Posts Tagged 'Trust'

Fear of Fear

fear of fearMost of the things we avoid are avoided because we’re afraid of being afraid.

The negative outcomes that could actually occur due to speaking up in class, caring about our work product, interacting with the boss – there’s not a lot of measurable risk. But the fear… the fear can be debilitating, or at the very least, distasteful. So it’s easier to just avoid it altogether. We avoid the feeling of fear.

On the other hand, artists and leaders seek out that feeling. They push themselves to the edge, to the place where the fear lives. By feeling it, by exposing themselves to the resistance, they become more alive and do work that they’re most proud of.

It usually looks higher from up there. When we find ourselves on the edge of a precipice, looking down at the depths of the chasm below, it’s easy to think that our plan is far too risky, or our behavior too weird.

The funny thing about perspective is that most bystanders don’t see you standing on a precipice at all. They see someone doing something a little risky, or even questionable, but by no means off-the-grid nuts. You’re far more likely to go not-far-enough than you are to go too far, especially if you tend to find yourself worrying over what others think.

Internal monologue amplifies personal drama. To the outsider, neither exists. That’s why our ledge-walking rarely attracts a crowd. What’s in your head is real to you, no doubt about it, but that doesn’t mean the rest of us can see the resistance you are battling. And most don’t care about it.

How deep is the water? If it’s over your head, does it really matter?

At some point, when the stakes are high enough, you will swim. And when you swim, who cares how deep the water is?

How much does it cost you to avoid the feeling of risk? Not actual risk, but the feeling that you’re at risk? What are you missing out on? Feeling risk is very different than actually putting yourself at risk. Over time, we’ve created a cultural taboo about feeling certain kinds of risk, and all that insulation from what the real world requires is getting quite expensive. It’s easy to pretend that indulging in the avoidance of the feeling of risk is free and unavoidable. It’s neither.

The fear doesn’t care, either way. The choice is to spend our time avoiding that fear or embracing it.


Reasons or Excuses


When something goes wrong we quickly build ourselves a narrative about it. The story we tell ourselves isn’t objective, and often doesn’t even mesh with reality in more than a cursory way. Let a little time pass and that story becomes the totality of the event. It includes our interpretation of the circumstances, rationalizations for what we did, how we perceive others behaved or reacted, etc. We develop for ourselves a reason that satisfies our need to make sense of it.

Reasons or excuses? What are they, and what differentiates these emotionally loaded terms? Culturally, reasons feel to us like valid explanations, whereas excuses feel invalid and lacking in accountability.

Let me give you some examples. Common excuses for why restaurants, or other businesses, fail include:

  • Our purveyors were cheating us
  • Our concept was too progressive for the market
  • The market didn’t appreciate good food
  • Our landlord was unreasonable

The list is much longer than these few highlights. There are as many excuses for failure as there are failed businesses. If a person were to take accountability for their decisions and their actions, those excuses could be seen as the real reasons for failure, and they would look more like this:

  • We didn’t know anything about negotiating purchasing, and ended up paying prices we couldn’t afford to pay
  • We didn’t research our market well enough to find out what the market wanted, so we ended up giving them what OUR idea of good food was, not theirs
  • We failed to communicate what made us special compared to the competion, and the market didn’t respond  – or – We didn’t realize that our market doesn’t have the same ability to notice quality that we have, and we were really banking on them realizing our food was better
  • We didn’t negotiate a good lease – or –  we didn’t learn enough about leases going in to be able to effectively negotiate a favorable one

Recognizing the lack of accountability in the first set relative to the second is the easy part. Culturally, we seem to lump excuses into a morally questionable realm, almost as if they are lies. Excuse, by definition, connotes an attempt or request to not be held accountable.

“I was late for class because I was held up by a train.” Assuming the statement is truthful, is it an excuse or a reason? As a statement of fact, it fits with being a reason. If there is an implied request to not be penalized in some way, then it starts to feel like an excuse. The moral attitude (with its limitations) starts to surface here: you should leave in time to allow for being held up by a train. Of course, what if the person did, but the train was unusually long? We don’t have to go far down these technical rabbit holes to see that the language and implied meaning can be broken. Suffice to say that they are contextual and judged in the perception of the speaker and hearer, who are not always on the same page because communicating the nuances thoroughly can be difficult and time consuming, not to mention emotionally taxing under some circumstances. Sometimes one party just doesn’t care enough to worry about it.

“I can’t.”  As I have written before, this is often code for, “I don’t want to enough.” Again, the easy ones are statements such as, “I can’t seem to lose weight,” or “I can’t make it to your important event.” The former feels like an excuse, even though we know there can be very valid reasons. The latter feels like it probably has a reason behind it. Thus is how culture and context drives meaning. The trickiness of the second example is often in the desire not to hurt people’s feelings. We dance around and make excuses, when the cold, hard truth probably is, “I don’t care enough about your event to miss out on the other thing I have to do.” Now it sounds even more like a reason (though not very tactful).

There are some things we simply can’t do in life, but most are choices we make.

“I can’t go out with you because I am already dating someone.” Most would be satisfied that this sounds like a reason, but is its really? The word “can’t” adds a weird layer of a lack of accountability, and therefor moves the statement toward feeling like an excuse, even if it’s deemed to be a valid one.

“I do not want to go out with you because I am already dating someone.” That’s closer to owning the accountability of it.

“I don’t want to go out with you because I believe that the risk of hurting the relationship I am in outweighs what I assess to be a very small chance I would be happier with you.” Or, “I don’t want to go out with you because I don’t feel attracted enough to break a date with this other person I like.”

Do you feel how these are getting uncomfortable? Excuses are often an (empty) attempt to keep comfort in tact by avoiding accountability. Reasons cut to the real truth of the matter.

It could also simply be, “I do not want to go out with you.” Sometimes what gets us into trouble is trying to provide a reason, and usually the reason is where it starts to feel like, and often is, an excuse.

Oh, but there is more.

Truth and trust become important currency when you’re in some type of valued relationship with someone. It’s easy to find ourselves caught between two valid concerns:

  1. I want and need to be honest with this person because…
    •  It seems like the ‘right’ thing to do
    • I want to maintain an assessment of trust;
      • It makes me feel good
      • I hope they will respond in kind
    • I believe it is in their best interest to know the truth
  2. I want to be dishonest with this person because…
    • I want them to feel validated, or not be hurt
    • I want to maintain the good feelings we have between us
    • I want to avoid conflict
    • I don’t want them to negatively assess me (as being rude or insensitive, a jerk, an idiot, etc.)
    • I believe it is in their best interest not to know the truth

You’ll decide to lean more toward one than the other, as conflicted of a choice as it may be. We can weigh it all out and try to do the least worst thing, but so much of what we often choose to do really boils down to our own comfort and desire to be liked.

An additional complexity of either of them is that sometimes the hearer just doesn’t buy it, and will believe you are operating in #2 whether you are or not. Now the speaker has lost the assessment of trust, the hearer is hurt, there are bad feelings, and potentially bad characterizations. Thus is the risk of the dishonest route, or is one of the nasty consequences of a weakness in trust and/or a weakness in the hearer’s self-esteem. It could also just be a misunderstanding or faulty assumption on the part of the hearer. In either case, now the tables are turned (insert dramatic music here). Now it is the hearer who must decide between #1 and #2. He can call out his concern to the speaker, or he can move along quietly with the bad feelings. Let it go, or ferret the truth out of it? Tough choice with the same pitfalls.

So this just turned into a post about how vital communication is between people who care about each other. It’s about how we have to accept the flaws in communication, the mistakes we make, and to a degree even the flaws in each other that lead to these mistakes. We need to give the other person grace, to empathize with how difficult it can be to parse through it all to find the right balance on the continuum between brutal honesty and smarmy validation, or between letting the other person save face versus the value of holding them accountable, all in the unavoidable context of our own comfort.

Probability: Facts, Statistics, and Reality

What is reality? Statistics are based on facts. We can’t deny or ignore them. But they aren’t always factual, or even meaningful.

I am a statistic and so are you. I drive a car. I eat. I buy things. I have an education. I don’t smoke. I was born at a place and time. I am programmed by my surroundings and DNA.

We use prior facts and statistics to reason with uncertainty, to get at probability, but we suck at it. In general we are really, really, staggeringly incompetent at processing all but the simplest statistical data in ways that produce meaningfully accurate evaluations. This is partly because it is much more difficult than it appears on the surface. We aren’t rigorous enough. But it’s also because our intuitive way of understanding complex relationships is…well…it’s too simplistic.

A Quick Lesson in Photography (It’s relevant, run with me)
In photography one learns about the relationship between the glass of a lens, the distance to the subject, and the focal point, which is where the image passing through the curved glass is in focus. The curvature, or varied thickness of the glass, bends light. Distorts it, providing a means to get a reasonably coherent image on to a sensor (without this, all light from all angles will hit the sensor, producing nothing more than a gray blur).


So a lens allows us to pick an area to capture, just like the position of your eye picks an area of the overall scene to project onto your retina through its lens (your brain further filters this into what it chooses to focus on). The focal point is where the image comes into focus after passing through the lens. The focal length is the focal point’s distance from the lens.

Modulating the distance between the lens and the subject changes focal point.


In short, there is a relationship between the shape of the lens, the distance to the subject, and the distance where light reflecting off of that subject that passes through the lens will come into focus. Five minutes playing with a magnifying glass gives one an intuitive understanding of this. Note: the eye changes focal length by changing the shape of the lens, whereas a camera does it changing the distance between two (or more) lenses. All of these ingredients, and others to follow below, interact with one another to vary the result.

Simple? Well, it’s not that simple. There is more. (Hang in there.)

In around 1000 A.D., Arabic physicist, Ibn el-Haitam penned the first known accurate and comprehensive description of how light is refracted by shaped glass. This led to the development of a myriad of mechanical devices that provided augmentation for human vision. Through a combination of lenses, we can “zoom in” on specific parts of a scene, bringing things far away closer to us for better examination.


In Astronomy, however, the concept of “zooming in” isn’t as significant, even though it would be cool if we could zoom way in to distant objects. At those great distances our earthly lens ratios don’t accomplish much. And we can’t change the ratios too much due to diffraction. Diffraction, or the scattering effect of light, always exists when light passes through or around something, or is reflected. Diffraction essentially acts to defocus the image, which means that as the magnification or zoom increases, the sharpness and clarity of the image breaks down. This defocusing is inversely proportional to the diameter of the lens, not to mention the optical quality, but is always an issue. It’s one reason why the best telescopes have a large diameter.



Larger f numbers indicate smaller openings. Intuitively one can see that zooming in to any of these images would cause an increased breakdown in apparent focus.


The other reason for wider lenses is because they are inherently able to gather more light, which is pretty important for looking at far away stellar objects, some of which are so faint they cannot be seen by human eyes or conventional optics.



Gathering more light is also useful in earthbound photography. More light reaching the sensor allows it to record the scene quicker, which makes it easier to freeze the motion of moving images. Aesthetically this may or may not be desired. Note how these different capture speeds reflect different interpretations of “reality.”


As capture speed slows, the motion of the water is revealed in different ways. The image on the left shows the exact position at an instant in time. The rightmost image shows the average position across a period of time.


The actual speed of the pinwheel was the same in all instances.


Wider lenses come at a cost beyond the expense of manufacturing them. As we let more light in, and reduce diffraction, we simultaneously narrow the range of distances from the source to the camera that will appear in focus because light is hitting the sensor from wider angles off dead center.



Photographers refer to the range of distances that will appear in focus at the focal point as “depth of field.” With larger apertures and lenses more precision in focusing is required, which is generally manageable, but the impact it has on the resulting photograph can be significant.



More or less of it my be desired, depending upon the look one wants. Like speed, the depth of focus also serves to depict different views of “reality.”




It is a very useful consideration for pulling the attention of the observer to a specific part of an image.



One can look broadly at an image and not see the distortions in the domains of time and clarity, but careful examination will reveal them. They can’t help but be there. We can capture a scene in a way that emphasizes or de-emphasizes certain of those, but in the immortal words of Scotty, “You can’t defy the laws of physics.”

We trust what we see with our eyes, too much. No doubt the reader has now surmised there is a matrix of trade-offs in what we “see” when we capture an image based on these parameters. Photographers make choices, intentionally and unintentionally, that affect the outcome. Observers usually take the photo at face value, with no regard for the actual reality of the scene, instead letting the photo determine the reality we believe existed in the moment.


Now, apply that same thinking to statistics and one can begin to see why it is so commonly held that statistics can be used to support nearly any conclusion. Unfortunately what often happens is that they are used too generally. Reputable (*) sources say things like…

  • 10% of our brains are used
  • 50% of marriages end in divorce
  • we share 99% of the genetic code
  • left handers die an average of 9 years younger than right handers
  • 18% of social media users use snapchat
  • 77 cent wage gap between women and men
  • 20% of women are sexually assaulted before they leave college
  • 0.0024% of deaths are from electrocution
  • men think about sex every seven seconds
  • The religion of Islam is growing at a rate of 2.13% per year
  • spousal abuse skyrockets on Super Bowl Sunday
  • The average household income in the U.S. is $70,000, or…
  • Any of the stats that show that the top X% earn [staggeringly large number]%
  • 80% of convicted sex offenders repeat the crime
  • 50% of 18-24 year-olds go on Facebook when they wake up
  • 30.5% of all desktop search traffic between 6/10/16 and 7/7/16 came from searches with the term “pokemon” in them
  • (my personal favorite – LOL) 90% of statistics can be used to say anything 50% of the time

There are so many more I could use: Crime Rates, School Quality, Unemployment, Mortality, Cost of Living, Obesity, Literacy, Birth Rate, Gun Control, Teen Pregnancy, on and on…

They are all generally accepted as true, yet none are precise across the board (stay tuned for a future blog post delving into the difference between precision and accuracy). There are nuances in specific ages, cultures, geography, time, education, temperament, weather, situations, and any of dozens of other variables that come into play. They are generalizations. Averages. Broad snapshots, or maybe narrow ones. Very useful as shortcuts to learning and not basing too much on mere assumptions, but also misleading in some ways. Many sound plausible. Some we believe. Some we would question. Some are subject to varied interpretations. Some are patently false. I’m not just referring to the inevitable weird exceptions that are in the noise of any statistical model. Noise is random. I’m talking about correlatable things with some significance that are missed, ignored, or misinterpreted.

For instance, Psychology Today based an article on the 10% of our brains get used statistic. We’re easy prey for this because we’ve been hearing variations on that number most of our lives. None of them account for what the data really says, which is that a small portion of our brains are used at any given moment, in a given activity, or for a given purpose. Other activities and functions require other parts of our brains to be used. The real number is significantly higher than 10% when all of this is factored in.

I can, to some extent, debunk every one of the above listed items with rigorous research, but then who says my facts are really correct? More significantly, is the interpretation of the data correct? For instance, the divorce rate of 50% seems pretty concrete. We have records to prove it, so there is no questioning the data, right?

If that’s the case, then why are the quoted stats sometimes so “approximate?” The APA website says “40 to 50%.” That’s a massive difference for something that seems so concrete. Further, we all seem to believe it, or do we? We accept it. But…most of us get married anyway!!! If you knew that you had a 50% chance of getting struck by a bus while crossing a street, would you dare to cross in spite of it? A little thinking and reading quickly leads us to realize there are tons of potential nuances to a statistic like this. So many it isn’t practical to try to list them all.

But there are also fundamental issues that skew the data. How is it calculated in the first place? Often the number is reached by simply comparing divorce filings to marriages over a given span of time. Make sense? It does on the surface, but it doesn’t necessarily tell us much because over time things change. Okay, well, what if we compare divorce and marriage rates in a given year? That’s a pretty short span of time and would seem to be a suitable snapshot. So, let me get this right…you want to add up all of the divorces in a year, no matter how many years all of those people have been married, with no consideration to when they were married or under what circumstances, and compare them to marriages this year? Doesn’t really work. As with photography, anytime you capture something moving in a static “image” or focus on a part of it, you’re forced to make decisions about how to present it to meaningfully convey the result. If anything, we should be comparing all people who are currently married to those getting divorces in a year, but it’s almost never done that way.

Yet we buy in. We’ve all heard the statistic so many times that it rings true to us, to the extent that nowadays any data showing something different would be called into question. We have become biased, mostly (in this case) by our own inability to effectively pick the data to look at, or in interpreting what it really means. And yet most of us decide to roll the dice and get married anyway.

We often apply statistics to provide probabilities about how the future will turn out. Seems simple enough. If 20% of children outgrow a childhood allergy to peanuts, then you could assume your peanut allergic child has a 20% chance of doing the same. It’s also easy to see there could be many subsets that could introduce other variables. Is the percentage the same across race? How about across a range of medical treatments or diets or subtle variations in DNA? That’s just scratching the surface – the basics.

Consider this test. Two groups of people engage in a coin flipping exercise. Group A looks for the pattern H-T-T (Heads, Tails, Tails), and Group B looks for the pattern H-T-H (Heads, Tails, Heads). Each member of each group records how many coin tosses it takes before the desired pattern occurs. The two groups then average their respective results. Do you think the average number of tosses between the groups will be the same, or will one of them happen sooner on average? (Don’t worry, most people, even very smart ones, get this wrong.)

It turns out it’s statistically provable that the average number of tosses to reach the pattern H-T-H is 10, while the average number to reach H-T-T is only 8. How could this be? It butts up against our common sense on the matter. If anything we would think that H-T-H would be easier to create, since it overlaps itself. Throw a T between any two occurrences of H, and viola!

But think about what happens the first time you get an H followed by a T. At that point, either of the two results can now occur.

Group A: you’re looking for H-T-H, and you’ve seen H-T for the first time. If the next toss is H, you’re done. If it’s T, you’re back to square one: since the last two tosses were T-T you now need the full H-T-H.

Group B: you’re looking for H-T-T, and you’ve seen H-T for the first time. If the next toss is T, you’re done. If it’s H, this is clearly a setback; however, it’s a minor one since you now have the H and only need -T-T. If the next toss is H, this makes your situation no worse, whereas T makes it better, and so on. Even when you lose you’re 1/3 of the way to winning.

Put another way, in Group B, the first H that you see takes you 1/3 of the way, and from that point on you never have to start from scratch. This is not true in Group A, where a H-T-T erases all progress you’ve made.

People write articles and make declarations every day who do not understand these types of relationships. We read them, and we usually believe them so long as they sound credible (often through citing studies and statistics) and/or match sufficiently with our common sense or already held beliefs.

Bipolar Disorder affects 3% to 5% of the population according to Gary Sachs, director of the Bipolar Clinic at Massachusetts General Hospital. It affects 2.6% of the population over 18 years old according to WebMD. The U.S. National Library of Medicine has been summarized as saying that it occurs more in women. The DBSA (Depression and Bipolar Support Alliance) say it occurs equally in women and men, but women tend to cycle faster. Closer examination, however, reveals that Bipolar II (a predominance on the depressive side) occurs more in women. These are basic examples of statistics being in general agreement, but presented in ways that show differences.

What about clinical testing? What if there is a test that is 99% accurate. When it returns positive, you could assume that there is a 99% chance the positive result is true, no?

Two problems…

  1. I have pointed out that there is almost always a higher level of detail or granularity that can be considered to further classify and characterize the risks of different individuals.
  2. It also depends on how common or rare the condition is. Suppose the condition affects 1 of every 10,000 people. If we sample a million subjects, the test will get the 100 who do have the condition right 99% of the time. 99 of them will test positive. Amongst the 999,900 who do not have the condition, the test will get it right 99% of the time, which means it will improperly show that 9,999 of them have the condition, when in fact only about 99 of them really do. So, less than 1% of the people who test positive actually have the condition!

Consider the case of Sally Clark. She was convicted of murdering her two male children, one of which died in 1996, and the other in 1997. Defense claimed it was likely SIDS that took them, but the prosecution, through expert witnesses, won, in part by showing that there was only a 1 in 73,000,000 chance that SIDS would affect two children in a single household.

Wrong, in two ways.

  1. The calculation was faulty. It was based on the probability of SIDS affecting a child of affluent non-smoking parents being 1 in 8,543, so therefor the odds of two children suffering from it are 1 in 73,000,000 (8,543 x 8,543). But this doesn’t allow for the fact that we don’t completely understand what causes SIDS. There are clearly unknown environmental and/or biological (hereditary) factors. It’s quite likely that if a child dies from SIDS that some of these unknown factors are in play, and may increase the likelihood of it affecting other children by a factor of 5 to 10.
  2. Even if 1 in 73,000,000 is correct, the statistical analysis of murder suffers from the same flaw as the medical example above. There are two parts to the explanation that must be considered independently. 1) That Sally was innocent – which is likely considering most mothers don’t murder two children – and she suffered an incredibly unlikely event. 2) She is guilty, which is unlikely, but if she were trying to kill them, she succeeded.

Figuring that out statistically is much more complicated, and in fact there are significant factors that could have and should have been considered from the get-go, such as the details that boys are more likely than girls to suffer from SIDS. She was eventually released from prison after the second appeal, which more carefully broke down the statistical odds of a double murder to between 4.5:1 and 9:1. Still likely, but hardly conclusive enough for a life sentence based on weak circumstantial evidence.

We can be pretty good at questioning conclusions from people who we believe are unlikely to have competence in a particular area. If the subject matter expert of the court had tried to present arguments about diagnosing an automotive problem, no doubt there would be suspicions. But this expert was in the field, and presumed to understand the data upon which he was drawing conclusions. Yet he got it way wrong, and nobody questioned it.

Sally, after spending a few years in prison as a convicted murderer of her two children (probably not the most enjoyable of prison stays, as far as prison stays go), died of an alcohol overdose a few years later. Her husband said she was never the same after that experience. There is more nuance and information on this story, but the takeaway here is that facts and statistics as used severely mischaracterized the likelihood of a natural death.

Data and stats should be subject to much more scrutiny than they commonly are. But we need them. We need the shortcuts, assumptions, and predictions they provide. It’s a shame we so often get it wrong, because it skews our perceptions and causes faulty decisions. But even where the data and conclusions are relatively good, which as laypeople we often have no way of knowing for sure, we often fail to see into the exceptions.

A whole pile of data can suggest that something is generally true, yet in certain circumstances it isn’t. We don’t or can’t always quantify those circumstances, but we know they exist. Marriage is an example where there appears to be a lot of opportunity. Can we study a detailed matrix of characteristics that will lead us toward better outcomes based on empirical results? I suggest that the big dating sites have an opportunity to do this with the big data they could be collecting. Employers already do it to some extent.

We can do better and learn more, but until then, you have to ask…

What about the exceptions? Now you have to decide. Do you trust what the data is telling you? It’s a lot more tempting to trust statistics at face value when they appear to align with what you already believe. But are you really looking at it the right way? Does it really apply to you, in your unique circumstances?

Is it a big decision? How does the upside balance with the downside, and how does that impact how you think about the stats? Here is where the dreaded lizard brain of fear steps in. We look at it through the filter of what we are in and interpret the facts accordingly, or by finding another’s interpretation that resonates through us, in some cases by stimulating a fear we already have. Fear is so powerful. It can even make us interpret unmitigated facts in a misleading way.

Sometimes you have to trust yourself. Nobody ever got anywhere important through only listening to others, and that includes the stats, the so called experts, the masses, and the common sense. That stuff is useful up to a point, but somewhere along the journey you have to pave your own way, lest you become a different kind of statistic: the person who is eminently forgettable (ironic oxymoron), not happy or satisfied.

Against All Odds

Invariably someone comes along who defies what others believe. The journey that brought them there can later be quantified. We just need the right lens and some effort and skill to be able to see it. It’s much easier, however, to divine it as mysterious or destiny. We look on from the outside with wonder, not always recognizing there is a quantifiable method to the madness. We tranquilize ourselves with belief that the person was lucky, or blessed.

Few achieve the big goal, or true happiness from solely following others, or common sense. Each of those success stories has a foundation of paving one’s own way.

So much of the past five years of this blog has been about the willingness to make a leap of faith. Not in some external force, but in yourself. As I continue to wrap things up and finish off all of the work that has been started, I still find I am frustrated and even hurt by how little progress has been made. I marvel at those who do it better than me, and hurt for those who continue to find excuses to wallow in the status quo. That’s not what life is about. But then, who am I to say? I’m just a guy with a camera and a blog.

Do not put your faith in what statistics say until you have carefully considered what they do not say. ~William W. Watt


(*) – I can substantiate every claim and example used here, along with my rebuttals, if necessary (just ask). I chose not to burden the reader with too many links and wild good chases in the interest of focusing on the heart of the message.


Hidden in Front of Your Face

SLSubliminalThere are hidden messages everywhere, in everything. It’s the extra stuff you don’t always perceive, but can color or change the meaning of what you do perceive in profound ways. They’re always there. Very easy to breeze through and not concern yourself with most of the time. It’s also sometimes easy to invent your own messages and takeaways, based on what you’re in.

Sometimes, once you become aware of something that wasn’t apparent, you are shocked that you didn’t perceive it before, which paints perceptions on our canvass of trust. After a time you usually realize it was right in front of your face.

In communication, body language, tone, reading between the lines of word choice, and knowing the full context are each important, if often difficult to fully attain. You must be aware and look for it, making do with what you have. Far more importantly, you must accept it for what it is, and not invent an interpretation driven by your own narrative.

Open your eyes, ears, heart…and see. Sonja, I love you.

6 Intangibles of Leadership


There’s been much written about it. We know when we sense it in others because we are willing to listen and follow genuinely, as if it’s in our best interest, not just because we’re supposed to or because we’re riding on the coat tails of some opportunistic agenda. Things like trust are vital, but what are the other mystery qualities that produce a characterization of genuine leadership?

In no particular order…

  1. Grit – Passionate perseverance over the long haul. Toughness and dedication.
  2. Self-Awareness – We all have our blind spots, those things that we have no idea exist that can trip us up. Leaders have fewer, or they seem less significant.
  3. Resourcefulness – Learning agility. The ability and tenacity (see #1) to figure it out.
  4. Self Sacrificing Love – Possibly the core of leadership. Truly acting in a manner consistent with and showing care for those around you. The willingness to take less when it counts so others can have more.
  5. Manages Discomfort – The emotional awareness to assess causes of discomfort and translate it into appropriate actions.
  6. Creates a Sense of Meaning in Others – People will gravitate toward those who provide clarity about the what, how, and all important why. They will be more compelled by someone who clarifies their own why. Call it the Big Why – that top box on the list of things that drive you.

For the most part these characteristics can’t be manufactured. You can fake some of them for a while, but eventually the truth shines through. They are part of the makeup of who you are. It’s possible to over time learn to amplify and leverage these characteristics in oneself, though it’s extremely difficult to navigate without help. Those capable of providing this type of profound wisdom need to believe in you enough (see #6) to invest that capital. You still have to figure a lot of it out yourself along the way.



Being delusional or referring to one’s delusions generally is part of a negative assessment, or puts things into a negative context. “Delusions of grandeur” is one manifestation of a negative characterization.

But it can be a good thing if you believe it enough, for long enough. “Delusions of grandeur” is another way of saying a person has confidence. Confidence, within reason, is generally helpful. What about delusions of a better life, career, relationship?

Sure, there are extremes we wouldn’t want to go to, and it’s probably not wise to get too disconnected from reality for too long, but give delusion a chance and it can help take you to new heights. Believe it can happen. That and love are the antidotes to the fear.

Blind Spot


Aside from our other senses, we are temporarily blind to the half of the world located behind our head at any given moment. Some call that our blind spot. However, it’s not completely blind because we’re aware of the fact that we aren’t seeing it, not to mention the fact that the blindness is usually pretty easy to remedy when we need to, though it can be dangerous if we’re not paying attention.

Contrast that with our actual blind spot. Ironically the very place where the eye connects to the brain (via the optic nerve) is an area on our retina where we do not see – the blind spot. We do not notice it, and are thus unaware of it, because our brain fills the gap by extrapolating the likely content from the surroundings. We make it up. Fortunately this defect in our vision is small enough that it rarely causes a problem.

Combine those two characteristics and there would be significant issues. Imagine large areas of your vision that appear to be functioning fine, but are in fact being made up by your brain. We would call that being delusional (or one of a few other maladies).

Yet we are, in fact, delusional to some extent. We roll through life with our programming while being largely unaware that we’re thinking and acting according to it rather than objectively processing all the input we receive. These blind spots in our awareness – things we haven’t been programmed to be sensitive to – are all around waiting to trip us up. Most of the time the stumbles are minor, however, on occasion we can go pretty far astray and not be aware of it. We can hit the wall and crash, or we can do more subtle damage that we don’t see for a while, or we get what appears to us as having been randomly blindsided.

There is no solution to this in the moment. No easy shortcut to improve your odds beyond simply acquiring more wisdom as you experience more of life. You must start by accepting that what you see and believe is not an objective reality. It is simply what your brain has selectively chosen to make you conscious of. The best you can do is educate yourself and work at being informed and aware. Work at empathy by forcing yourself to be sensitive to others. Prepare within reason for mishaps so you can recover. There is a discipline to managing the risk, but in the end it’s impossible to eliminate it all. Being prepared includes the perspective of knowing we can’t be completely prepared. We must still be willing to act. To risk that we may be stepping into something that isn’t as it appears. Once we recognize how often this actually happens in our lives it could help us reconcile the fear we have when we do see the potential pitfalls. The risks our limbic system chooses to put in front of us are often as overblown as the risks we don’t see that are glossed over. Even the seemingly sure things had them. We just weren’t aware of it.

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