Quick Tip: Microsoft Word: Keyboard Movement and Selection

Keyboard shortcuts are a well-known way to reduce the amount of times you move your hand from your keyboard to your mouse and vice-versa when you’re editing your document. However, there are ways to navigate your document and even select text using just your keyboard as well. I’ll show you in this quick tip how to reduce the number of times you reach for your mouse when you want to select text or move around your document.

See more quick tips here: Quick Tips for Microsoft Office Applications.

Book Review-The Signal and the Noise: Why So Many Predictions Fail-but Some Don’t (Predictions)

People make predictions all the time. They predict that their team will win the Super Bowl, or they’ll win the lottery. These predictions are based on little more than hope. The Signal and the Noise: Why So Many Predictions Fail- but Some Don’t seeks to set us on the right path to understanding what we can learn from data, what we can infer from data, and what we can’t. By looking at the power and weaknesses of statistics, including both using the wrong model and supplying bad data, we can see how statistics has the power to improve our lives through productive forecasts and predictions.

In this part of the two-part review, we’ll look at predictions.

Forecasts and Predictions

Sometimes in our rush to be amazed at something, we simplify the questions we ask. We fail to recognize that our brain has simplified the thing that we’re trying to sort out (see Thinking, Fast and Slow for more on substitution). In the case of looking into the future, what we really want is prediction, and what statistics gives us most frequently is a forecast. Forecasts necessarily have a certain amount of error and involve statistical relationships. Forecasts become predictions when they become specific and precise.

Each day when we look at the weather, what we want is a soothsayer to predict what the weather will be like. However, what they offer us is a forecast based on models that result in a chance of rain somewhere between zero and 100%. We look at economists and seek the answer about whether we’ll make more money next year – or not. We want to know whether a risky investment will be worth it. However, economists and meteorologists are subject to the same rules as any other statistician.

While it’s true that statistics can predict – as long as we’re using this in a general sense of the word – events that are to happen in the future, there must always be some level of uncertainty as to whether the event will happen – or not. Predictions are just an attempt to refine forecasts into specific, tangible probable outcomes. Sometimes that process is successful but often it is not.

Falsifiable by Prediction

Karl Popper suggested that every forecast should be falsifiable via prediction. To test a model, you needed to be able to make some sort of a prediction with it that then could be proven false. In this way, you could create a test to ensure that your model was accurate and useful. A model that doesn’t forecast appropriately and that you can’t make a prediction from doesn’t do much good.

Everything Regresses to the Mean

One thing about statistics is that it can tell you with relative authority things you want to know with less precision than is useful. Statisticians can forecast the economy but not predict whether you will get a raise or not. The Black Swan artfully points out the challenges of statistics and modeling when the sampling size is insufficient. Until you’ve seen a black swan, you’ve not sampled enough to make the statistical models work. Until you’ve sampled enough, the noise will dramatically pull your results askew.

With large sample sizes, everything regresses to the mean. We no longer see the outlier, even as something that is distinct and that does happen, rather it gets lost in the law of averages. Tragic events like 9/11 are never forecast using the wrong model. They’re not perceived as possible if they’re averaged into the data. It’s like the proverbial statistician drowning in a river that is, on average, only 3 feet deep – all the depth of the data was averaged out.

Right Model, Right Results

Perhaps the most difficult challenge when working with data is not the data collection process. Collecting data is tedious and needs to be done with meticulous attention to detail; however, it’s not necessarily imaginative, creative, or insightful. It’s the work that must be done to get to the magic moment when the right model is uncovered for working with data. Though statisticians have ways of evaluating different models for their ability to predict the data, they must see some inherent signal in the noise.

For a long time, we couldn’t find planets outside of our solar system. One day, someone identified a detection model – that is, they discovered a theory for the strange oscillations in the light frequency from distant stars. The theory proposed that super-massive planets in close orbit were causing the star to move. This created a Doppler effect with the light from the star causing what we perceived as light frequency oscillations. Consensus coalesced, and the scientific community agreed that this was indeed what was happening. We had found the first extra-solar planet. Almost immediately, we found nearly a dozen more.

These super-massive planets were hiding in the data we already had. We had already captured and recorded the data to indicate the presence of other planets, but we didn’t have a model to process the data that we had to allow us to understand it.

There were plenty of ideas, thoughts, theories, and models which were tried to explain the light variations, but it wasn’t until the consideration of a super-massive planet that we settled on a model that was right.

The Failure of Predictions

We got lucky finding extra-solar planets. The right idea at the right time. It was a good fit model. It wasn’t a specific prediction. With predictions, our luck is very, very poor. The old joke goes, “Economists have predicted nine of the last six recessions.” They predicted a recession where none happened. Earthquakes and other disastrous cataclysmic events are predicted with startling frequency. It seems that everyone has some prediction of something. Sometimes the predictions are harmless enough, like whose team will win the super bowl. Sometimes the consequences are much direr.

Disease

When you think in systems, delays are a very bad thing. Delays make it harder for the system to react to a change in circumstances. In the case of the SR-71 Blackbird, the delays in a mechanical system made engine unstarts a regular occurrence. Reduce the delay with electronic controls and the unstart problem is dramatically reduced. (See The Complete Book of the SR-71 Blackbird for more.) In the creation of vaccines, the delay is great. To scale up production and get enough doses for the country, it takes six months.

What makes the vaccination “game” worse is that vaccines are designed to target specific viral strains. If the virus mutates, the hard work of creating the vaccine may be wasted, as it may become ineffective at protecting against the new strain. Each year, the vaccine makers attempt to predict which variations of influenza will be the most challenging. They start cooking up batches of vaccines to combat the most virulent.

What happens, however, when you get noise in the identification of the influenza that will be the most impactful? From 1918 to 1920, swine flu afflicted roughly one-third of humanity and killed over 50 million. So when there was an apparent outbreak of a strain of it at Fort Dix, who can blame President Ford for encouraging the vaccine industry to create a vaccine for it and encouraging every American to do their part in preventing the spread of the disease by getting vaccinated – and hopefully increasing the herd immunity?

It turns out it was all a bad call. Issues with the vaccine caused Guillain–Barré disease in some. The virus strain turned out to not be that virulent. The noise at Fort Dix that had produced the scare wasn’t a result of the virus’s potential but was instead a result of environmental and cultural factors that allowed the disease to spread at Fort Dix but weren’t generalizable to the population.

SIR

A classic statistical way of modeling diseases is the SIR model, which is an acronym for susceptible, infected, and recovered. The assumption is made that everyone who is recovered is not susceptible again, and everyone has an equal level of susceptibility. This simplified model works relatively OK for measles, but fails to account for natural variations in susceptibility in humans. More importantly, the model fails to account for the connections that we have with each other. It fails to account for how we interact.

Another classic example of disease was cholera in London, but it didn’t seem to have any connections. There was no discernable pattern – that is, until John Snow discovered a connection in the Broad Street well and removed the pump handle. The disease slowly dissipated, as Snow had correctly identified the root cause. However, his job wasn’t easy, because people who were far away from the pump were getting sick. Those who weren’t close to the Broad Street pump had hidden connections. Sometimes they lived near the pump in the past and still used it for their main water source; in other cases, they had relatives close by. The problem with forecasting diseases is the hidden patterns that make it hard to see the root cause. To correctly forecast, we need to find and then use a correct model.

An Inconvenient Truth

It’s an inconvenient truth that, in the decade when An Inconvenient Truth was released, there was no substantial change in temperatures across the planet – in truth, there was an infinitesimal reduction in temperature from 2001 to 2011. However, Gore wasn’t the first to claim that there were problems. In 1968, Paul and Anne Ehrlich wrote The Population Bomb. It was 1974 when Donella Meadows (who also wrote Thinking in Systems), Jorgen Randers, and Dennis Meadows first published Limits to Growth. (It’s still on my reading list.) These books both sought to predict our future – one with which the authors were most concerned. Of course, population is increasing, but it’s far from a bomb, and we’ve not yet reached the feared limits to growth.

These predictions missed what Everett Rogers discovered when working with innovations. In
Diffusion of Innovations
, he talks about the breakdown of society created by the introduction of steel axe heads in aboriginal tribes in Australia. They missed the counter-balancing forces that cause us to avoid catastrophe. However, presenting a balanced and well-reasoned point of view isn’t sensational, and therefore doesn’t sell books, nor does it make TV exciting. The McLaughlin Group pundits’ forecasts about political elections are not at all well-reasoned, balanced, or even accurate – but that doesn’t stop people from tuning into what amounts to be a circus performance every week.

So the real inconvenient truth is that our predictions fail. That we overestimate, and we ignore competing forces that attempt to bring a system into balance. In fairness to Gore, the global temperature on a much longer trend seems to be climbing at 1.5 degrees centigrade per year. It’s just that there’s so much noise in the signal of temperatures that it’s hard to see – even over the course of a decade. We need to be concerned, but the sky isn’t falling.

Watching the Weather

If you want to find a prediction that’s guaranteed to be wrong, it’s got to be the weather. The oft quoted remark “What job can you be wrong most of the time and still keep your job?” refers to meteorologists. However, in truth, forecasts are substantially better than they were even a decade ago. They’ve done a startlingly good job of eliminating the problems with the mathematical models that generate weather forecasts. Increases in processing power has made it more possible to create more accurate and more precise forecasts. And they’re still frequently wrong. A wise weatherman goes outside and looks at the sky before going on air to share their predictions, because they know that the computer models can be wrong.

The problem isn’t the model. The problem isn’t our ability to model what will happen with the forces of nature. The problem is in our ability to measure precisely the inputs for the model and the inherent dynamic instability of the systems. It was Lorenz that first started the conversation about the butterfly effect. That is, a butterfly in Brazil can set off a tornado in Texas. That’s a mighty powerful butterfly – or the result of an inherently unstable and dynamic system. A very small change in input has a very large change in output.

As a quick aside, this is where the hash algorithms have their roots. We use hash algorithms to ensure that messages aren’t tampered with. They work by small changes in input resulting in large changes in the output.

The problem with predicting the weather, then, isn’t that we don’t know how to process the signal and arrive at the desired outcome. The problem is that we can’t get a precise enough signal to eliminate all the noise.

Overfitting and Underfitting

In attempts to find the models that perfectly describe the data, we run the risk of two sides of the same coin. On the one hand, we can overfit the data and try to account for every variation in the dataset. Or we can look for mathematical purity and simplicity and ignore the outliers – this is “underfitting.”

“Overfitting” mistakes noise for signal. An attempt is made to account for the randomness of noise inside the signal we’re trying to process. The result is that our ultimate predictions try to copy the same randomness that we saw in our sample data. In other words, we’ve mistaken the noise for the signal and could not eliminate it.

Underfitting, on the opposite side of the coin, is the inability to distinguish the signal in the noise. That is, we ignore data that is real signal, because it looks like noise. In a quest for mathematical simplicity, we ignore data that is inconvenient.

Brené Brown speaks of her scientific approach to shame and vulnerability as grounded theory and the need to fit every single piece of data into the framework. (See The Gifts of Imperfection for more.) When I first read this, it stood in stark contrast to what I saw with scientists ignoring data that didn’t fit their model. It seems like too many scientists are willing to ignore the outliers, because their theory doesn’t explain it. In other words, most scientists, in my experience, tend to underfit the data. They are willing to allow data to slip through their fingers for the elegance of a simpler model. Brown and those who follow the grounded theory approach may be making the opposite error in overfitting their data.

Statistical Models

In the next part of this review, we’ll talk about models and statistics.

Article: The Actors in Training Development: Instructors

If a tree falls in the woods and no one hears it, did it really make a sound? This question is at the heart of the need for people who help training reach students. It’s only by helping students through the course that it has had any impact or value. There’s no good in a course that sits on the shelves, never to be used. Distribution staff, of which instructors are a part, are the bridge from the completed training to the impactful implementation.

Part of the TrainingIndustry.com series, the Actors in Training Development. Read more…

Quick Tip: Microsoft Word: Quick Parts

If you’re working in a collaborative space, such as a SharePoint library app, you’ll often use certain fields or metadata to contain important information. Microsoft Word can capture this information, and even change it. In this quick tip, I’ll show you how you can use quick parts to update some of the document’s properties, which can then be populated to a collaborative space.

See more quick tips here: Quick Tips for Microsoft Office Applications.

Book Review-A Spy’s Guide to Thinking

I never wanted to be a spy. Astronaut, yes. Spy, no. I’m not sure why. Spies are glamorized in the movies (unless it is Spies Like Us), but it wasn’t my thing. When the short book A Spy’s Guide to Thinking came across my path, I thought it was worth looking into. It’s a short book, a quick read, and more of an interesting aside than it is hard-hitting details about how spies think. Still, there are some interesting things from the book to consider.

Side of Paranoia

In my head, being a spy means being at least a little bit paranoid. You’ve got to be on guard for people discovering who you really are and your mission. While this wasn’t an acknowledged component, the book centered around one encounter on a subway – which had nothing to do with being a spy, but could provide insight to how a spy thinks. Generally, the word would be “paranoid.”

The entire encounter kept asking the question about whether the other person knew he was a spy was. Great. He’d rule out that the other person was a spy catcher and then retest that observation over and over again. I suppose that is what makes a good spy. They’re paranoid.

Observe, Orient, Decision, Action

Throughout the book, our spy did a loop: observe (data), orient (analysis), decision, and finally, action. The origin of this loop is John Boyd. He talked about how the most successful pilots can run the loop quicker than their peers. It’s not smarter that matters, it’s quicker through the loops.

Whether you use the word “observe” or “data,” “orient” or “analysis,” the result is the same. You observe the situation, assess or orient to the data you have, and then make a decision and act upon it. The loop – the slightly paranoid loop – was running frighteningly fast.

Zero, Positive, Negative

There are only three types of games we can play. Those that are net positive, those that are net negative, and those that are zero-sum. When we play a net positive game, more is created – it may not be evenly distributed, but more is created through the game. In zero-sum games, one person may win, but the other person loses by the same amount. In net negative games, someone always loses something.

It’s interesting to view life through the lens of a spy, always wondering who knows what. A Spy’s Guide to Thinking really does get you thinking – about whether you could be a spy or not.

Quick Tip: Microsoft Word: Record a Macro

Sometimes you need the same piece of text used multiple times over tons of different documents. It could be a short piece of text, like a slogan or trademark, or a longer paragraph. In Word, you can create, or record, a macro, as I’ll show you in this quick tip, and use that macro in all sorts of documents, removing the need to copy and paste from one document to the next.

See more quick tips here: Quick Tips for Microsoft Office Applications.

Book Review-The Hidden Brain: How Our Unconscious Minds Elect Presidents, Control Markets, Wage Wars, and Save Our Lives

It was years ago. I was working on a billing system. It was designed to bill based on the amount of time used. It billed in six second increments – 10ths of a minute. It was late, and I noticed something odd. There was a bit of math, but it didn’t add up – or rather it added up a bit too much. It’s typical to have to adjust mathematical errors in code. If someone started and ended in the same tick, you charge them for not zero ticks, as end minus start would imply if they’re the same. Instead, you add one to the math equation to say that there was non-zero utilization. However, the code was written in a way that added this adjustment in twice. As a result, the billing was always two tenths of a minute at minimum.

The problem wasn’t discovering the error, it was the comment that prohibited developers from fixing the bug and an instruction to speak with the manager if there were questions. The double addition could have been an accidental mistake. I remember the math being broken into two places and the correction made in both places. However, the note made it clear that the bug was a known bug. One that was charging people for an extra six seconds for every call. It wasn’t much per transaction. Maybe a few pennies. However, as the story line of Office Space can attest, those pennies add up.

This subtle math “error” is the kind of thing that we encounter all the time, and it’s the subject of The Hidden Brain: How Our Unconscious Minds Elect Presidents, Control Markets, Wage Wars, and Save Our Lives. It’s not about the radical changes in direction that are placed outside our conscious view, but rather the subtle tilting of the scales by placing a finger or two on the final outcome. It’s fundamentally about System 1 lying to System 2, to use Khaneman’s language from Thinking: Fast, and Slow.

Lies, Damn Lies, and the Brain

We think that we’re in control. We’re wrong. Haidt in The Happiness Hypothesis describes the Elephant-Rider-Path model (which is also covered in Switch). It clearly illustrates that a big elephant (or emotions, System 1, Lizard-brain, or whatever you want to call it) is in charge. The rider gets the illusion of being in control so long as the elephant allows it. Incognito demonstrates through visual illusions and thoughtful stories how much we fool ourselves. It’s spooky how much we believe we understand reality and how much our mind plays tricks on us.

Paul Ekman would undoubtedly, at the very least, have concern about saying that our hidden brain (again, System 1, or whatever you want to call it) lies to our rational brain. In Telling Lies, he clarifies that the liar needs to know that he’s lying. In fact, the stress that lying produces because people know it’s not true is how the polygraph works. (Ekman is perhaps best known for his work in detecting lies or, more accurately, emotions through monitoring involuntary facial muscle movement. You can learn more about his life in Nonverbal Messages.) However, our hidden brain keeps taking shortcuts, tilting the scales, and not letting us in that it’s doing it. It’s lying to us – even if we aren’t conscious of it.

Rules of Thumb

In general, heuristics are great. Heuristics are simplifications. They’re “rules of thumb” that you can use to make complicated things simple enough to be understood. Our brains are great at creating them. It’s hardwired into us to find associations and correlations to see if we can simplify the world. If there were no heuristics, there would be no comedy, as comedy and jokes use heuristics to create the wrong impression. (See Inside Jokes for more on how comedy uses heuristics.) The problem isn’t in using heuristics; they’re a great tool to allow us to comprehend the world around us. The problem is when we use a heuristic that doesn’t apply, or the heuristic hides a bias.

I’m biased to people with straight hair compared to curly– at least, that’s what the Implicit Association Test says. (It’s available at www.implicit.harvard.edu if you want to take it for a spin.) How strong is the bias? I don’t know. The test doesn’t say. It simply says a bias exists. If I were to be interviewing two people for a job, I’d have an ever so small bias to the person with straight hair. I’d be applying a heuristic bias that I like straight-haired people more – and I wouldn’t know I was doing it.

Pervasive Biases

I’m not alone in being biased. You are too. Perhaps not in the same ways, but biased. Consider the work of Dr. Clark who gave white children two different dolls – one of a light skin and one of darker skin – and the children called the dark-skinned doll “dirty” and “bad.” It seems like a clear-cut case of racism. That is, until you realize that the black children he tested next had the same general response. It wasn’t racism per se. It was a generalized bias that permeated culture. It’s wrong, I agree. However, to call it racism would be calling black children racist against their own race. (See The Cult of Personality Testing for more on these tests.)

On a much lighter note, waitresses who subtly mimicked their customers tended to get larger tips – 140% larger tips. We have a bias towards people that “get us.” We want to be understood, and those that understand us are more valuable to us – both in general and, apparently, monetarily as well. The subtle act of mimicry is interpreted by the hidden brain as understanding and is valued – even if we aren’t informed that the bias is happening.

Competitive or Complementary

Gottman predicted divorce rates at 91% accuracy by watching a short fight. (See The Science of Trust for more.) This was impressive to say the least. He identified factors that he believed signaled intimacy longevity and those that drove couples away from one another. (See Intimacy Anorexia and Trust=>Vulnerability=>Intimacy for more on intimacy.) However, Abraham Tesser found something else that is different and intriguing. Tesser found that people find joy in others’ success – unless their success was in the same area as they were seeking success. In those areas, if their partner or close friend was successful, they became jealous. Couples that who weren’t emotionally close allowed success in a common field to become the wedge that drove them apart. However, emotionally close couples instinctively found complementary ways of dividing up their tasks.

In essence, they found a way to convert competition into cooperation. Richard Hackman is clear about how to build collaborative teams in Collaborative Intelligence. He explains that systems that create a competitive spirit within the team are corrosive to collaboration. It seems like emotionally close couples sense this and unconsciously move into complementary positions, where they could stay a part of a well-functioning team. Instead of a wedge, it becomes a binding that makes them more dependent upon one another.

Talk is Cheap

William Wundt started a branch of psychology that relied on introspection. The behaviorists, led by B.F. Skinner, didn’t like it, because it couldn’t be objectively measured. Even Wundt’s successor William James struggled with introspection not because it couldn’t be objectively measured – that is, it couldn’t be observed. James’ struggle was that one could not hope to be without bias for thoughts and feelings occurring inside themselves.

This is the basis of the hidden brain. Much of what happens in our brains isn’t accessible to our consciousness. Even if it was, it would be distorted to protect our ego. (See Change or Die for more on The Ego and Its Defenses.) We can’t directly access our hidden brain through reflection or introspection. We’ve got to get to it another way.

Recently, we’ve begun to discover planets in solar systems other than our own. We’re discovering them not because we can see them. We can only see the effect that they’re having on their stars. Super massive planets in close orbit to their stars cause the star to wobble. This wobble is discovered in a slight shifting of the light spectrum from the star in a repeatable pattern – the Doppler effect on a stellar scale. We can find planets, but only by looking for them indirectly.

We find our hidden beliefs by looking at our self-talk and using tools like cognitive behavioral therapy (CBT) to change that self-talk. We don’t change the hidden brain directly, but rather we train the rider how to better control and regulate the elephant in certain conditions. In general, CBT has been found to be effective. (See The Heart and Soul of Change and Science and Pseudoscience in Clinical Psychology for more on CBT and efficacy.)

Kids Say the Darndest Things

One of Art Linkletter’s gifts to culture is a segment called “Kids Say the Darndest Things.” That is, they respond in a “cute” way. Sometimes they didn’t understand the question as an adult would. Sometimes they answered in an honest way that an adult never would. Young children and adults are both guided by the hidden brain, and both have the same biases. The difference is that children will say what their hidden brain thinks where adults have learned to restrain their responses. Responses that in children are “cute” would be appalling from an adult. Often the answers are true – but uncomfortable.

There are plenty of examples of celebrities becoming overwhelmed and saying inappropriate things. There’s even a line of commercials from Snickers talking about people who need a snack. They’ve become other people due to their hunger. Researchers have found that much of this isn’t hunger but low blood sugar. They’ve we able to reduce apparent adult prejudice by simply giving them more sugar.

Carried by Currents

Instinctively, we wait. We wait for some sort of consensus to form. The fire alarm may be ringing. The air raid or tornado siren may be blaring. The overhead announcement may be confirming that we need to evacuate the building. Rather than moving immediately, we’ll instinctively pause, survey the group, and attempt to determine what the consensus is before acting. The larger the group, the longer the delay to reach some semblance of consensus – and the more likely we are to have a problem.

We all think that we’re independently protecting our own self-interests when, in reality, we’re waiting on the herd to move so we can keep from being singled out. Even in non-emergency situations, we by default will go with the flow. We’ll assume that our decisions are ours alone; but if you’re always going with the group, how can you be sure that you’re really making your own decisions? If you’re always swimming with the current, you’ll believe that you’re a better swimmer than you are.

Good Samaritans

The good Samaritan story is relatively well known. A stranger, a Samaritan, saves a man on the road by taking him to an inn and agreeing to pay the fee for keeping them there. (I spoke of this in Book Revisited-Theory U, Organizational Traps, and The Dalai Lama’s Big Book of Happiness.) The funny thing is that the research shows you’re better off having one Samaritan come by rather than two. It turns out people are more willing to help out when they’re the only one. Whether it’s picking up pencils or something more serious, the more people there are, the lower the expectation of individual intervention.

Similarly, giving to support a single person is easy. Giving to a cause that would save dozens is harder. Somehow our compassion is easily overwhelmed by a dozen when helping one seems easy. It’s almost as if there’s an internal governor that wants to make sure that our efforts are enough to save a “reasonable” portion of the total. If we can’t get to the belief that we’ll make a substantial difference, we’ll do nothing.

Psycho Suicide Bombers

We assume that anyone that is willing to be a suicide bomber must be mentally unstable. How else could we explain their strange and unthinkable behavior? The answer is that they’re living in an alternative universe of their making. They interact with people who focus them in a direction and they’re teleported along a path until their beliefs and behaviors seem unthinkable to the general public.

It doesn’t take religion to perform this conversion. It doesn’t take mental illness. All it takes to create a suicide warrior is to separate them from the rest of reality and slowly move them to a new reality. Terrorists aren’t recruited by terrorist groups. They volunteer because their ideas have become so distorted that the terrorist group seems like the best option.

Groups of people get together and insulate themselves from the outside world while creating a tight mesh of their reality. The band of brothers is formed through shared experiences. One man marries the sister of his good friend. This happens over and over again until the network of people mostly interacts with itself and not with the outside world – the “real” world. Progressively, their attitudes adjust in ways that don’t make sense to most of us.

In the case of suicide bombers, they come to believe that they’re part of something, that their life will have meaning, that they’ll make a difference. While the terrorists rarely come from humiliation itself, they often empathize with persecuted groups and want to make their humiliation and pain go away. They see their role as minimizing or eliminating those inhumanities.

Don’t Drink the Grape Kool-Aid

Certainly, cults show the same tunnel behavior and cut off ties to the outside world. One tragic example is The People’s Temple religious group, whose leader, Jim Jones, warped reality such that parents killed their children and themselves with cyanide-laced grape-flavored Kool Aid, because they believed that they were going to be captured and tortured. Their struggle was over.

They’re not alone. The Heaven’s Gate cult killed themselves March 25th, 1997 believing that they would be picked up by an alien space ship following the Hale-Bopp comet. Most of us believe that this is an odd way to get aboard a space ship, but the shaping of their belief system was so complete that 39 members of the cult followed orders and killed themselves.

Assault on Ourselves

Too often, our hidden brain ignores the statistics, the logic, and the rational in its pursuit of simplicity. Too often, we do things that statistically make no sense. We’ll drive instead of fly, because we perceive it to be safer when it, in actuality, is much less safe. We purchase guns to defend ourselves when the statistics say that our risk of death is much higher when we have guns in the house. It turns out suicide is a much bigger problem than murder – but our hidden brains are assuaged.

We continue to march on, following the orders of our hidden brain. Perhaps if we learn more about The Hidden Brain, we’ll be able to make better decisions both morally and logically.

How 3D Printing is Changing My World

At the risk of being redundant, 3D printing is transforming the world. Note that I expressed this in the present tense. It is changing the world today – not tomorrow, and not some day in the future, today. It’s changing how people solve problems in what may seem like small ways – but in ways that are profound. Coupled with free modeling software like Blender, I want to tell you a story of how, in literally less than one hour and having purchased no equipment, I got exactly what I needed.

Unique Problems

Even though in many ways we all have the same things, we still have custom needs. Maybe 80% of our needs are the same, and the industrial revolution did a great job of solving those needs. (In a supermarket, this amounts to about 150 items, according to The Organized Mind.) However, there are still many unmet needs that take a large degree of time and effort to address. Around here, I’ve had plenty of these “needs” that I’ve solved. From custom stair noses to airlock doggy doors to the solar powered mini-barn, I’ve created solutions by hand to more than a few unique problems. I’ve gotten used to these solutions being crazy and expensive. However, 3D printing is changing that.

I recently removed some fluorescent lights from my video studio. Some of the challenge was aesthetic, but mostly I wanted to address challenges with reliability as the lights were starting to fail. I opted for drop-lighting like you’d see outside. That meant converting the power supplies for the fluorescent lights to outlets that I could plug the strings of light into. The problem was that the drywall around these boxes weren’t finished well, because the drywaller knew they would be hidden behind lights – or, at least, they were.

I can certainly pay to have the drywall finished right up to the boxes, but that’s a labor-intensive process that becomes expensive. A larger than normal duplex plate would more than cover the gap, but finding what I needed proved to be an impossible task. So I decided to do something radical: print them.

Into the Blender

I quickly went to the internet, found some duplex wall covers to get the basic shape of the outlets and ratios. I dropped that into Adobe Illustrator. A few minutes later, with the help of image trace, I had a basic shape. To that I added a circle at 143mm in diameter. The printer I had access to had a maximum Y dimension of 145mm, so I sized the cover to 143mm around. I had what I needed in a vector-based image file in black and white for the part I needed.

It took a minute or two to merge paths and output a SVG (Scalable Vector Graphics) file that I could import into the free Blender 3D modeling software. Unlike Illustrator, I had never used Blender. I watched a few videos at 2x speed and did a few searches and discovered the ability to extrude my 2D graphics. This would add depth. I settled on 1/8″ because it would be thick enough to stand up to long-term placement.

A few more minutes later, I had a 3D model that I could share with my public library.

Public Printer

I live in Carmel, IN and we have an amazing library. One of their recent additions is a digital media lab that, among other things, has two 3D printers. They charge a usage fee of $3-7 per part you print based on how much 3D filament you use. There wasn’t a way to email a part, so I drove the 3 miles to the lab and handed the librarian my model and answered a few questions.

Total time invested from the point I decided to create the parts myself to dropping them off at the library – less than one hour. I easily would have spent this trying to locate the exact part I wanted (assuming I could find it) and would have spent many more hours trying to adapt whatever I found to match what I need.

Sure, I didn’t have the part right that second, but a few days later – and one revision due to an error I made – and I’ve got exactly what I need. I would have waited for a few days to get something had I ordered it from out of town – so ultimately I got my solution in about the same time.

What’s the Change?

So what’s the point? Well, we’re moving to a time when anyone who can design something in 3D can have it made flawlessly by computers. We can already buy (or download for free) stock photography and print our own artwork for our walls. Print a picture on canvas and apply a brush stroke and who will be able to tell that it wasn’t painted?

As I was walking through a gift store recently, I realized that most of their wall hangings were either engraved sayings – which were public domain – or they were words over stock photography. What happens when it’s cheaper to have a piece of artwork custom printed for you and delivered to your door than it is to buy artwork from a gallery?

In the 3D space, why keep small parts? If you can keep a 3D model of the part, and if the printing material (PLA or ABS) is strong enough, why not just keep a printer and the models around?

What’s the Difference?

I had the pleasure of working for a rapid prototyping company in the mid-1990s. We had SLA (Stereolithography) , SLS (Selective laser sintering), and a few more obscure prototyping systems available to us. The idea of 3D printing of a part isn’t new. What’s new are two things. First, the price point for a printer is $1,000 – or less – for something that used to cost hundreds of thousands of dollars. $1,000 isn’t a consumer purchase, but the smaller $200 units are. Oh, and they’re faster than the old machines, so you can get more throughput.

Second, the materials are more rigid. The materials that SLA and SLS used were notoriously fragile. PLA and particularly ABS plastic is sufficiently rigid to be the final product. With SLA and SLS, we were making casts of the prototypes to make copies, and then casting them into harder materials.

Having the materials that you can use directly, that can be produced more quickly, and at a price point that’s “consumable” – suddenly you have the door to mass customization shoved wide open.

Quick Tip: Microsoft Word: Turn on the Developer Tab

The Ribbon is a staple of Microsoft Word, allowing you to use a plethora of commands with the click of a mouse, from the widely-used Home tab to the Review and Mailings tabs. Every once in a while, there comes a time when you need to use a tool or do a task that isn’t at hand by default. I’ll show you how to turn on the Developer tab in this quick tip, so you have easy access to even more commands in Word.

See more quick tips here: Quick Tips for Microsoft Office Applications.

Book Review-Unthink: Rediscover Your Creative Genius

Somewhere deep in the recesses of our mind are the recesses from our grade school. Buried by decades of cruft, these memories and others call us back to the state that we had back then when we knew we were creative. It’s a time that we knew we were creative, before we got tied up with how others view us and before the need to be productive and rational. This is the place of Unthink: Rediscover Your Creative Genius.

Claude Baudelaire wrote once, “Genius is the capacity to retrieve childhood at will.” Perhaps that’s why it’s no wonder that Einstein considered his genius the result of remaining childlike into his adult life.

Information Processing

Children learn differently than adults. That’s the primary premise of The Adult Learner. It’s not just that adults have more complex mental models (see The Art of Explanation), adults fundamentally learn differently. The neurology of our brain has changed, and we’re not forming the number of new neural connections that we did as a child. However, more importantly, we’ve developed a usefulness filter for what we learn.

Somewhere along the line, we got exposed to so much information that a switch flipped, and we started filtering what we learned. (See The Information Diet and The Organized Mind for more on the information overload world we live in today.) The switch that flipped made us more discerning consumers of information. Instead of learning everything, we learned that there were things that we didn’t need to know. We didn’t need to know the number of atoms in a liter of gas at standard pressure. We’d look it up when we needed it – or, in today’s terms, we’d just google it.

So, quite literally, we filter everything coming into our brain for awareness – to fight information overload – and for retention to see if we need to reserve precious brain space for the information, or if we can look up the information again when we need it next. That’s different than what we did as children when everything was interesting.

I can remember playing with paper clips and rubber bands just to see how they work – well, in truth, just to be fiddling with something. It’s been a long time since those days. Now, it seems like everything that I’m working on has some productive or at least semi-productive reason for being.

Ambition

Too many people have books which are screaming to get out. Too many people want to be more than they are today. Edgar Lee Masters, a poet, laments, “Ambition called to me, but I dreaded the chances. Yet all the while I hungered for meaning in my life.” (See Start with Why and How Will You Measure Your Life? for more on finding purpose.) The problem with ambition, with the desire to be greater, is that, if you try, you’ll know for sure if you can make it – or not.

In How to Be Yourself, I shared the awareness that it’s easier to project a false image than to be real. Being real means that when you’re rejected you’re really rejected. Ambition is the same thing. You don’t have to face your ego if you don’t try. Try and fail, and there’s a reconciliation that must happen with the ego to figure out why you didn’t achieve your goals. But if you don’t try, there’s no hard conversations to have with yourself. (See Change or Die for more on your ego.)

Masters concludes, “To put meaning in one’s life may end in madness, but life without meaning is the torture of restlessness and vague desire – it is a boat longing for the sea and yet afraid.”

Corporate Creativity

There’s a crisis in boardrooms across the country. The crisis isn’t capital. The crisis isn’t communication. The crisis is creativity. Following the rules, being in fear of the next layoff has driven creativity out of the corporate culture, and it may be exactly the thing that organizations need to survive. (See Drivers for Conformity and Originality for more.)

IBM chief executives found that they believed the critical activities for the future included taking balanced risks, considering unheard-of ways, comfort with ambiguity, courage, and different assumptions. These skills are the heart of creativity, and they’re missing.

Creativity springs from safety, as Creative Confidence
compellingly explains. The rounds of cutbacks. The layoffs and restructurings in corporate America have left employees shell-shocked in their own form of post-traumatic stress disorder that has them walking from meeting to meeting like zombies awaiting the zombie apocalypse.

Creating Creativity

Beyond creating safety to try and fail, there are other tools that you can use to encourage creativity. If you’re willing to do the things that you least like to do – in service of important goals or responsibilities – you’ll put your brain on tilt and typically generate unique ideas.

Originals explains that it’s quantity that produces quality. That the best works of artists have come in the periods of their greatest productivity. We can get more creativity by creating more opportunities to produce – without pressing so hard that there is stress on the deadline.

Creativity comes from curiosity. It comes from “can I do that?”, “how did they do that?”, and “what’s making that happen?” If you can instill a sense of curiosity in yourself, you’ll find that you’ve recaptured a bit of your childhood and have opened the door to creativity.

Conviction

Standing strong against the winds of conformity requires strength. It’s a strength of character that’s rare. When confronted with someone who exhibits character, most people generate respect for that person – even when that person has diametrically opposing views. You can appreciate the conviction of someone’s beliefs whether you agree or not. In fact, this respect is the way that things used to be done.

Before the digital age, when we’re fascinated with the latest tweet about a ham sandwich, the latest Instagram picture of the ham sandwich, and the Facebook post about how you had a ham sandwich two years ago, we used to watch behaviors over a long time. We’d see how people acted when people weren’t watching and use this to judge their character. Now we can see people become popular because of one post. We don’t assume that people aren’t watching, because we know they always are.

We used to have to have conviction to develop a reputation. Today, it is all too easy to manipulate the news stream to capitalize on a meme, someone else’s post, or some passing fad. We don’t build respect that same way that we used to.

The people that we used to learn to respect had one thing on their heart. It was something that they cared deeply for and for which they were willing to toil and sacrifice for. No more.

Lines of Varying Lengths

It was Solomon Asch who was curious about conformity and why people would give up their perceptions for the perceptions of others. In an ingenious experiment, he filled a room with test subjects and collaborators. When the collaborators answered truthfully about the length of line that matched the length of line they were still seeing as a reference, the subjects answered truthfully. As he added collaborators that spoke the wrong answer, he found that his subjects would report the wrong answer like the others had given. This progressed from some of the time to over 75 percent conformity at least once with three collaborators or more answering incorrectly.

It wasn’t that the subjects couldn’t literally see the right answer. It was that they literally couldn’t see the right answer. That is, visually, they saw the same information as before, but the image in their mind’s eye was manipulated to match what the collaborators had said. (See Incognito for more about our mind’s eye.)

Closing in on Creativity

I have no way of knowing what is blocking your creativity. For me, I know there’s a part of it that’s the logical sequential thinking that was the start of my career as a developer. Allowing free thinking isn’t always easy for me. Being unproductive feels like a waste. However, sometimes I need to Unthink. Maybe you do too.