A while back I was interviewing for a research scientist position at [company redacted]. I had already picked up kind of iffy vibes during the day, but there was a point where it crystalized into “ah, I don’t want to be here, and they probably don’t want me here either.” It was when, after an interview loop that was mostly focused on my research and places where I could intervene, I was asked by a new interviewer to take a marker, go up to the whiteboard and, in my “preferred language,” implement a stack data structure using queue data structures…
Huge swathes of people, in Europe and North America in particular, spend their entire working lives performing tasks they secretly believe do not really need to be performed. The moral and spiritual damage that comes from this situation is profound. It is a scar across our collective soul. Yet virtually no one talks about it.
–David Graeber, On the Phenomenon of Bullshit Jobs: A Work Rant
This is one of those historical stories that probably never happened (or didn’t happen like we think), but is so useful as a metaphor that it’s best to pretend that it did. The story…
This post was collaboratively written by Heather Froehlich and Michael Correll as part of our “Provocation” submission to the Visualization for the Digital Humanities workshop at IEEEVIS 2020, “Making Sense of a Sea of Dashboards.”
Tl;dr: Dashboards in the visualization community are often conceived of as decision-support tools that sharpen the mind, triage otherwise ungraspable amounts of information, and bring into focus a single accurate and actionable picture of a subset of the world (as admittedly fraught and positivist as that project is). But we see a troubling trend of dashboards specifically, and massed collections of data more generally, acting…
This post will largely be about the MIT Media Lab’s “Moral Machine” work, after a brief detour. If you don’t recall, the Moral Machine was a series of crowdsourced experiments where people were presented with a dilemma in which there is an autonomous car with, say, malfunctioning breaks, careening down a street, and we are given the choice to either let the car continue (striking and killing the pedestrian(s) crossing the street in front of us) or swerve out of the way (striking and killing pedestrian(s) on the side of the road), in essence a version of the famous Trolley…
This post is meant to accompany our honorable mention paper for CHI 2020, “Truncating the Y-Axis: Threat or Menace.” For more information, read the paper or consult our osf repository. This post was written collaboratively by Michael Correll, Enrico Bertini, and Steve Franconeri.
If you’re not immersed in information visualization culture, this is one of those papers that looks so obvious as to be trivial. The general gist of the paper is that, in charts like the following, the bars on the left look more different than the bars on the right:
This is despite the fact that both charts…
I am a researcher in information visualization. I’ve focused on lots of things in the past, including uncertainty visualization, statistical graphics, and bioinformatics. There are lots of current pandemic data visualization challenges that feel directly connected to my past or current areas of research. How do we translate the argots of virology and epidemiology into contexts that are useful for mass audiences? How do we communicate exponential growth, confidence intervals, log scales, model errors, and simulation results to audiences who may not have seen those sorts of things before?
This post co-written by the organizers of the Visualization for Social Good tutorial at IEEE VIS 2019 in Vancouver, BC: Leilani Battle, Michelle Borkin, Michael Correll, Lane Harrison, Evan Peck, and Uzma Haque Syeda.
What We Did
Information visualization is often portrayed as just one more arm of the data science octopus, a highly technical skill that is employed to help scientists and specialists with esoteric data sets navigate their enormous databases or noisy collection of .csv sheets. Amongst academics, there’s sometimes an impression that persuading or advocating with data visualizations is somehow beneath us, that this sort of deviation from “just” presenting…
I recently attended the IEEE VIS conference in Vancouver, BC. There were a lot of interesting and compelling talks, but of course my sunny and optimistic disposition kept returning to the same thought: “aha, this is the year when the wheels start coming off.”
What I mean by that is that academic visualization work is often situated within computer science (hence why our main conference is an IEEE conference, and most [but not all!] of our bigwigs are in computer science departments). But this allegiance is more or less just an accident of history. Sure, you need some computer science…
Do not knock — Technology is making gestures precise and brutal, and with them men. It expels from movements all hesitation, deliberation, civility.
— Theodor Adorno, “Do Not Knock,” Minima Moralia.
Context/ tl;dr : I was asked to give a keynote for the upcoming Workshop on Visualization for the Digital Humanities. I take keynote duty as an opportunity to make as provocative a point as possible. The particular Hot Take I’ve decided to go with is that visualization is a bad neighbor to the digital humanities: it exacerbates the worst tendencies of DH scholarship and promotes parasitic, technocratic collaborations. …
Academic Q&A sessions are, in theory, a good idea. When they work, they allow people to walk away with a deeper or even just more accurate representation of the speaker’s argument. They allow presenters to clarify things that may not have been communicated well in the talk. They hold presenters accountable for their claims. They can spark new ideas or new approaches by letting people engage with new perspectives. They allow groups that would otherwise be lost or absent from the debate to have their voices heard. …
Michael Correll
Information Visualization, Data Ethics, Graphical Perception.
