Daniel Miessler's Blog, page 72

Security and Prosperity Are Both About Perception

Many think security is about ensuring nothing bad happens. They think we’re either secure or not based on whether we stop the bad guys.

But while eliminating bad things from happening is a tidy goal to shoot for, I don’t think that’s the best way to think about security.

Security originally meant a lack of worry, not a lack of danger.

The etymology of the word security is fascinating. It’s a portmanteau from Latin that combines Se (without), and Cura (care/worry). So it’s literally focused on eliminating peoples’ worry, not sanitizing the world.

You can also make someone feel safe by eliminating all evil, but that’s hard.

So it’s possible to have a gap between reality and perception when it comes to security, where you are either in grave danger and feel secure, or are very safe but feel the opposite. As an example, the TSA could be providing little reduction of technical terrorism risk, but still provide security if it makes the public feel better.

Peers and media are two common sources of comparison.

What I find interesting is that prosperity and happiness seem to obey these same rules. It’s not about how well you’re doing on some objective scale; it’s about how well you think you should be doing based on your inputs.

And like security, you can be doing extremely well on numerous objective metrics (health, attractiveness, income, education, etc.), and still be deeply unsatisfied. Or you could be lacking in most of those and be one of the happiest people around.

This is why I have a serious problem with the latest work from Steven Pinker and Matt Ridley. They both speak of historic prosperity metrics as if they’re some official currency of human wellbeing.

They are ignoring the gap between reality and perception, and so is most of the conversation on this topic.

One place we see this is with peoples’ view of violent crime in the US. If you ask most people (around two thirds, actually), they think crime just keeps getting worse. But if you look at crime trends since the late 90’s, violent crime is quite low.

The perception doesn’t match reality, and the perception is what matters.

We see something similar with depression and suicide rates in the US, with both rising massively in the last 20 years. In September of 2018, 96% of teens said anxiety and depression were concerns, with 70% saying they were a major concern. Combine that with suicide rates being up between 20-50% in various groups and it’s clear we have a problem.

It’s not about how great the world is. Or how safe it is. And it’s especially not about comparing those things to the distant past. Humans aren’t inclined towards objective truth. We process narratives, not statistics.

This is especially true in the US.

The problem isn’t reality—it’s our perception of it. There are a thousand reasons to be angry and sad about the state of the world in 2020, but things were unfathomably worse 50 years ago for most people on this planet. Including for women and minorities basically everywhere.

Pinker and Ridley get that part right, but the answer is not to bludgeon people with the numbers. We have to recalibrate our sensors, reset our baselines, and re-evaluate what it means to be happy in the first place.

Both happiness and security describe how you feel about your state, not the state itself.

People are less religious today. They hang out less with their friends. They participate less in their communities. We have fewer life-long goals. And the (often artificial) success of others is thrust in our faces without end.

So we’ve stopped doing that which produces the deepest fulfillment, and we’ve maximized our visibility of—and sensitivity to—the factors that cause unhappiness. We see the rich more than ever. We see other peoples’ suffering more than ever. And new media thrives off of continuously showing us the extremes in every spectrum.

People are empty. They lack a framework for meaning. And in that state, people become vulnerable and hypersensitive to both the happiness and suffering of others. Rich people on vacation? Why don’t I make enough? People in a happy relationship? Why can’t I find love? The rich taking advantage of the poor? The system is broken and hopeless.

There is no positive data from Pinker or Ridley that can fix someone who responds to data in this way.

If someone lives in a first-world country in 2020, is healthy, has a university education, a high-paying job, and reasonable access to the mating pool, they’re already won the data lottery. They’re already doing better than 99.999% of everyone who’s ever lived on the planet. And the vast majority of people living today.

If someone in the socio-economic 5% is deeply unhappy, the answer isn’t to get into the 4%. And it’s not to tell them how bad people have it in the other 96% either.

We need to completely reset our expectations of life. We need to reset our baselines.

Mindfulness. Gratitude. Appreciation of the very basics. Studying history. Reading the biographies of great people who grinded for decades to achieve something. Determining a life purpose. Spending time thinking about someone other than yourself.

We have something like Happiness OCD, where perpetually adding positives to our lives does nothing to improve them.

These are some of the keys to resetting one’s baseline. It’s a different formula for everyone, but this is the hard work that must be done to address this epidemic of unfulfillment and meaninglessness.

People with OCD can wash their hands for hours and still feel they’re filthy. Paranoid people can feel unsafe in the best possible conditions. And we’ve somehow arrived at a similar state, where we can have everything in life and still feel miserable.

For those with OCD and paranoia we recognize their perception as the problem, and we address that instead of buying more hand soap and flak jackets.

It’s time to do the same with human meaning.

Buying another Tumi bag won’t help you, but neither will telling you how awesome it is that Tumi bags weren’t available to people in the 1500’s.

Notes


Let me be very clear about one thing here: I am not a doctor, or a psychiatrist, or any other type of medical professional. I know there are situations both in biology and in life that are causes for concern, and that must be addressed. Not everything is about perception, and not everything can (or should) be solved by “thinking about it differently”. Hopefully you can tell the difference between the two in the piece.
Another interesting way to see how much perception matters is to imagine how Tiffany in Beverly Hills could be distraught and destroyed by getting the wrong color BMW for her 16th birthday, and could actually require hospitalization for her condition. And this could be true while a girl in Congo is overwhelmed with gratitude and joy at being given a set of colored pencils to go to school with, even though her family was killed just a few months ago. Comparing happiness and suffering is so often, and so much, about relative states within a person, not between people. And that’s why this resetting of baselines is so important.
Since a number of people have asked, no, I’m not feeling depressed. But thank you for asking! I write about this so much because I feel that human meaning is the ultimate problem to work on, as a life project. And in this case I was nagged by a single idea, i.e., that happiness and security describe how you feel about your state, not the state itself.

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My Conversation With General Earl Matthews on Election Security

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Unsupervised Learning: No. 215

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My Attempt to Explain Trump’s Reality Distortion Field

With Trump just being acquitted in his senate trial, many people are again asking how Trump does it. How does he disrespect and disregard everyone around him, get enemies to fight for him, make weekly mistakes that would destroy any other politician?

I’ve thought a little about this, but after hearing Sam Harris and Paul Bloom talk about it and ultimately walk away unsatisfied, I decided to take a swing at a description.

First, I think we’re conflating multiple things about the situation. There are many things that contribute to the Reality Distortion Field, or Trump Derangement Syndrome. Some of these include:

He says non-sensical things and doesn’t pay the price
He’s obviously being shady (still no tax returns?) but doesn’t pay the price
His MeToo past has completely failed to stick to him
He turned the GOP from his enemies to his supporters
He bypasses government completely and markets to the people, which control the government
You have a downtrodden white, middle-America cohort that is willing to support him no matter what because he’s promising to bring them back to previous glory
There is actual, acute incompetence in US government, which he’s promised to address
He’s an experienced showman from pro-wrestling and reality TV

The problem is when people try to describe how Trump does X, or Y, the explanation might apply to some of the items in this list, but not to others.

So what I’m going to specifically try to address is how he can be immune to damage from his own mistakes, and how he can continue to attract supporters despite constant blunders.

The theory I’ve come up with is a somewhat simple one: it’s that there is a certain type of male personality—which is actually quite common in real life—that is a special combination of selfish, arrogant, delusional, and relentlessly repetitive about his own success.

This type of person doesn’t like talking about other peoples’ successes. They talk about their own. Everything in their life is great. They have the best business, the best steaks, the best buildings, the best car. The best barber. The best everything.

Their enemies? Worst ever. Dumb. Stupid. Not smart. Worst ratings. Nobody likes them. Total losers.

And this is just at a dinner party with friends.

But if you go to their house it’s the same thing. It’s a single narrative on repeat. They are awesome. Their opinions are the best opinions. They are powerful and successful. And most other people are stupid, unless they’re helping their goals in some way—then that person is a stand-up guy. Until they aren’t.

This type of person uses humiliation and ridicule as their main weapon, drawing power from taking down others. Notice most of Trump’s humor is based on making fun of people. Even his own friends. He makes up nicknames for generals. He totally disrespects almost everyone around him, at least some of the time.

Now, you might think that this would be horribly unsuccessful as a way to live in the regular world. Like, who would tolerate this?

As it turns out, lots of people. This personality type is remarkably effective at attracting followers. They might hate the guy deep down (as so many obviously do with Trump), but they like his charisma, his refusal to admit wrongs, and his constant broadcast of a winning mentality.

They’re hating from a position of weakness, and they like being close to strength, so they tolerate him.

We’ve all heard that assholes get all the girls. And we’ve seen that be effective from grade school through college and into real life. Well ask yourself what assholes and many CEOs have that most regular guys don’t? It’s basically this:

There’s often insecurity on the inside, of course.

An unshakable belief that they are the best.
A constant, repetitive broadcast of that sentiment.
A sense of humor based on making fun of people.
An unwillingness to participate in conversations that aren’t about them and how great they are.
Disdain for people who aren’t powerful or popular in some way.
Seeing everything as a competition that they must win.

If you ask a common follower-type (woman or man) if they’d be attracted to a guy like this, you’ll definitely hear them exclaim, “Never! I hate people like that!”. But notice how they act in their presence and you see something different.

Ted Cruz comes to mind. Supposedly a strong moral backbone (gag), a strong conservative leader (gag), but look who’s following Trump around with a pooper scooper. He’s been turned into a moral cuckold who basically carries water while Trump has sex with everything he used to pretend to stand for.

That’s the power of a charismatic asshole.

They create acolytes all around them, which are treated horribly by the supreme leader, but somehow they feel they deserve it. And when he’s crushing someone with cruelty they’re just happy if it’s not them.

Tech companies are full of these types, and while they might have started the company on their idea and their force of personality, those same Divine Asshole qualities often create the toxicity and dysfunction that inevitably destroy it.

And for the Asshole, it’s a constant battle to suppress the natural, decent tendencies among his followers. If he were to show weakness, stop winning, or stop humiliating people for too long, the spell can instantly break.

Suddenly everyone would look at each other with clear eyes and a bit of embarrassment, and say, “Wow, he’s a really horrible person. I’ve always hated him.”

Everyone will agree, and they’ll vow to pretend the whole thing never happened.

Anyway.

This theory does raise the question of how Trump was able to pull this off when other people with similar personalities would be—and have been—taken out of contention far before the presidency.

Being helped by Putin doesn’t hurt either.

I think that’s where all the other factors come in. Being rich. Being a reality TV star. Being a perplexing combination of idiot and genius. Having a very 50’s and simplistic view of America vs. the world. Etc. I think all those variables just made it so that he was able to survive long enough for his Divine Asshole personality to take hold and start broadcasting its Reality Distortion Field.

And once that starts, it’s hard to stop.

Summary


All Divine Assholes have the ability to disrupt reality and make people love/follow them based on being a horrible person.
This no doubt goes back to our desire to back winners in an evolutionary playing field. If someone in the African plains was killing all the enemies and bringing home the most food, he was going to be the most popular even if (and perhaps because) he was an asshole.
Trump just has the biggest antenna because he’s the president of the United States, which results in the most powerful Reality Distortion Field.

America is particularly vulnerable to the Popular Asshole trope because of our national DNA. Winning World wars. Football. Quarterbacks. Cheerleaders. Wall Street. Picket Fences. Consumerism. Hollywood.

America is about winning, and so is being an asshole. Trump’s presidency is just that dynamic at the grandest possible scale.

This, more than anything, is what makes him dangerous in elections. Just like in normal life, you can’t ask the current or potential follower of an asshole if they like assholes. That’s not good information because they’ll tell you no every time.

But just like in 2016, that’s not what happens when it’s time to pick. When you’re not asking the cheerleader (America) what they like, and instead looking at who they decide to date, well, they pick the rude guy who won the game—not the skinny nice guy who would treat them well.

That’s what America is doing right now. It’s picking Chad, because they think Chad wins games. Until the left figures out that 1) this is the problem, and 2) how to deal with Chads, they’re hopelessly lost.

Talking about how Chad won’t let felons vote in jail is not a solution; it’s an opportunity to get made fun of by Chad on national TV while everyone points and laughs. Same with giving migrants free healthcare when Americans themselves can’t afford it. Sanders might as well be part of Trump’s campaign staff.

The left needs to stop studying political science and debate tactics, and start looking at high-school dating activity.

If you want to see biblical levels of preference falsification and cognitive dissonance, look no further than the groupies and romantic hopefuls fawning over the local bully.

That is what both makes Trump powerful and makes the polls highly ineffective at estimating that power.

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Unsupervised Learning: No. 214

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Unsupervised Learning: No. 213

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The Dark Web Has Nothing on Data Brokers

To regular folks with some basic computer skills the Dark Web seems to be Enemy #1.

People talk about it like it’s the Internet Demogorgon. And the media doesn’t help either, not to mention InfoSec marketing departments. As far as they’re concerned, if you don’t say the name of your password manager 7 times before bed the Dark Web will haunt your closet.

And sure—the Dark Web can be…well, dark. There are actual people selling personal data, credit card data, etc. And some people really go there to steal identities, buy things in your name, and all those cybercrime things you’ve heard about. Plus there are marketplaces for other bad stuff, like drugs, guns, and worse.

So it’s not nothing, and it can definitely be seedy.

But for me, and most of the other security professionals I know, the Dark Web is insignificant compared to its corporate counterparts. There are thousands of companies that legally, professionally, and efficiently collect, organize, and sell your data—and they do so as completely legal businesses.

the various types of data brokers

The biggest US data brokers include Acxiom, Oracle Data Cloud, LexisNexis, and Intelius. Among those, Acxiom is particularly interesting.

According to Wikipedia, Acxiom was founded in 1969 as Demographics Inc., and in 2012 the New York Times said they had the largest commercial database on customers.

Acxiom collects, analyzes and sells customer and business information used for targeted advertising campaigns.

Wikipedia

But the best way to see how powerful they are is to list some of the data they collect and maintain on a given person.

acxiom data profiles track every part of you

There’s a popular story about privacy where a father saw his high-school-aged daughter had received an offer from Target for something pregnancy-related, and he became extremely irate and complained about it. A short time later his daughter told him that, actually, she was pregnant.

This is the magic that makes it possible for advertisers to show you the exact right thing at the exact right time. They simply collect as much as they can about you and keep that information updated in as near to realtime as possible—all so that they can sell it.

In 2012 they had tens of thousands of servers doing this, 24/7, comprising over 50 trillion transactions per year. Those numbers are surely far higher now.

While everyone is looking at cybercriminals and the Dark Web, Data Brokers are doing far more damage to people’s privacy in plain sight.

And to be clear, I’m not saying every iteration of collecting and selling data is bad, always and forever. It’s pretty cool to have high-quality ads when you want them, i.e. ads that are customized for your preferences. It’s part of a future promise of having the world tailored for us.

That’s all great, and positive, and optimistic. We could imagine an implementation of these technologies that was benign—or even beneficial—where people would know the privacy tradeoffs involved, and they would be making them transparently from a position of education.

But we’re not in that timeline right now. Not even close.

Right now most people don’t even know this is happening. They think the real danger to their privacy comes from hackers in basements, when it actually comes from big companies with parking lots, coffee budgets, and health benefits for their employees.

As I wrote about recently, any tool can become a weapon, and right now that tool is personalization. The answer is not to proclaim that all personalization is bad, but its weaponization is—especially when most of the public is completely unaware.

Fixing this has to start with awareness of these companies, and the tradeoffs we’re making by letting them operate without oversight.

If you’re interested in seeing what data brokers have on you, or asking them to stop tracking you, you can do so here and here.

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Unsupervised Learning: No. 212 (Member Edition)

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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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