful. And especially happy.

A high SAT score is a measure of whether or not you scored well on the SAT. That’s it. A bank balance is a measure of how much money you have in the bank. That’s all.

In the face of the difficulty the system has in measuring things that don’t measure, we create proxies. Things like popularity as a proxy for whether a work of human creativity has worth or not.

It’s a method built to process commodities instead of people, and it’s running amok.

A precision ranking is nothing but a number, an inaccurate and ultimately useless stand-in. These proxies are created and spread and relied upon by a system that craves certainty and order.

Realizing the fraud of the proxies might help us get back to what matters instead.

The reverse value/luxury curve

For most products and services, we rate them on a curve.

Of course the seat on the discount airline was cramped, but that’s okay because it was cheap.

Of course this Camry doesn’t look or ride like a Porsche, don’t be stupid…

But, the opposite is true in the high end. When luxury goods are compared to luxury goods, the narrative is, “this one must be better, in absolute and relative terms, precisely because it’s more expensive.”

And so hiring McKinsey costs 10x more than hiring a former McKinsey consultant. And so it’s worth more.

And so $150,000 elephant-sized stereo speakers (yes, they exist) are far better than $5,000 speakers (can’t you see?)

This goes beyond the standard understanding of a Veblen good. Because in addition to being more expensive, these super-luxury goods are less effective, harder to use and generally a pain in the neck. That’s part of their appeal.

(And yes, the same is true for corporate luxury goods, like software and IT consulting…)

Price accordingly. And listen to the reviews with a careful skepticism.

That might not be the right question

“Where do you get your ideas?”

The thing is, everyone has ideas. All the time, every day. Having ideas is part of the human condition.

The right questions might be:

Are you exposing yourself to new inputs and new situations, and challenging yourself to find more interesting ideas?

Are you pushing the ideas you have further, making them more complete, turning them from hunches to notions to ideas to theories?

Are you publishing your theories, sharing your reasoning and having your ideas collide with the real world in service of making things better?

Careful what you wish for

Because wishes don’t always come true, but wishing takes a lot of time and energy and focus.

What you wish for determines how you’re spending a juicy part of your day. If you wish for something you can’t control, that might fill you with frustration or distract you from wishing that could lead to productive work.

Better to wish for something where the wishing itself is a useful act, one that shifts your attitude and focus.

The end of dumb pipes

The phone company didn’t care what sort of conversation you were having. The call was the call. Same is true for cable–what you watched didn’t matter to them.

The reason retail banks are so frustrating to many customers is that because they began with a geographic focus, they’re dumb about who their customers are. They underserve or overserve in random ways. And in trying to serve everyone, they end up doing a lousy job of serving anyone.

But there’s no longer a reason for a provider to be dumb. They can optimize for you and your needs. They know what you’ve done and they should be able to guess what you might want next. Not to do this to you, but with you and for you.

“You can pick anyone and we’re anyone” is a lousy slogan.

How do you make your pipe smarter than that?

Algorithms give or they take

If there’s scarcity, we need to make choices.

Who gets hired, what website shows up at the top of the search results, who gets a loan.

And while we can make those choices on a case by case basis, at scale, we rely on algorithms instead. A series of coded steps, inferences and decision-making heuristics that ostensibly get better as they gather more data.

At this point, it’s clear that algorithms are remaking our culture. They drive how social media networks surface content, how search engines highlight websites, how AI makes decisions about who flies or doesn’t, who gets a loan or doesn’t, it’s everywhere, all the time.

And algorithms are not neutral. They can’t be. Every decision has consequences, and unlike the pythagorean theorem, there isn’t a right answer, simply a choice about now or later, all along a spectrum.

An algorithm takes when it finds a selfish or defective element of society and magnifies it for short-term profit. It finds habits or instincts that individuals might have and exploits them to do something that benefits the algorithm-maker without leaving the culture or the user better off in the long run.

And an algorithm gives when it amplifies the better angels of our nature, when it helps us do the things we’d like to do in the long run, for us and the people we care about.

A challenge for anyone programming at a monopoly, a public company, a well-funded startup or even a non-profit in search of donors is this: Do you have the guts to build an algorithm you can be proud of even if it doesn’t pay off as well in the short run?

Because if the answer is no, blaming the system isn’t going to help anyone. You are the system, we all are, and given the power of invisible and leveraged algorithms, it’s essential that they be created and maintained by people who understand that they’re responsible for the impact they make.

More on this here and here.

An abundance of caution

Lawyers are fond of this.

And sometimes, parents are too.

At least you won’t get blamed if something goes wrong.

It turns out that we don’t need an abundance of caution. We need appropriate caution. They’re different things. Abundant caution is wasted.

Things like ripe avocados and morel mushrooms are terrific to have in abundance. By definition, though, abundant caution is not only more than we need, it’s more than is helpful. Because we get hooked on the feeling.

We can always make a risk ever smaller. But the cost is that we will increase other risks.

Please don’t avoid appropriate caution. It matters to you and to the community. But seeking reassurance and peace of mind by trying to drive risk to zero doesn’t get you either one of them.

Connection, possibility and forward motion are tools for resilience and a healthy life.

Publishers, curation and algorithms

Publishers take two risks to bring new ideas to the world.

(And I’m talking about any middleperson–a gallerist, a TV network, a movie studio, a label–they’re all publishers).

One risk is the time and money spent attracting and supporting the creator/artist.

And the other risk is curatorial. They are risking the trust and attention of the audience by choosing THIS instead of THAT. If they develop a reputation for having good taste (in however the audience defines that) they earn more attention and trust and the benefit of the doubt.

The great publishers might not be famous (Motown was, and The New Yorker is) but they change the culture.

TED takes a risk when they put someone on the main stage or feature a video online. And a podcaster takes a risk when they choose a guest.

The artist gets two benefits. They get the benefit of being picked: cash, editing, the emotional solace of being selected and supported.

And they get the benefit of curation. They reach a scarce audience with help from an organization that’s good at that, and is willing to risk their permission asset to support the artist’s work.

The internet has pockets where all of this is intentionally undermined, often by organizations that adopt the mantle of publisher when it’s convenient.

The Long Tail is Chris Anderson’s term for a library with infinite shelf space, one where the rules of scarcity don’t apply in the same way. The internet platform doesn’t care how many different titles they carry, and in fact, benefits from carrying all of them. Spotify and YouTube and Amazon don’t actually care what you listen to or watch, as long as you come back tomorrow.

Because they have nothing much at stake when it comes to content, and because they are focused on scale, they defer to an algorithm. It’s the mysterious program, by now so complex that no one knows exactly how it works, that decides what works get attention. Even the people who work there guess at what the algorithm wants.

And this has consequences.

Look up a recipe online. It’s a very different experience than finding a recipe in your favorite cookbook. The recipes online offer nearly infinite variety, but they’re largely untested, and they’re formatted in a time-wasting upside-down sort of way because someone decoded that this is what Google’s algorithm would like.

Look at most of the junk in the app store, or most of the content in social media. The algorithm sorts through everything, and when anything can make a buck, anything will.

Of course, there are enormous benefits to the long tail. It gives creators who don’t match an existing editorial paradigm a chance to be heard. It gives readers/listeners/watchers a chance to discover things that would have been unpublished in the old model. And it creates room for discussion and access where it might not have existed.

But…

Publishing to an algorithm is not the same as publishing to an audience. If the creator has no publisher and no permission asset, then being heard is dramatically more difficult. As is getting paid.

And living in a culture that’s driven by profit-seeking algorithm owners is different as well. Because without curation, who is responsible? Who is guiding the culture? Who pushes the boundaries or raises the standards?

Wikipedia has 5,000 curators who work overtime to keep the site from becoming yet another example of Godwin’s Law. Sites that only obey the Long Tail and the primacy of the algorithm have fewer standards. They view curation as a last resort, and if mass is the standard, then mass is all that will be rewarded.

It’s tempting to hope that there’s a hybrid out there. But for that to exist, the algorithms have to work for creators and publishers, not the other way around. The publishers have to embrace the cost of curation, focusing on what they want to promote and paying the price to do so, owning the upside and downside of that intervention.

Culture is almost always improved not by what the masses want tomorrow, but by what a small and dedicated group of people are willing to commit to for the long run. “People like us do things like this” is the recipe for culture.

Creators: It’s possible (perhaps required) to not wait to get picked by a traditional publisher. At the same time, we benefit when we realize that the algorithm isn’t rooting for us and quite probably is working against us. The only winning approach is to earn permission and a direct connection with our fans and then act as curators for ideas (and as our own publishers).

Platforms: It helps to acknowledge that you’re not actually a publisher, that ceding decisions to the crowd and the algorithm and walking away from curation might make you a landlord, but you’re not incrementally improving the culture. Yes, it’s possible to find a middle ground, as Netflix has, but it requires awareness, persistence and discipline.

You probably won’t find this post by searching for it on Google, because they moved my blog down in the results a really long time ago. That’s okay, I’m not writing it for them, I’m writing it for you.

What does it mean to do well in school?

Is it the same as “doing well on some tests”?

Because that’s what we report–that perhaps 240 times in a college career, you sat down for a test and did well on it.

That’s hardly the same as doing well in school.

Where do we look up insight on your resilience, enthusiasm, cooperation, curiosity, collaboration, honesty, generosity and leadership?

Because it seems like that’s far more important than whether or not you remembered something long enough to repeat it back on a test.

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