The election results didn't surprise me. I knew Trump would win.
My Californian friends had shifted from passion and outrage during the 2015 campaign to complete disengagement. Three months traversing the Midwest last year showed me a different view of North America. Where the rhythm of life beats differently outside the coastal bubbles of California or New York, the enthusiasm for the Republican candidate was tireless.
What baffled me wasn't the outcome, but how people ignored clear data that showed the predicted disastrous impact of Agenda 47 (closely related to Project 25) on those who are already struggling, freedom of speech, and our environment. Numbers that should have mattered, didn't. Facts that should have resonated were drowned in factless debates on gendered bathrooms, eaten dogs, and politicized hurricanes (remember “Sharpiegate”?).
Think about your last encounter with information. Did it come from a research-driven report? A detailed dashboard? Or was it something that bubbled up through your social feeds (yes, LinkedIn too), mentioned by friends, and referenced in memes and viral content, until it simply felt like something you'd always known?
We data practitioners believe in the power of well-crafted, accurate visualizations. We trust that if we present the facts clearly enough, truth will prevail. But we're using obsolete tools in a transformed landscape.
Nathan Heller eloquently describes this phenomenon in the New Yorker recently:
Trump seemed to think that much of the voting public couldn't be bothered with details—couldn't be bothered to fact-check, or deal with fact checkers. [...] Detail, even when it's available, doesn't travel widely after all. Big, sloppy notions do. […]
Planting ideas this way isn't argument, and it's not emotional persuasion. It's about seeding the ambience of information, throwing facts and fake facts alike into an environment of low attention, with the confidence that, like minnows released individually into a pond, they will eventually school and spawn.
The election result emphasizes how our relationship with information has fundamentally transformed. It no longer flows from expert to audience in neat lines, from precise data charts buried into PDFs to institutional voices sharing it with authority to targeted audiences.
Now, information spreads like rumors crystallizing into assumed truth. From YouTube influencers to podcast discussions, to our social media feeds, and back to our dinner tables, the cycle continues.
For those of us committed to data-driven change, this poses a provoking question: How do we create visual, data-driven messages that can survive – and thrive – in this “ambiance of information” while preserving their essential truth?
We can no longer treat data visualization as isolated evidence.
Our visualizations need to support broader narratives. They need to be modular pieces that can be adapted and shared across various platforms to ensure a consistent message.
The future of data visualization is not about perfecting the most precise chart for every application; it is about creating visual shortcuts—entry points that spark deeper conversations.
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