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How Charts Lie by Alberto Cairo or how one lecture about misleading charts can change a life

written by human, not by AI

My career had many twists and turns. I wasn’t born of privilege. I grew up watching everyone around me constantly concerned with money, and the scarcity mindset is still embedded in me to this day. I am aware of it, but It is a hard thing to shake off. One of the main things that the lack of freedom of choice imposed by lack of resources does is to narrow career possibilities.

Growing up, I didn’t have as many opportunities to explore things I could be good at, try them, make mistakes and try again later with little consequence. Every choice I made had to be carefully analysed: can I afford to do this? Can I afford to sit here and read a book, or should I look for work instead? Can I afford to learn English, and if I do make this sacrifice (considering other things I won’t be able to afford because of it), is it going to be worth it? Can I afford to go to college, and if I do, can I afford to change my mind if it’s a terrible career choice? If not, can I afford to live with this choice forever? Can I afford to have lunch at school today, or should I use the money to catch the bus back home later in case it rains? Poverty is an exhausting mental exercise of trade-offs, a constant reminder that the idea of freedom of choice does not seem to apply to your portion of society.

“What does that have to do with today’s book recommendation?!” I hear someone in the back ask. Stick around, you’ll see!

I finished high school at a public technical school (where you go to learn a trade) and later got into their Graphic Design course. This was not decided without protest from both my family and the nagging voice in the back of my mind, saying, “Are you insane? Artists die of starvation. You won’t make a dime. Go find a real job instead”. A little after, I got an unexpected government offer of a scholarship to attend a private University (the first of its kind in my country back in the day!), so suddenly, career choices weren’t as scarce. I then decided to drop Design and invest in studying International Relations. It was an interesting subject, it seemed like career prospects were better than a creative field, and I would make everyone happy by choosing something that would have them see me walking around in a business suit and high heels. Most importantly, because of the scholarship, I could afford the risk.

I still had to work while studying, though. I got a job at a bank, then an insurance company, then an oil company, then a couple of FMCGs, then mining and so on. Each job was in a different industry, in various sorts of teams. My resume was one of those that makes HR people scoff in disgust and label me as a job hopper. Looking from the outside, I didn’t really have much of a career at all. The thing is - it was a career. I just didn’t have a name for it back in 2006 when I got my first internship.

There was indeed a common thread running through all my experiences. I was always asking questions, trying to understand the processes, systems, and data I was working with. This curiosity evolved into a skill, and I inevitably became the spreadsheet person in every job I had. I excelled at picking up complex data, making sense of it, and communicating it to my bosses and other teams. My background in Graphic Design (albeit brief) allowed me to present the information in a way that was easy to understand.

Yes, I had different jobs in different teams across different industries - but in all of them, there was data visualisation. Everywhere I went, I ended up with a report (or many) to run or slide decks to improve. Slowly all of my jobs would morph into being a thing nobody in a non-IT function had a name for and, therefore, couldn’t fit into a budget. Hence, the hopping.

My first official data analyst role.

I moved to New Zealand in 2016. Here, I got a job as an Insights Analyst. I had never heard such a position name before, but it was in a supply chain team, an area I was very familiar with. It seemed that being a spreadsheet person and a design person at the same time was a useful combination, after all!

I learned a lot as time progressed, but that process came with several challenges. I am a Latin-American female immigrant. Despite having the skills to do the job and the recognition of some of the leadership, it was hard to bring my experience to the table and have my voice heard. The way I did things clashed a lot with how the members of my all-male team have always done things.

I’ve always emphasised the communication element of what I was analysing and sharing with others. My Design knowledge gave me an advantage in knowing strategies to help me showcase that work in engaging ways to my audience. But I found out that to my colleagues - with more traditional backgrounds, mostly coming from Accounting and Engineering - design and communication were almost dirty words. Whenever I brought up anything remotely related to either concept as an alternative way to increase stakeholder adoption of our reports and dashboards, I’d be laughed out of the room. I would hear arguments such as “data speaks for itself, no need to do anything else” and “all the data is there, they can interpret it themselves” or “if you want to draw pretty pictures, maybe you should be in marketing instead”. What good is it to have all this data if others can’t make use of it? It baffled me every time, and I kept trying.

Needless to say, my shine and love for the work I was doing had diminished dramatically after a couple of years, and I was not as engaged as before. Even though I believed in the potential of how I wanted to approach my projects, there’s only so much someone can take being hammered into status quo compliance. By 2018 I was already nearing burnout.

The day I figured data visualisation could be a career.

During the years between 2016 and 2018, Data Visualisation was a functional part of my job. I knew what it was. I had heard of Hans Rosling and Tufte and followed a few blogs and websites that shared amazing charts and infographics. I was always left in awe, thinking I wanted to be able to do something like that. Then the dream bubble would be popped by the next monthly deck of slides I had to update on why we didn’t hit delivery targets. I knew that someone, somewhere, did those awesome things for a living, but it looked so far removed from where I was and what I knew at the time I never considered this to be a possibility (see the scarcity mindset here again?). But that changed when I watched Alberto Cairo for the first time.

Alberto Cairo gave a lecture at the University of Auckland in March 2018. It was called Visual Trumpery. A colleague invited a friend and me to come along, and we did. All I knew about it was the blurb I had read in the flyer before the lecture. Visual Trumpery was a tour of lectures Alberto Cairo did on his research on misleading charts and visualisations - which eventually became this week’s book recommendation: How Charts Lie.

If you’ve never seen Alberto Cairo talking about data viz and all the visual trumpery that was happening everywhere circa 2018, you should stop everything and watch it now:

There I was, watching a long lecture about design and communication and how they are so essential to help people consume data. The lecture was very informative in general, but to me, the most meaningful bit was getting someone with years of expertise in the field and who makes a living out of it, telling to a room full of people (including some accountants and engineers from my then workplace) that design and communication matter when dealing with data. He opened by saying he got nervous when talking about his job in front of statisticians, and here I was nodding in agreement like: “yes! I, too, don’t belong here, yet here I am!” It may sound silly, but I felt validated and empowered.

Suddenly I realised that there was something I could do with my unusual set of skills after all. Later that year, I enrolled in a free online course offered by the Knight Center for Journalism from the University of Texas in partnership with a Google News initiative. Alberto Cairo was one of the leading instructors, and it was probably the best course teaching data visualisation I’ve ever seen. It covered the theory, the research, and the tools, it had plenty of practical examples and exercises and extra materials, and it lasted weeks. I loved every bit of it, but I, unfortunately, fell behind and never delivered my final project to get the certificate. I was deeply excited by my newly discovered passion, but my day job was becoming more and more soul-crushing each day. Something had to give. Hello, burnout.

Not all was grim and dark, though. I had acquired new skills, and a tiny seed had been planted in my mind. I just had to nurture it. In 2019 I took a leap of faith and quit my job. A couple of months later, in October 2019, I launched Data Rocks. For the first time in my life, I felt like I could afford to make a risky choice. I chose to be my own boss. The pandemic hit a little after, and there I was, doing reports for a Health Insurance company. A little later, I was helping a consultancy to get going with their new data viz team. I trained a whole group of early career data viz practitioners. Afterwards, I created a dashboard for a frozen berries factory. Hopping from one project to the next became a feature, not a bug. My expertise is well received and acknowledged. I help people see and do more with their data. I make a living out of Data Visualisation and love every minute of it.

Thanks, Alberto.

Enough about me, to the book:

How Charts Lie is a book aimed at a general audience that consumes charts daily through news, social media, TV, work or other mediums but is unaware of how it all works. If you are a data viz person and your aunt always asks you what is it that you do, but you never manage to explain, give her this book with a note saying: “I help the charts not to lie.”

Alberto Cairo has a very humanistic, almost philosophical way of writing. His years working in journalism and academia show through the way he constructs the book. He opens his first few paragraphs by explaining that the well-known idiom “a picture is worth a thousand words” should be complemented with “if you know how to read it”, - giving us a taste of what comes next. His first chapter explains a bit of the theory of how charts work. The author takes us through several ways how we may be misreading charts or how they may be inducing us to an incorrect perception of the data they are supposed to communicate.

His framework is a neat, simple way of breaking down how a chart is formed by simpler parts, which helps us see more clearly how each element in a graphic representation of data can mislead us.

Here’s how Alberto Cairo teaches us to read a chart:

  1. Identify the scaffolding elements - title, legends, axis, scales, and units. What are they? Does the value axis start at 0 or not? Is there a callout or headline? What is the source of the data represented? Is it trustworthy?

  2. Look at the visual encodings used - to visualise data, we encode numbers and dimensions using shapes and colours. Bars (a rectangle placed on an axis) can vary in length based on a number. A bunch of dots can vary in position over a plot and be grouped by colour. What are the encodings used in the visualisation? Can you name them? How are they representing the data?

  3. Read the annotations - are there any annotations guiding you through the visualisation? Do they explain more of the context around the visualisation?

  4. Take a bird’s eye view - can you spot any trends, patterns or relationships? What are they? Do they make sense in the context of the chart?

How Charts Lie also contains multiple examples of graphs that deceive us - whether intentionally or accidentally - and how we can become more aware of the ways the deception may occur. Design and communication are vital factors discussed all across the book. The examples range from multiple subjects - from elections in the US to heavy metal music, from crime to movie box offices, never forgetting to discuss the ethical considerations that everyone producing charts should keep front of mind to avoid falling for each of the “lies” discussed.

Beyond design critique

The ways the book presents how charts can lie to us are not limited to how the charts look. This may be a common misconception when picking up a book like this: that the focus is on charts that are bad by not following a prescribed set of style rules. This is not the case here.

The meaning, the context, and the misrepresentation of the data’s characteristics are all mentioned as ways we can be misled by visual representations of data.

According to How Charts Lie, charts can mislead us in several ways:

  • by being poorly designed

  • by using incorrect or untrustworthy data

  • by showing an inappropriate amount of data - either too much or too little

  • by concealing or confusing uncertainty

  • by suggesting misleading patterns or relationships

  • by pandering to our expectations, prejudices and personal bias.

In the closing chapter, Alberto Cairo discusses one of my all-time favourite charts - the Nightingale rose. He goes through a bit of the history behind her charts and how Florence Nightingale used them as tools to promote the need for change in sanitation practices during wartime. It is a fascinating piece of history. Throughout the chapter, the author points out that everyone has a crucial responsibility in designing charts as truthfully as possible, according to their data. The data must be, first and foremost, trustworthy. We should avoid using charts as instruments to validate and perpetuate our preconceived ideas. Charts may convey an air of certainty, clarity and reason, and while that can be beneficial, it can be very damaging if this air of authority is used for the wrong purposes.

How Charts Lie by Alberto Cairo shows how representing data visually is a powerful tool but one that comes with great responsibility. It is a double-edged sword. The same techniques that can be used to inform, clarify, explain, and persuade for positive change can also be used to mislead, misinform, cause confusion and perpetuate harmful biases. And while the designer has a lot of responsibility to acknowledge these risks and work to minimise them as much as possible, the reader of such charts also plays a fundamental role in ensuring they don’t fall for the lies that graphs may be telling them.

This is an excellent introductory read on how charts work and what could go wrong. By the end of the book, you’ll have learned how to be more aware of how charts can be misleading and influence you to believe incorrect or false statements. You’ll also understand a bit more about the craft that goes into designing and communicating data effectively and truthfully.

Should you read it

Everyone interested in being well-informed about the current digital society should read How Charts Lie. It will help you make a more informed assessment of the information you consume daily. This book will serve as a good guide on how not to fall for misinformation in chart form.

If you are interested in working with data analysis and visualisation, keep in mind that this is an introductory book to the subject, even though it does provide a framework and strategies to prevent creating or perpetuating misleading visual representations of data.

Always check your local library first to see if any of the books I recommend are available. If they’re not, consider donating a copy!


Get a copy at your local library | Amazon


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written by human, not by AI

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