April 2019

Normalizing Dysfunction

Being in school was a bit of a rough time for me. I had a great group of core friends, but experienced a fair amount of bullying, especially in junior high. Even as I got into high school, and the bullying lessened, I never really felt comfortable in my skin, or around most of my peers. People were very clear about where you stood if you weren’t popular. But my discomfort wasn’t something I thought about much. After all, it was normal.

Then I got to college. I was lucky enough to go to a small liberal arts school, and there I discovered something so different. People who hadn’t been super popular in school, people who loved geeky things, people who had experienced bullying for themselves. They didn’t judge me or make comments based on what I wore or whether I raised my hand in class. And suddenly I realized that my high school experience wasn’t normal. And that something much better was possible. That I could feel good.

I think we’ve all had an experience like that. An experience of going through stress, and yet only when the stress is lifted, realizing just how much we were carrying. Of thinking our experience is normal, only to move into a new environment that shows us how off our perspective was.

"Ok, got my work for the day! Let's do it!"

One of my earlier jobs in government was Personnel Coordinator. This meant that I tracked all of the positions in my district and which offices they were assigned to. Every new hire, every resignation, every dismissal, and every move, I was the one who typed up the proper form and submitted it to the head office. I was also in the same office as district management, so was in a unique position to watch the outcomes of various decisions.

There were two different agencies run out of this office. And one agency in particular had a very distinct approach when they were dissatisfied with the performance of a specific office. Not only would they reassign the manager from that office, but they would reassign almost all of their managers at once – essentially shuffling the deck of managers until most were in a new location.

At first I didn’t give this strategy much thought. I was a low level admin, they were upper management, and I just did the paperwork. But after a while, it started to feel…weird.

There were so many deeply entrenched issues in the agency, staff morale was always an issue, resources were tight, and yet it seemed the main solution to so many problems was to reassign managers.

Now admittedly, I wasn’t privy to all the high level discussions to these decisions. But I was in a position to see the impact. Keep in mind, each move wasn’t just an adjustment for the managers. Each time this happened, all of the staff would be affected as well.

I also started to get to know some of the managers. One of them facilitated with me in a leadership program. She would talk about her connection with her staff, and the progress they were making in reaching program goals. She’d be so proud of what she was accomplishing. And then suddenly she would be moved. She’d start over, gain the staff’s trust, refocus the goals of the office. And then it would happen again.

I can see how something like this would get started. A manager is struggling, and a different one may seem to have a more appropriate skill set for that particular office. So you do a swap. And maybe the first few times you do it, it’s actually quite effective.

Until there’s a day, far down the line, where instead of providing support or training, or looking deeper at the underlying issues, or considering the impact on your workers, the standard in resolving any problem is to move managers. It’s become normal.

"Um, sure...I guess while we're shortstaffed I can help out a bit..."

I’m a fairly avid gamer, as any recurring readers know.. Recently, there’s been an increasing awareness of how toxic game studios can be, especially in how they are treating their employees. There’s been a number of articles written on just how much the workers are expected to bear, all in the name of being a good employee. Current and ex-employees are speaking out against the severe conditions in prominent companies such as Bioware and Rockstar. In some cases, these employees are working vast amounts of unpaid overtime only to face abrupt job loss when the studio folds.

I found the example of Bioware particularly interesting. This was a company that used to be my absolute favorite developer. I was so excited whenever they would release a game. And then, over time, cracks began to show.

What some of the reporting has revealed was that there was a particular game that was close to disaster. And the employees were able to pull a last minute miracle, and release something that was fairly successful.

Now, for most of us, we would see a close disaster as an opportunity to reevaluate. To be grateful for the workers that were able to pull out “magic”, but to understand that this is not a viable strategy. In reality? Nothing of the kind happened. Instead, management decided that if it could happen once, it could happen again. If you can push your staff to the limit and get a decent product, why not keep pushing?

Only the real world doesn’t work like that. You can’t make a strategy based on a one time occurrence. And it shows, as recent projects relying on this “magic” have been failures, experienced staff are fleeing for the hills, and new bright minds never dare walk in the door in the first place.

One of the most important aspects of leadership is the ability to learn from failure. And yet, in these companies, and so many others, leadership learns absolutely nothing. Time and again they rely on forcing workers into a crunch. And over time, it gets worse. People are pushed beyond reasonable bounds, beyond the point of breakdown. And yet inexplicably, it’s become normal.

"Just another Wednesday. *sigh*"

I want to be very clear here. I’ve been a manager, and I know how hard it is to stay on top of things. To see the forest for the trees. I know how easily we can all slip into seeing the unhealthy as normal.

But when you are in a position of leadership, you are absolutely still making a choice about how you treat your employees.

You are making a choice in the language you use. You are making a choice in accepting the culture, instead of fighting it. You are making a choice in telling your staff to pull up their bootstraps and stick it out until things get better.

And if you normalize dysfunction, you are normalizing abuse.


To be continued…

Empathy Isn’t Ending, For Crying Out Loud

Ok, I really, really wasn’t planning to write another post relating to data right after the first two. And then NPR, a source I usually enjoy for its content, published a piece called “The End of Empathy”. And I read it, and got annoyed. So now I have to write about it.

But this is only partly about data. Empathy is a really important topic to me, and I think it deserves better.

As I’ve said before, it’s important to call out how our media misuses data in service of an attention-grabbing headline. It’s easy for me to pick on Fox News for misrepresenting data, because I loathe their messaging. However, we should never let any media organization off the hook, including ones we support.

In this article on the supposed end of empathy, the author Hanna Rosin, quotes a statistic from a survey of studies done at Indiana University. “By 2009, on all the standard measures, Konrath found, young people on average measure 40 percent less empathetic than my own generation — 40 percent!

It’s a very shocking statistic. It’s what you’ll see most people quoting on social media when they post the link to the article and shake their heads about “these kids today”.

And I don’t believe it.

Now, I don’t want to come across as one of those people who will look at peer reviewed science and dismiss it. Studies are important when it comes to recognizing things like the efficacy of vaccines. But like I’ve said before, context is important. And drawing a conclusion about the entire population based on a study needs to be done carefully.

"Nuance? I can't get page views with nuance!"

Let’s break down some of the details of this study.

So for this particular study, the researchers collected data from 72 other studies that used the Interpersonal Reactivity Index (IRI). According to their paper, this is “the only personality scale that follows a multi-dimensional theory of empathy”.

Wow, a multi-dimensional theory of empathy! Sounds great!

Snark aside, psychology and sociology have a number of indexes and other tools for measuring what happens internally for human beings. And this is helpful, because we need to be able to study and compare human thought and behavior. But remember, this isn’t taking a temperature. This isn’t a hard and fast number. It’s not objective. It’s a theory, and it’s used and interpreted by human beings.

Secondly, when you are pulling together the data of a number of different studies, dating from different decades, there’s a lot of information you don’t have. You may not be able to verify the validity of each study, to double-check the methods of research, or how participants were selected. You have no window into the biases or beliefs of the researchers. There’s a huge number of variables that may be unknown.

Thirdly, in this study, the researchers are collecting this IRI information to examine the change in college students over time. The researchers make deliberate mention of how they feel that this is a valid group to use, because college student populations have not changed much over time for “important demographic variables”.

So in the actual study, we are told we have 13,737 college students, of which it is estimated that 63.1% are female, and 69.0% are Caucasian, although the researchers admit that not all the studies they used included racial demographics.

And to be clear, when they say college students, they exclusively mean 4 year institutions.

And all of this would be fine, if the NPR article had bothered to make a distinction between “young people” and “college students”. But the author doesn’t. She uses these terms interchangeably.

She takes this information about a certain subset of the population, makes the broad generalization that it applies to everyone, and to top it off, makes some huge assumptions about what this means for our society as a whole.

"So based on the author's conclusions, we should be in total anarchy in about twenty years."

Now, my problem is not with the study itself. Sara Konrath and her associates wrote a really interesting paper. They talk about alternative theories, they acknowledge the limitations of their study, and are very clear on their data collection and analysis methods. They speak to the lack of similar studies being done in other countries, and a corresponding absence of cross-cultural information.

My problem is in the representation. I understand that all writers want a lot of clicks. I love getting clicks myself! And of course we love to come up with catchy headlines.

But what we say matters. If you’re talking about college students, you are not talking about people in the demographics that are less likely to go to college. You’re not including people in certain socioeconomic groups. You’re not talking about how attitudes may change for people at different stages in their lives. That is not everyone.

And if you’ve looked at 13,737 college students over the past few decades, that’s great. That’s a lot of information. But we have over 300 million people in this country right now. You may have an interesting piece of the picture. You cannot say it is the entire picture, not honestly. Not enough to conclude that “Young people just started questioning what my elementary school teachers had taught me.”

There’s nuance to be had here. And this article shows none of it.

"If kids today have no empathy, clearly I am part of a much superior generation! Ha!"

I also want to take a moment to address something else from the article. The author is talking to a writer who is promoting his book on empathy, and includes this quote: “Breithaupt is alarmed at the apparent new virus of selective empathy and how it’s deepening divisions. If we embrace it, he says, then “basically you give up on civil society at that point. You give up on democracy. Because if you feed into this division more and you let it happen, it will become so strong that it becomes dangerous.“.

I’m trying to think of a really polite way to say that I’m really tired of this kind of BS.

First of all, this “deepening divisions” rhetoric is being used so frequently, and I’ve seen it from a number of writers and creators that I respect. And it bothers me so much.

Because to me, speaking about deepening divisions is a huge red flag that we are dealing with someone who has not engaged with or read much about human history. To be blunt, If you think people are more divisive now than ever, you need to learn more.

And to me, it’s a double red flag when the word “civil” is used. Because telling people they need to be civil is a literal supremacist technique. I’ve written about this before, but claiming that oppressed people will get all their rights if they just ask “nicely” is a strategy of dominant culture to get everyone to sit down and shut up, and just accept the status quo.

Oppressed people finding their voice isn’t divisive. It’s empowering. And yes, to those who don’t want to hear those voices, or haven’t done the work to understand their own privilege, it is unpleasant. It does feel “uncivil”. It feels divisive when you want people to just go away, and they insist on continuing to exist, and even (*gasp*) being treated like full human beings. And many are attempting to deal with this by frowning and writing articles and publishing videos that bemoan how our society is just going down the tubes.

But there is always more to the story.

"No, there's no reason I have so many quotes from someone promoting a book. Why do you ask?"

Finally, it’s also a good reminder to be cautious in reading articles like this when the author finishes her piece with the declaration that the quoted Breithaupt has an “ingenious solution”, when he is oh-so-coincidentally selling a brand new book on empathy.

No bias there, I’m sure.

In the end, yes, we can look at studies like this, and have interesting discussions about the data. I think talking more about empathy is a fantastic thing. Studies that reveal some insight into how people think are great. But using data responsibly matters. And how you talk about things matter.

Empathy isn’t ending. There have always been those who have been cruel, and those who have been kind. Change happens, and attitudes and beliefs ebb and flow. Nothing is constant.

But let’s cut it out with the grand pronouncements, ok?

Sunday Reflection – Grief and Perspective

When my friend texted me the news that Notre Dame was burning, I was surprised by my reaction. I was surprised by the level of my grief.

Yes, I’ve been lucky enough to get to go to Paris. But it wasn’t my favorite city. I found it less memorable than other places I visited on that trip. And we didn’t even go inside Notre Dame, just walked past and took a few pictures.

And yet, watching the video of the flames made me cry.

A writer, Chuck Wendig, said something on Twitter that really resonated for me. He said, “Hard not to see it both for the loss of itself and what history it carries and also as a symbol for the fragility of things and the dangers and anxieties of our era.”

It’s important to give ourselves grace when it comes to grief. There will always be those who question why people will feel sad over buildings or ideas or even fictional characters. But these things do mean something. And that’s ok.

However, at the same time, I think what’s happening with Notre Dame is yet another glimpse into privilege and a lack of perspective. Because as of writing this, there has already been 1 billion dollars donated to the rebuilding of the cathedral. And I’m sure there will be more.

I understand. We all had an emotional reaction, and people with money want to make their mark on something they see as important.

But the Catholic Church already has a lot of money and resources. There are many other institutions and organizations that could really use some of that billion dollars. A building is never going to be worth more than human lives.

Our grief is valid. But we shouldn’t forget that even our grief can have bias.

Data and Leadership

Last week I talked about some of the ways that data is misunderstood and misused. Today I want to circle back to leadership, and talk a bit about how these data issues can have far reaching impact in the workplace, and why every good leader needs to use data responsibly.

I know, I know, two posts in a row about data. But I think this is important for two reasons.

The first is that not everyone has access to the same levels of education, including math and science. There’s a large number of people who don’t have the background to understand how easy it is to misunderstand data, and inadvertently cause harm. The more we talk about it, and the more accessible we can make it, the more everyone benefits.

The second reason is that there are a number of people out there who know exactly what they are doing when they misdirect or abuse data. This happens extremely frequently with those in high levels of power. And I want all of us to have the capability to call out bad data when we see it.

Not all of us are managers, but all of us can be leaders. And a leader, at whatever level, needs to be able to question data being used in bad faith.

"Bob, your chart is terrible!"

Today, I want to break down one of the most frustrating examples I’ve seen of bad data used in bad faith, which was sent out by my agency’s HR department. Not only was the data suspect, the way it was delivered was problematic.

HR did regular employee engagement surveys, which on its own, is not necessarily a bad thing. As defined by Gallup, engaged employees are “those who are involved in, enthusiastic about and committed to their work and workplace”. Doing these surveys is common at workplaces, and often a well-intentioned attempt to take the pulse of the workforce. But like most surveys, it’s extremely important to recognize the limitations of the data that you can collect.

And yet, a few years ago, the department sent out a very cheerful email to all employees. After the most recent employee engagement survey, they were thrilled to report the results. According to them, employee engagement was extremely high. In fact, we even beat the national average as reported by Gallup. We may have assumed that our overwhelmed, overloaded bureaucratic institution with constant turnover was struggling, but in fact, we were in great shape!

Any theories on what the issue might be with a message like this?

It’s a bit of a trick question. Because there’s not just one issue.

"I'm pleased to inform you that you're all very happy at work!"

Issue one – these surveys are voluntary. Now I don’t necessarily advocate forcing staff to fill out surveys. But tell me this – if you’re feeling disengaged at work, unmotivated, invisible, checked out – how likely do you think you are to do a survey asking you how you feel?

If you’re so overwhelmed with work that you’re doing overtime, and still unable to keep up with workload, how likely are you to stop what you’re doing to fill out a survey?

If you’ve spoken out to management and asked for help and support, and they’ve ignored you, how likely are you to think it’s worth your time to fill out a survey?

This is what is known as a sampling bias.

Let’s look at it this way. Say you want to do a survey to find out if everyone in your office would be willing to chip in for a new microwave. So you sit in the kitchen with your clipboard, and ask people as they come in to heat up their lunch. And you discover that a strong 90% of those people would be willing to give money. So you decide to let your manager know that 90% of the office is in favor of the idea.

But you didn’t ask the entire office. You asked the people who come into the kitchen. You didn’t ask the people who go out to eat, or go home for lunch. And those are the people who are less likely to want to chip in for an appliance they don’t typically use.

You didn’t sample everyone, so you can’t conclude your results apply to everyone.

This is what HR did. They sampled only those employees who had the time, interest, and inclination to provide feedback. And yes, most of those people would come across as engaged.

But that’s not all your employees. And HR should know that.

"I think we can safely say the two of us represent everyone's opinion!"

Issue two – we had huge rates of turnover at this agency. I know, because I worked in personnel for a number of years, and also handled hiring as a manager. It was not uncommon to see workers come in and burn out within a year, or for longer term employees to shift to the private sector.

So this employee engagement survey, even if you could get every employee to voluntarily fill it out, is missing a huge piece of data.

It’s missing the thing we can’t see. The people who aren’t there.

This is another common kind of bias, called survivorship bias. There’s a fantastic article on it written by David McRaney, that I highly recommend.

Essentially, we as humans, have a tendency to ignore what we cannot see, and give extra weight to what we do see.

Say, for example, that you are tasked with doing a survey of all the chairs in the office to see which brands hold up the longest. And you find some chairs that were bought twenty years ago, and yet are still in almost perfect condition. You make note of the brand, and think, wow, this brand is just amazing! We should only buy this brand from now on!

What you’re not seeing? All the chairs from that same brand that broke down and were thrown out years ago. The chairs that didn’t make it past a year or two. The chairs that would lead you to a different decision.

You’re missing an important part of the picture.

And again, this is what HR did. They didn’t do exit surveys, they didn’t follow up with ex-employees. They just looked at what was in front of them and used it to drawn conclusions for everyone. It’s not a true picture of what is happening.

"Well, I don't see any problems from up here!!"

Issue three – the presentation is a problem, as are the power dynamics.

This is not about why the data itself is important, but rather what you try to say with it.

Now it’s entirely possible that the HR team responsible for the survey and email didn’t realize the issues with their data. Which is rather concerning, but it’s possible.

However, it’s one thing for a co-worker to send out some information that could benefit from a second look. It’s a different thing when it comes from those who have power and control over your career.

There is a danger when those in positions of power misrepresent the truth, intentional or not. When people with power use data in bad faith, it has an impact. They’re sending a message, even when it’s not deliberate.

And I can guarantee that HR does know the turnover rates for the agency. I can guarantee that they were very aware of the problems employees faced with workload, stress, burnout, and other office frustrations.

We can give others the grace of assuming good intentions. But it doesn’t give them the right to not be called out for what they say. And HR should be called out for this.

Because there’s a big problem with HR sending out an email that says “you are all really happy and engaged, aren’t we so lucky!” while ignoring all those missing pieces of data.

It sends a strong message that your problems are not important. That they care more about their numbers looking good than delving into the reasons people are leaving. That if you’re not happy, the problem is entirely with you, and not the agency.

This is why I use the term bad faith to describe how data is sometimes used. Because data is good for educating and making informed decisions. But when you’re using it to sugarcoat, minimize problems, or otherwise distract focus from the negative, you’re not using it in good faith.

It’s one thing to want to encourage positive thinking. But when you refuse to acknowledge the negative, and try to throw sparkles over the situation, it’s patronizing. You’re trying to invalidate employees who are not engaged. You’re telling them they’re the minority, based on bad information, instead of trying to actively solve what’s wrong.

"No, I don't want to hear about your problems, the data proves that everything is fine!!"

I know this may seem like a lot to write about one email, but I think it’s such a good example of how small things can have a big impact. I still remember this email after several years, because of how insulting it felt.

When you are in a leadership position, it’s important to consider these things.

Doing a survey is fine. But be honest about what you’re measuring and what might be missing.

Sending out an encouraging email is great. If there are some positive trends in the data, fantastic. But don’t make grand claims. Don’t insult the intelligence of your employees by pretending one survey proves anything beyond a shadow of a doubt.

And above all, be aware of how you’re presenting your information. If you have power over others, you have to consider that in your message. You will not always be able to see your own bias, but if you are open to criticism, people will let you know.

As with all of the important tools of leadership, this is about being mindful, careful, and smart. A hammer can be used to hurt or to build. Data is no different. Use it wisely.

Sunday Reflection – Gratitude Check-In

Lately I’ve been thinking about how I’m never going to run out of examples of bad leadership. All I need to do is look at the news for five minutes. Whether it’s our government or a major company, poor leadership is everywhere.

I do really enjoy writing for this blog, and it’s often very cathartic to call out the bad stuff. But every once in a while it feels good to focus on the positive. So I think today is another good day for gratitude. To push away the selfish and the narcissistic. They’ll still be there later.

Right now I’m grateful for:

  • Waking up to birdsong by my window, and getting to see my neighbor’s cat sitting at the back door, watching the world outside.
  • Finishing a creative project, and feeling really proud of myself for it.
  • Unconditional support from loved ones.
  • People who never stop fighting for what is right, no matter what.

What are you grateful for this month?

Amplifying Voices – Ijeoma Oluo: Confronting racism is not about the needs and feelings of white people

Most people would agree that in order to learn, you need to listen. Truly listen, not just waiting for your turn to talk, but actually taking in and thinking about what other people are saying.

And yet, time and again when people from marginalized groups are talking about their experiences, members of the dominant group jump in. “Wait,” they say, “What about what I think?! What about my feelings!”.

The author of today’s piece, Ijeoma Oluo, just relayed a story on Twitter, where a white man was the first in line at a Q & A and proceeded to yell at her for making him feeling discriminated against by writing the article.

Here this man had a golden opportunity to listen to a woman of color speak to her experience. And yet, all he cared about was how he felt. Not only did he only care about how he felt, he thought it was Oluo’s responsibility to answer to him for his feelings, and felt entitled to take up one of the questions for his personal wants.

There’s a lot to say about this kind of entitled reaction, but for now I’ll keep it to these two things.

1) If there are discussions happening around a culture where you are a member of the dominant group, shut up and listen.

2) Members of the marginalized groups owe you nothing. They don’t have to explain themselves, defend themselves, or take time to educate you. Many of them do, out of generosity and a desire to foster change, but you are not entitled to it.

And with that, please read Oluo’s piece.

Data Matters

I want to do something a little different today and talk about data.

I know, not the sexiest topic in the world. But it’s an important one.

I was in a unique position while working for a social services agency, because I didn’t start in that field. I majored in biology while an undergrad, and after college I worked in the natural sciences for a number of years. I worked on a number of studies, and even published a paper called “Variation in resource limitation of plant reproduction influences natural selection on floral traits of Asclepias syriaca”, which is very fancy language for the time I spent an entire summer measuring flowers under a microscope.

One of my required courses as a science major was statistics. It was an interesting class, but what was most interesting was how it made me realize that statistics are incredibly easy to abuse. People are often impressed by them, because, well, they look impressive. But the truth is there are huge limitations and how statistics are used can have dangerous repercussions. Data can be used to oppress and abuse. It can be used to reinforce the status quo. It can be used to outright lie. And that’s why we need to understand it.

Even heroes needs math!

Coming from a science background meant that I had some pretty horrifying moments in joining social services, when I realized how data was talked about and used in making important decisions. Because it was bad. Really bad.

When I was recruited to join the training team for a local leadership program, I knew I was going to have to talk about data. In order to graduate, each participant had to design, implement, and complete a project. (To the best of their ability – we did give leeway for existing in a giant bureaucracy that could crush a months long project in minutes flat). And the last thing I wanted was for them to continue following the agency’s lead when it came to the use of data in project planning and implementation.

My co-trainers were kind and encouraged me in my data needs. Logically, I knew part of a one day session was never going to be enough to change the behaviors of a whole agency, but I had to try.

And as we hear a lot of the political discourse that is happening in the news, I feel like I need to talk about it again. Because there is a lot of bad data out there.

For some reason, the training montages always leave out this part.

Item 1 – who benefits from the data?

In the 1990s, pharmaceutical company Merck was developing an arthritis drug called Vioxx. They wanted FDA approval, because approval means money. So they engaged in a number of unethical practices to fudge their results in the clinical trials. The worst part is that they were not just hiding unpleasant side effects, but actual deadly ones. The end result? In 2006, estimates stood at 88,000 Americans having heart attacks from taking the drug, with 38,000 of those events being fatal. The drug was pulled, but the health impacts lingered.

More recently, Boeing has made the news for their 737 Max plane being involved in two crashes. Although there are still ongoing investigations, there is some evidence that the Federal Aviation Administration allowed Boeing to choose their own personnel to conduct safety studies, allowing the manufacturer to hold most of the power in approving their own aircraft. And if your job depends on you finding an aircraft safe enough to go to market in time for an important deadline? It’s going to get approved as safe.

It’s important to understand that this happens a lot in studies. Some of it is deliberate. Some of it is accidental. Some of it is due to unconscious biases. But you have to ask the questions, any time you see a study. Who paid for it? And who benefits?

As you can see, there's a clear increase...

Item 2 – correlation is not causation

People really struggle with this one. And it can be confusing.

Conveniently, there’s always plenty of examples of how this one works. Pretty much any time you pick up a paper, you’ll see some form of this.

Recently, an article was published about a study that found a correlation between men’s cardiovascular health and how many pushups they could do. Simple enough, right?  And most follow-up articles you find about it have headlines like this one from USA Today that say “Men who can do 40 push-ups have a lower risk of heart disease”.

Then there’s another type of headline, like this one from the Good News Network: “New Harvard Study Says That Men Can Avoid Heart Problems By Doing a Certain Number of Push-ups”.

Do you see it?

In the first article, they are reporting a correlation. Men who can do a high number of push-ups also have a lower risk of heart disease.

In the second article, they are reporting a causation. Go do push-ups, and you will lower your risk of heart problems.

Both of these are top articles on google. Both are reporting the same study. Both use the same data. And one is drawing the exact wrong conclusions.

When I was writing on empathy previously, I looked at a number of videos on Youtube. And I watched a particular one that talked about the science of increasing empathy. It’s a well intentioned piece, but there’s a flaw. At the end, they have an actor pretending to be homeless, and they watch as their study participants donate money. The participants who watched a video with a personal story about homelessness donated more money on average than the participants who watched a video with only statistics. So in the experiment, they confidently conclude that the personal video caused the participants to donate more.

It’s possible that this is the case. But again, we don’t have enough data to know for sure. There definitely seems to be a correlation. But a correlation is not causation. Much more data is needed, with a much bigger group of participants, before you can say something didn’t happen by chance. Maybe the participants were influenced by the video they watched. And maybe the designer of the study, subconsciously wanting a specific result, happened to sort the people in specific ways. Or maybe the people were just coincidentally sorted in a way where people who tend to donate more were in one particular group.

And this is the problem with much of pop culture science. It’s meant to make an impact, but it’s limited. This is why studies need to be repeated, with different participants and different scientists.

So if you see a really exciting headline, just remember to ask yourself. Did they prove causation? Or are they jumping to conclusions?

Ugh, of course it was a fake graph! Do your research!

Item 3 – getting only part of the picture

There’s a British magician named Derren Brown who once filmed himself flipping a coin and getting ten heads in a row. Something very statistically improbable, and yet he made it happen in under a minute. Magic!

Only, it wasn’t. Because he was only showing the last minute of what actually happened. And what actually happened was that he filmed himself flipping a coin for over nine hours, until he got the results he wanted.

One of the most popular “health indicators” in our society is the use of the BMI (Body Mass Index). For many years, the BMI has been used to provide a part of the picture when it comes to a person’s health. But it’s not a complete picture.

Did you know where it comes from? The original formula was developed by a Belgian mathematician named Adolphe Quetelet, back in 1835, in an effort to define a “normal” man. So almost 200 years ago, this guy crunched some numbers. And that’s fine, that’s what mathematicians do.

Then, in 1972, a researcher named Ancel Keys modified the formula, when he studied 7,400 men.

Sit with that one for just a moment…

Now, after years of major health organizations promoting BMI numbers as something to aspire to, more recent studies indicate that the BMI may not be the most accurate indicator of health, including for the following groups: Asian people, athletes, women who may be pregnant or nursing, nonpregnant women, and people over 65.

Now, maybe it’s just me, but I think that if you take all women who are pregnant or nursing, and all women who are nonpregnant, than you actually end up with…let me calculate here… all women?

And this isn’t even delving into into racial biases when it comes to health studies and data.

In fact, Keys himself didn’t think the BMI should be a diagnostic tool, as there are so many variants in health for each individual. It was intended to show an average for a population, not an aspirational goal for an individual.

Caroline Criado Perez recently released an entire book on the way science has excluded women from studies, and focused almost exclusively on men. Everything from seatbelts to medications can be more dangerous for women, because of this bias. You can read an extract here.

Excluding half of the world’s population is not good science. And misusing things like the BMI or designing safety measures based on men’s measurements can cause real damage to real people.

So it’s important to ask. Who’s not being included here? What data might I be missing?

What...am I even looking at!?!

Item 4 – misdirection

This one isn’t about who funded or initiated a study. This is about people taking numbers and misusing the data to prove their own conclusions.

One recent example is the movie Captain Marvel. Heading up to the release date, a number of people online, mostly men, were deeply critical of the female-led movie and the lead actress, Brie Larson. These men kept talking about what a failure the movie would be, and they would do everything they could to present data that supported their position.

After the movie’s opening weekend, the box office on Monday showed a drop of over 70%. Immediately the critics jumped on this number, writing that it proved that the movie would be a flop.

The problem? That kind of dropoff is completely normal for big blockbusters. More people go to the movies on the weekend than on Mondays. It’s a number that only seems shocking if you don’t know any of the context.

This is a strategy you’ll see a lot when it comes to political discussion. And one of the most common ways to misdirect people about data is to use a graph.

I won’t go through every way that graphs are poorly used, although I do highly recommend reading this fantastic breakdown by Ryan McCready.

Some graphs are bad through sheer incompetence, but sadly, a large number of them are manipulated on purpose. Fox News is one example of an organization that consistently misuses public data to draw faulty conclusions. They’ve played with the axes on their charts to make changes over time seem more significant, double-counted data to improve the numbers that matter most to them, and my favorite, made a pie chart with numbers that came to a total of 193%. (For those of you unfamiliar, pie charts go to 100%. You can’t eat 193% of a pie).

This is why it’s important to look critically at any data that is presented to you. You should always be able to go back to the original source and find a match in what is being presented. If you don’t, you’re being mislead.

So who’s presenting this data? And what do they have to gain?

Death to bad data!! Aiieeeee!!

We live in a world where we are inundated with bad information. Organizations are run by people and people have agendas. Being able to think critically and question our sources is vital to making good decisions. This is particularly true if you are in a position of leadership. Because you’re not just making decisions for yourself. You’re impacting employees, co-workers, customers, and clients.

And I get it. I’ve been in management. I know how little time and money there is to think about data.

But the cost is far greater if we don’t.

Sunday Reflection – Changing Times

It’s been interesting to watch the news cycle this week and hear people talk about changing social norms, and people being a “product of their times”. A lot of people like to jump on the idea that people are just too sensitive these days, and everyone is a “snowflake” who can’t handle anything serious and needs trigger warnings on everything.

What I find funny about this idea is that it assumes that because people didn’t speak up the same way in the past, that somehow no one was being offended or hurt in prior generations. That somehow all of this has been spontaneously created out of nowhere.

Which is absurd, if you actually take the time to think about it. Do people seriously think that women were just completely ok with being manhandled all the time, and then one day flipped a switch to say, nah, I guess I don’t like this anymore? No, we never liked it. We’ve only just now started being heard when we say so. And even now, it’s a fight to not be dismissed or silenced.

It’s the same thing with people who like to claim that we are more divided today than ever. Sure, there are a lot of challenging things happening, with those who want to maintain the white male privilege status quo, and those who are fighting to change it.

But are we truly more divided? Or are there just more people able to speak their truth now than before? Everything may feel extremely “civil” when voices are being silenced. But it doesn’t mean the hurt isn’t still happening.

It’s ok to admit you’ve made a mistake. That you’ve evolved. That you have more growing still to do. Because we all do.

It’s not ok to say it’s just how you were raised. That you’re sorry if people were offended, but you’re not sorry for your actions. That you’re a person of your time.

Time isn’t a fixed point. You aren’t either. It’s time to let that excuse die.

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