Bridges, families, global warming and Data Literacy
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One month of blog posts!
2023 is the year I decided to start blogging. I like to read long-form content while I sip some coffee, so that is the format I chose. I went with an alternative style of making book reviews. Instead of just reviewing the book's content and arguing why you should read everything I read, I'm using the blog space to share my data viz journey and knowledge. Reading books is great, but to me, the greatest value is in applying what I learned and reflecting back on how the theory translates to real life. This is what my posts are about: why do I consider a book worth recommending? What was the impact? What did I take from it into the real world? I hope you're enjoying reading them as much as I'm enjoying writing them.
In January, I focused on Data Literacy. The skills we need to read, work with, analyse and communicate with data. Data Visualisation is an important part of it, but Data Literacy is much bigger.
I started the month telling you about Hans Rosling's Factfulness or how I learned to love visual storytelling; then, I shared how a book can become your best friend in a journey full of traps with Avoiding Data Pitfalls by Ben Jones; next, I gave you ten lessons about how not to run a Data Literacy Initiative with Jordan Morrow's Be Data Literate; and last Friday I reflected on Kevin Hanegan's Turning Data Into Wisdom and why throwing money at BI tools doesn't work.
Data Literacy is an ethics issue
Data permeates everything we do, and understanding data also means being aware of the consequences of what you choose to do with it. Data Literacy is a double-edged sword that can be wielded for good or bad. This is where data ethics comes in. The utilitarian application of data without the humanistic consideration of its impact on society and our environment is objectively worse than making uninformed decisions. It is a recipe for disaster.
Earlier this month, a group of scientists published a study showing that ExxonMobil has been aware of the effects of their industry on climate change since at least the mid-70s. Internal documents of the company, shared on Twitter by one of the people involved in the study, included incredibly accurate data visualisations predicting the increase in atmospheric CO2 concentration and related temperature increases. The NY Times picked up the story, too.
ExxonMobil is a very data-driven company. They have all the structure, processes and frameworks that enable them to make well-informed decisions, and this became even more abundantly clear in light of this new evidence. Yet, they choose to make their highly data-informed decisions with objectives in mind that have little to no regard for the broader long-term consequences of their actions. Being data-informed doesn't automatically result in good decisions. We can't divorce Data Literacy from Data Ethics.
This timely article by Bridget Cogley offers an interesting perspective on the subject. It's worth the read.
How bias and design shape our world
I also stumbled upon two other rather interesting articles that are tangentially related to the issues of Data Literacy, Design and Ethics, and if you feel like dipping your toes in deeper discussions about the world we live in, they make for very interesting reads:
Finally, I'd like to thank Kat Greenbrook for pointing out that the reply link for the previous e-mail was broken. It's fixed now!
If you tried replying to my first newsletter issue, you may have received an error message back. This time around, if you enjoyed something you read here and would like to get in touch, hit reply and let me know all about it!
As I said in issue #1 of this newsletter, I'm new to this whole content creation thing, and I will certainly go through a steep learning curve.
See you again in 4 weeks!
-- T.
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