Cognitive Bias in Data Visualization

Cognitive bias is a systemic error in thought or understanding of the world around us. They are subconscious and often result from quickly processing information as part of the decision-making process. These biases can affect how we see and interact with the world.

Cognitive biases affect everyone and are often unnoticed. With more than 100 cognitive biases recognized in this comprehensive list compiled by Buster Benson and John Manoogian, III, it is easy to conceive that they could make their way into how visual storytellers and designers view data to create visualizations.

Data visualization allows people to understand huge amounts of data quickly. Agency EA reports that 90% of information transmitted to the brain is visual and that visuals are processed 60,000 times faster in the brain than text. It is no wonder that data visualization plays such an important role in boiling down the huge amount of data being collected in our world and transformed into understandable, useable, shareable bites.

In my the IGNITE presentation, I’ve explored cognitive biases, how they shape storytelling, and how designers can work to avoid allowing biases to affect the stories they tell through data visualization.

Cherry, K. (2019). How Your Decisions Are Biased by the First Thing You Hear. Verywell Mind., K. (2021, April 10). How Does Representativeness Affect Your Decisions? Verywell Mind.

Dimara, E. (2019, February 13). Visualization Research in Cognitive Biases: A Survival Guide for Engineers. Medium.

Genoux, C. (2019, May 7). How to prevent misinformation in data visualization? Medium; Towards Data Science.

Hooper, L. (2021, May 23). Ten Ways Cognitive Biases Impact Data Design Work. Medium.

Noor, I. (2020, June 10). Confirmation Bias | Simply Psychology.

Wikipedia Contributors. (2019a, May 23). Confirmation bias. Wikipedia; Wikimedia Foundation.

Wikipedia Contributors. (2019b, August 16). Availability heuristic. Wikipedia; Wikimedia Foundation.

3 thoughts on “Cognitive Bias in Data Visualization

  1. lhrobins27 says:

    This is such a helpful piece; I Had some great takeaways from it. The most standout information was that our brain groups hundreds of cognitive biases into only four groups!

    As storytellers, and to some degree, marketers, I feel there is a constant need always to present a sense of urgency or a sense of missing. As you mentioned in the Kohl’s examples, including an “original price” might make me feel like I’m missing a great deal, when in reality, it could be cognitive bias we’ve been conditioned to learning.

    Looking at how this translates into data, it becomes super important, like you state, to correctly interpret the data in a way that presents bias-free consumption.

    I would be curious to know if there are any steps consumers can take to unlearn these biases to understand better the data they are being presented. That, or we can better scrutinize those who intentionally lean on cognitive biases to skew data and influence opinions. That might be an excellent area to explore in your paper if you haven’t already thought about it.

    Great job fitting so much information in so such a short time; also nice job avoiding words, it was hard for me too 🙂


  2. Julie Anderson says:

    Hi Jenny,

    Great video and very interesting topic! Your audio and pace sound smooth and clear, making it easy to understand and follow along with you. The organization of the video is done very well, starting with stats, moving onto how biases happen, and how to avoid them.

    I’ve always thought about the viewers of data visualizations and infographics as being the ones with the biases, but of course, it has to start somewhere – the designers. Biases are hard to break so I can see how this is a substantial issue when designers take on projects, whether it’s handed to them or not.

    I’m curious about the difference between designers who do it without realizing, and the ones who do it intentionally. As you said, it’s important to be ethical to stop the spread of misinformation. But some designers have full intention of skewing views – particularly in politics. So this might be a good touchpoint to expand on in your essay.

    1. What can you do to prevent your own bias from slipping into your design? (which you’ve already covered),
    2. And what can you do to recognize information that is influenced by bias? Because not everyone is interested in following the ethical route, unfortunately.

    Thank you for helping me realize that I can unintentionally slip my own biases into data visualizations and how to avoid them. Awesome job!


  3. briannamejia says:

    Hi Jenny! I was so interested the minute I read your topic. This is something I think a lot of people don’t talk about, but it is an extremely important topic. I like your personal anecdotes because they added so much to the audiences understanding. You presented yourself as an expert on the topic and made the presentation as interesting as it was informational.

    I learned so much from your presentation. I like how you first discussed cognitive bias and then extended that to data visualization. The questions that you gave the audience to think about made the presentation seem interactive as well as the call to action for content creators and designers at the end. The visuals you used were perfect and the presentation flow was one of the best that I have seen! I loved the old photos from the 80s when you spoke about that time period because it made the presentation feel even more personal (even if those photos were not of your or people you knew).

    For criticism, I don’t think I have any. You obviously have a great grasp of the topic and I think that this will translate to a paper wonderfully, since it is obvious you have enough information and even personal anecdotes to make this a cohesive paper! Great job!


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