Daniel Miessler's Blog, page 73

The Difference Between Nihilism, Pessimism, Cynicism, and Skepticism

Cynicism, pessimism, and nihilism are often conflated, but for anyone looking to help people suffering from these ailments, it’s useful to break them apart.

Nihilism is the belief that there’s no meaning to our lives, and that it’s pointless to look for it. There are many flavors of this belief, and they are commonly—but not necessarily—paired with hedonism, pessimism, and cynicism. Importantly, Nihilism is simply the “lack of meaning” component, and not any positive or negative valence that can come with that belief.

Since Nihilists don’t believe in any intrinsic meaning, they often find something to use as a substitute.

Hedonism—the belief that one should pursue physical pleasure as a primary calling—is one option. Another option is to simply be happy-go-lucky, enjoying the surface of things and not looking any deeper than that (since you already know there’s nothing to find).

So it’s definitely possible to be a happy or positive Nihilist, but the state is mostly associated with negative outlooks.

Just keep in mind that Nihilism itself is neutral. Think of Nihilism as an empty vessel. All the Nihilist is saying is that the empty bucket isn’t full of invisible morality and truth and meaning by default. It’s up to them what they put in there themselves.

Pessimism is the lack of hope, the belief that bad things will happen, and that things will get worse. Importantly, this doesn’t require Nihilism. You can be a devout Christian Pessimist. And you can be a Nihilist Optimist. Nihilists probably lean towards Pessimism, but they’re not inexorably tied.

Keep in mind that many people believe they’re skeptics, but are in fact only apply skepticism to things they don’t already believe.

Skepticism is a general attitude of doubt towards claims of truth, especially when the claims are not well-supported. Skeptics often reject almost any claim that doesn’t have extremely good evidence supporting it.

Cynicism is skepticism regarding people and organizations that claim to be selfless, altruistic, and good. If they hear that some manufacturing plant owner paid their employees over the holidays, despite the plant being shut down for repairs, they’re likely to believe they did it for the PR.

Summary


Nihilists just don’t believe there’s meaning in the world, but they can take that belief into positive or negative directions.
Pessimists believe things are going to turn out badly and generally deteriorate, but they don’t need to be Nihilists to be that way.
Skeptics are doubters.
Cynics are doubters regarding people and organizations acting in any way other than their own self-interest.

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The Difference Between Business Intelligence, Reporting, Metrics, and Analytics

After 20 years in technology I’ve taken away one thing when it comes to religious tech battles: When people are disagreeing, they’re probably using different definitions for the various terms.

Business Intelligence is no different. You can spend three hours on Google searching for definitions of Business Intelligence, Metrics, Analytics, and Reporting, and find 3-5 conflicting meanings. And not only different meanings between pieces, but conflicts within the same piece.

This article will provide a framework in which all the terms can be used in a consistent way.

Conflicting views

Most of the rancor comes from vendors who provide one of these offerings to their customers, and their product managers and marketing teams go out of their way to make sure nobody confuses it with a “lower” art form.

Mine is an opinion piece too, but I don’t have a BI product and I purposely started by ingesting all others to triangulate the truth.

Here are some of the differences you’ll see drawn from various blog posts and opinion pieces online. Note that some of these distinctions were legitimate in the past but are no longer the case.

Reporting supposedly only related to the past, which makes sense given that you can’t “give a report” on something that hasn’t happened yet. Realtime reporting in this context just means a very small delta between the past and present, i.e., the report updates quickly.

Metrics is generally the umbrella term that people use for all these terms, which I think is correct. It’s simply a measurement of something.

There’s used to be a common belief that if you can “drill into” a piece of data, that means it’s Business Intelligence rather than Reporting. This used to be somewhat true back when every piece of software didn’t produce interactive charts, but now being interactive has nothing to do with the content’s value or depth of analysis.


One strong distinction was between Operational and Strategic, with these even having separate technical infrastructures in many cases. Basically the Operational systems would be more frequently updated, and the BI system would pull certain data from that system at certain intervals, place it into a separate BI system, and BI reports would only be produced from that second system.

Whether information updated slowly or quickly was also a key distinction in the past, and this is because in the past you would run “reports”, which would often only be monthly, weekly, or daily. As a result, systems that could run reports more often started getting their own names.


Business Analytics seems relatively synonymous with Business Intelligence, meaning it’s more advanced analysis.


My attempt at agnostic definitions

In short, I think these terms are chaotic right now because technology has dissolved many of the distinctions that made them separate.

So what I did was read dozens of these articles online and a couple of Business Intelligence books. Then I triangulated what most agreed upon for the definitions. Then I removed all the definition differences that came from legacy computing. And finally I went back to first principles for what these words mean in other industries and contexts, e.g., “intelligence”.

Data, information, and intelligence


Data are raw, unorganized facts. (“Login from X at time Y.”)
Information is a collection of data that help to answer a basic question (“How many people logged in within this period?”)
Intelligence is the combination of information into a form that tells a story and informs decisions. (“People who don’t go through the training are 74% less likely to make a final purchase.”)

Knowledge is often listed as part of this hierarchy, but I believe that to be incorrect. Knowledge is not something that’s provided by a metrics or BI system, but rather the effect that’s created when information and intelligence are consumed by a user. Knowledge, in other words, is the result within the user that enables better decisions.

Operational, tactical, and strategic


Operational relates to the day-to-day functioning of the organization
Tactical relates to the implementation of the strategy
Strategic relates to the state and trending of the strategy


Metrics, reporting, analytics, and business intelligence


Metrics are just measurements, and they can apply to pretty much everything from the most basic reporting to Business Intelligence.
Reporting is any view of the current state or the past that provides information or intelligence.
Business Intelligence provides intelligence about an organization.
Analytics is synonymous with metrics, but has the connotation of including both information and intelligence in a relatively real-time fashion.


Discussion

Using these definitions we can talk about real-world use cases without tripping all over ourselves. Here are some observations about these different types of metrics.

You can have reports that happen monthly or every second. Update frequency is not part of the definition.
You can have reports that show information or intelligence. A report is just a presentation of something, and the content can vary. Think of it like a “screen”. What’s on a screen? That’s the same with a report.
There is a temporal aspect to Business Intelligence that’s interesting. A modern BI platform should be able to at the very least show you different slices of the past, get you as close to current as possible, and through its intelligence capabilities (combined sources, innovative visualizations that tell stories, narrative, trends, etc.) provide some indication of the future as well.
The use of Machine Learning is not some new tier in the hierarchy of data, information, and intelligence. ML simply helps inform the intelligence side, i.e., people who have X and Y are 93% more likely to do Z within 21 minutes of purchase. In this context think of ML-like Spark or Hadoop; it’s just underlying technology that helps you produce information and intelligence.
You can combine the various definitions above to create different outputs, e.g., Operational Information, Tactical Information, Strategic Intelligence, etc, with the keys being “answering a basic question”, “telling a story”, “relating to basic day-to-day business function”, “implementation of strategy”, or, “state or trends around strategy”. Combining those you end up with a matrix of different types of business value.
Providing operational metrics/reporting is often considered an operational position because issues with the reporting could cause production-related problems. This is another reason that such a bright line was drawn between operational and strategic metrics in the past, as the latter were always delayed and untethered from day-to-day activities.
Highly attractive and interactive interfaces should be separated from whether they’re showing information or intelligence. A good interface can show one, the other, or both. For example, a pivot table in Excel can slice widget sales a million different ways, and if you have the ability to display those views in an attractive, modern, and interactive way then you might be compelled to call it “intelligence”. But the distinction between information and intelligence is whether a story is being told from the content, not whether or not the interface is attractive. Keep those separate in your mind.
At the high end of intelligence lies the ability to make recommendations. The Holy Grail here is, “if you make the following change, we expect the A and B metrics to move by C and D amounts.” Like ML, this is not a new type of intelligence, it’s just better intelligence combined with built-in analysis. It’s moving into the territory of the user of the platform, i.e., decision-making based on what was presented.


Summary

Much of the confusion in this space is caused by people conflating metrics technologies with the purpose of metrics itself.

The entire purpose of all of this—from a printed bar chart to a realtime, next-gen, predictive, AI, recommendation engine platform—is decision support. We’re helping people make better decisions. That’s it.

My recommendation is to think of things as data, information, and intelligence—processed to inform at the operational, tactical, and strategic levels.

Don’t let marketing and other forms of dogma take you away from these first principles.

Notes


A special thanks to Tracy T. for her knowledge in all things data.

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Low-Glycemic Information

Here’s my summary of the book.

In the 1950’s Neil Postman wrote a brilliant book called Amusing Ourselves to Death, which basically argues that text and print are superior mediums for exchanging information, and that radio and TV made us dumber.

He believed that the effort involved in parsing long-form communication mediums is what gave us the value, and that removing that effort—making it easy—removes all its nutritional value.

It was a compelling argument.

And now I wonder if our current bout with polarization and depression in the US could somehow be caused by the extreme end of this spectrum.

Maybe social media and memes are like high-fructose-corn-syrup, and networks like Facebook and Reddit inject these chemicals directly into our neurotransmitters.

Maybe hatred in this form is more potent. And maybe wisdom in this form is little more than water.

Perhaps it’s impossible to become wise if we consume wisdom in the form of candy, because it only comes as meat and potatoes. Free-range meat, that you had to chase down yourself. And large, leafy vegetables that are as green as black, and that taste like the Earth.

We might need slow information the way the body needs slow exercise. You can’t, for example, lower a semi-truck onto yourself as a way to do three years of gym workouts all at once.

Of course there’s a simpler explanation as well, which is that the two are simply correlated.

Maybe sugary content simply stops people from going after the higher-quality stuff, so they never get exposed to deeper ideas. So it’s not that the medium is a problem, but that attractive mediums distract would-be learners into complacency.

It’s probably both.

All I know is that if it were up to me, I’d have large stretches of time in school where inputs are severely restricted. No mobile phones, no YouTube, etc. And I’d expose kids to high-quality written content that is consumed and discussed slowly.

Like leafy green vegetables.

Slow, face-to-face conversations that last a couple of hours. About books with pages. And about the most important ideas known to humans.

I’m not a Luddite. I love tech. I think it’s spectacular. Multiple mediums, fast messaging, always-on connectivity. I’m all about it. The more the better.

But I’m increasingly thinking that we need the other extreme as well to be healthy.

We need to be able to slow down, limit our inputs, open our awareness to the subtlest of vibrations, and consume and discuss ideas at the pace of the campfire.

We don’t have to choose between these two models. We just need balance.

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Unsupervised Learning: No. 211

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Summary: The Infinite Game

Capture


Many efforts in life can be seen as some sort of game.
A game can be defined as something that distracts us from existential depression (not an idea from this book).
Some games in life, like chess and football, are finite, meaning they are short-term, have set rules, a limited number of participants, and the goal is always to achieve some tangible victory.
Some games in life, are, or should be, inifinte, where the rules are wide open, people can enter the field of play at any time, and the goal is to show worthiness that allows you to continue the game. The game of life should arguably be one such game.
A common human problem is treating what should be an infinite game like a finite one. For example, living your life to make as much money as possible, have the biggest house, the nicest car, etc., all the while ignoring a personal cause, a desire to help others, and ignoring deeper things like friendships.
The five principles for the infinite game are: advance a just cause, build trusting teams, study your worthy rivals, prepare for existential flexibility, and show the courage to lead.


Observations


One thing that starkly shows the divide between finite and infinite to me is the idea of competing with friendly peers. People thinking in a finite way think that their friendly peers, or even their friends, doing well is a sign that they’re not doing well. People playing the infinite game are happy for their friends because their competition is with themselves and their long-term goals of being a good person, or a helpful person, and not being better than everyone.
If you find yourself being upset when good people are successful, it’s a symptom of finite game playing. It means you’re focusing too much on other people and relative success, and not enough on your own systems and goals, which should be long-term and identity-based, not achievement-based.


Summary


Much of peoples’ unhappiness comes from playing finite games when they should be playing infinite ones.
If you find yourself unhappy, ask yourself what your Just Cause is, and whether you’re focusing too much on other things instead of it.
Competition with peers and friends is finite thinking.

Find my other book summaries.

Notes


This work comes from another author who came up with the idea, but his book was hard for me to follow. So I’m thankful that this book exists to make the original ideas consumable.

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Summary: Atomic Habits

These book summaries are designed as captures for what I’ve read, and aren’t necessarily great standalone resources for those who have not read the book. Their purpose is to ensure that I capture what I learn from any given text, so as to avoid realizing years later that I have no idea what it was about or how I benefited from it.

Capture


It’s not about goals, it’s about systems.
The way to change outcomes is to focus on identity changes; so it’s not about eating less, or eating more healthy, as a behavior—but rather that you are now the type of person who eats better.
Habits are the compound interest of improvement, and that works in both directions. If you owe it, it digs you a grave, and if it’s accruing for you, you’re doing really well.
The four laws of behavior change are: make it obvious, make it attractive, make it easy, and make it satisfying.
The trick isn’t to have unbelievable willpower; the trick is to craft an environment where it’s easier to make the right choices, and that’s part of the system.

You don’t rise to the level of your goals, you fall to the level of your systems.

Atomic Habits, James Clear

It’s far worse to miss days in your system than it is to continue them.
If you want to see your future, just imagine behaving exactly as you have in the last period of time.
Breakthroughs come suddenly after repeating a system, not all at once while chasing a goal.
Improving by 1% a week, or even per month, adds up massively over time.
There are three tiers of penetration for behavior changes: the outermost is outcomes, the next one in is process, and the bullseye is identity.

Every action is a vote for the person you wish to become.

Atomic Habits, James Clear

Habit stacking is where you connect a new, desired habit with something you have to do every day anyway.
Time and location are the biggest triggers.
We tend to mimic the habits of people close to us, the masses, and the powerful.
Bad are attractive when we associate them with something positive. So that’s the thing we have to break.
Focus on action, not motion.
It’s more important to do a habit often than it is to have been doing it for a long time.

When you start a new habit, it should take you less than 2 minutes to do.

Atomic Habits, James Clear

The trick is to make the system satisfying, not the goal.
I need a habit tracker for eating less, meditating, lifting weights, and getting cardio.
Never miss twice. If you miss a day, get right back on.

The Goldilocks Rule states that humans experience peak motivation when working on tasks that are right on the edge of their current abilities.

Atomic Habits, James Clear

Professionals stay on a routine while amateurs let life get in the way. This reminds me directly of War of Art.


Observations


This is a lot like Infinite Games, which talks about the difference between having long, meaning-based and sustainable goals that you accomplish through a system, vs. short, aggressive goals that don’t necessarily point in the right direction and require constant resetting.

The purpose of setting goals is to win the game. The purpose of building systems is to continue playing the game. True long-term thinking is goal-less thinking. It’s not about any single accomplishment. It is about the cycle of endless refinement and continuous improvement.

Atomic Habits, James Clear

Summary


It’s all about the system. Your system is what determines what you’ll become.
Serious people stick to the system and the plan, and don’t make excuses for life getting in the way.
Habits are compound interest in the outcome of your life.

Find my other book summaries here.

Notes


This is by far the best book on habits I’ve ever read.

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Visibility and Understanding Create Both Tools and Weapons

Being in security I think a lot about whether things are tools or weapons.

The distinction applies to guns. It applies to encryption. It applies to offensive security tools. And it applies to technologies like machine learning and the use of AI-monitored cameras throughout society.

The link I’m highlighting here is:

Visibility plus Understanding --> Tools and Weapons

Visibility means you have the opportunity to observe a given object or behavior, like a message sent between people, or people traveling from place to place.
Understanding means you can learn a lot about that thing once you see it, like who it is, what it is, how it’s built, how it works, etc.

This applies to so many things. People, bridges, locks, neighborhoods, and populations.

If you know precisely how DNA and human biology work, it’s easier to make DNA-based biological weapons.
If you know how bridges work, and how to build them, it’s much easier to blow them up.
If you know how web applications are built, it’s a whole lot easier to break into them.
If you have visibility into everyone moving within a city, and you can see their faces, and you have ML algorithms and facial recognition software monitoring those feeds, you can learn a lot about everyone being watched.
And if you know psychology, sociology, and neurobiology—and you combine all those disciplines with knowledge of people’s biometric data, their facial expressions, their body language, etc.—you end up with the ability not just predict their behavior, but to influence it.

Medicine and Bioweapons. Civil Engineers and Terrorists. Personalized ads and Population Control. This is the curse of progress.

Weapons are mirror images of tools. The insight that gives you one gives you the other simultaneously. It’s only a question of time.

Humanity’s chances hinge on maturing fast enough to contain the weapons that emerge from the tools that we cannot help but create.

We’re so in love with new functionality—and the money that comes with it—that slowing down is not an option. We run in dark rooms carrying scissors because we don’t want to be outside when someone else finds the treasure.

The best we can hope for is a series of small mistakes that hurt us enough to pay attention, but not enough to end us. This seems to be what the Unibomber saw, and why he thought it was acceptable to kill.

He was wrong about that, and also to think what he did could make a difference.

There are billions of dollars being spent right now—using our planet’s smartest minds—to create the breakthroughs that will enable bioweapons, autonomous attack drones, and algorithms of population-scale manipulation.

I find it pleasantly ironic that an atheist like myself is resigned to faith as a strategy against despair.

I’m not sure it’s faith actually. More like resignation—to the unfolding of the universe.

Here’s to hoping we master the tools, and ourselves, before civilization-ending weapons become too easy to create and use on each other.

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Visibility and Understanding Lead to Tools and Weapons

Being in security I think a lot about whether things are tools or weapons.

The distinction applies to guns. It applies to encryption. It applies to offensive security tools. And it applies to technologies like machine learning and the use of AI-monitored cameras throughout society.

The link I’m highlighting here is:

Visibility plus Understanding --> Tools and Weapons

Visibility means you have the opportunity to observe a given object or behavior, like a message sent between people, or people traveling from place to place.
Understanding means you can learn a lot about that thing once you see it, like who it is, what it is, how it’s built, how it works, etc.

This applies to so many things. People, bridges, locks, neighborhoods, and populations.

If you know precisely how DNA and human biology work, it’s easier to make DNA-based biological weapons.
If you know how bridges work, and how to build them, it’s much easier to blow them up.
If you know how web applications are built, it’s a whole lot easier to break into them.
If you have visibility into everyone moving within a city, and you can see their faces, and you have ML algorithms and facial recognition software monitoring those feeds, you can learn a lot about everyone being watched.
And if you know psychology, sociology, and neurobiology—and you combine all those disciplines with knowledge of people’s biometric data, their facial expressions, their body language, etc.—you end up with the ability not just predict their behavior, but to influence it.

Medicine and Bioweapons. Civil Engineers and Terrorists. Personalized ads and Population Control. This is the curse of progress.

Weapons are mirror images of tools. The insight that gives you one gives you the other simultaneously. It’s only a question of time.

Humanity’s chances hinge on maturing fast enough to contain the weapons that emerge from the tools that we cannot help but create.

We’re so in love with new functionality—and the money that comes with it—that slowing down is not an option. We run in dark rooms carry scissors because we don’t want to be outside when someone else finds the treasure.

The best we can hope for is a series of small mistakes that hurt us enough to pay attention, but not enough to end us. This seems to be what the Unibomber saw, and why he thought it was acceptable to kill.

He was wrong about that, and also to think what he did could make a difference.

There are billions of dollars being spent right now—using our planet’s smartest minds—to create the breakthroughs that will enable bioweapons, autonomous attack drones, and algorithms of population-scale manipulation.

I find it pleasantly ironic that an atheist like myself is resigned to faith as a strategy against despair.

I’m not sure it’s faith actually. More like resignation—to the unfolding of the universe.

Here’s to hoping we master the tools, and ourselves, before civilization-ending weapons become too easy to create and use on each other.

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Why High-end Podcasts Reduce the Bass in their Audio

I’ve been podcasting for around 5 years now, and at some point in the process, I became obsessed with mics and sound and recording.

For a while I used an RE-27 mic, which was quite nice, but I recently upgraded to a U87AI, by Neumann. It’s probably the world’s most respected mic, used by NPR.

The sound that I thought I was into was a clear, deep sound, and I had created that in various ways over the years.

But then I read a piece about how NRP acheives its famously grep podcast sound, and it was all about doing the exact opposite.

Basically, when people are traveling, driving, on trains, or just generally out and about, there is a lot of low frequency droll.

Like a deep hum that blends into the background.

And what NPR found was that audio that had these low frequencies in it would often get drowned out by—or mixed in with—that noise.

So they decided to cut through using higher frequencies.

They recommend activating low-pass roll-off, either on your mic itself or post-production, which takes that deep rumbly bass out of the voices, and speaking at an oblique to the mic from around 6-12 inches away.

This is taking some getting used to because I love that other sound, but I’m trying to see this as outsourcing a problem to NPR for the last 20-30 years.

They have high-end people who’ve come to this conclusion after decades of experimentation, so who am I to argue with that?

So if you want to make your audio more NPR-like, apply a low-pass filter so your product can cut throught the din.

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San Francisco is a Microcosm of America’s Future

San Francisco is a strange place.

In one part of town—on any given weekday—you can see tens of thousands of 20-50 year-olds scurrying to their top 5% jobs.

They are educated, they have careers, and they’re minds are on their work, their hobbies, and a search for meaning in it all.

But walk for 10-20 minutes and you can be surrounded by a complete breakdown in society. The sidewalks are littered with human feces and drug paraphernalia. There is garbage everywhere. And people are gathered together without anywhere to go or anything to do. Naturally, it’s a center for suffering and crime.

This area doesn’t just cover a few blocks like most think. It’s actually a massive part of the heart of the city—a city that’s much smaller than people imagine.

This is getting some attention, of course. The media has been highlighting the homeless encampments, the crime, the drugs, the bad roads, the lack of affordable housing, etc.

But the craziest part about this isn’t actually how bad it is. It’s how bad it is just a few blocks from the richest place in the world, with the people there completely ignoring it.

Police—when they are there at all—stand in these areas as if they’re in Mr. Rogers’ Neighborhood. They completely ignore drug use, mentally deranged people, overt littering, and much worse. It’s invisible to them, like everything is ok.

And the privileged people with—you know—jobs and careers and stuff—we do the same. We walk through these areas casting whatever spells in our minds that keep us sane.

We should be doing more to help these people.



This is a travesty. We should be ashamed.



I wish someone would just take all these people somewhere and clean this all up.



This is why I am ok with paying higher taxes; that’s my way of helping.



I need to do more to help with this, but I don’t know what to do.

The Poverty Patronus

We mutter these incantations like a Poverty Patronus that protects us from crumpled bodies on the street, shuffling zombies looking dead-eyed at us as we pass, and all the other poop-shaped affronts to our civilized nature.

Then the phone rings, or we get to work, and it’s time to prepare for that next meeting.

Everything is fine. Nothing to worry about. It was all a bad dream.

Except it’s not. It’s not fine. It’s not ok. And some people—the people you passed actually—didn’t actually wake up from the dream. They’re still living it.

So that’s one point: the people in the top 5% live right next to the people at the bottom, yet neither society (the city, the police, etc.) nor the people (you and me) do much to improve it.

The second point is that this is happening all over the country. Hayes Valley and the Business District are the vibrant coastal cities, and The Tenderloin is becoming everywhere else in America.

We’re producing violent disharmony in this country right now. Disharmony in education, in job opportunities, and in lifestyle. And those divides are like tectonic plates: sooner or later they will make noise and snap back in place.

We saw some of that in 2016, and I think we’re likely to see a lot more in 2020.

If you look at the stock market, the tech sector, and the thriving businesses at ski resorts and meditation retreats, things look quite healthy. We’re doing amazing!

Well, no. We’re not.

You are. I am. But we’re not America.

We’re in the Business District. We’re in Hayes Valley. We’re in the top 20%.

The rest of the country is quietly suffering. They need multiple jobs to pay rent. They are getting pillaged by profit-focused healthcare pricing. And their children have grim options even if they do go to college.

America is becoming Downtown SF surrounded by The Tenderloin, and we step over those bodies on the way to work at our own peril.

As Piketty tried to tell us, the Patronus will only hold for so long.

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