I'm new to the CHI community, and have been involved with only one project that submitted a paper to CHI. I was struck by the cadence - it's a once-per-year submission deadline that sets the pattern of activity for an entire research lab. That feels weird. Maybe it's good, though, as it pushes people to publish their work on a regular basis rather than just at the end of a thesis or dissertation projectā¦
This hurt. A lot. The scores showed this submission was the weakest academically of the 97 NSERC applications written by UCalgary PhD students, according to the committee. Ouch. It also scored very poorly for āresearchā ā but scored well for āinterpersonalā. So, Ms. Congeniality. Awesome. I, like, totally am all about world peace and junk.
I think the results show a couple of things.
So. Next year, Iāll try for SSHRC funding for part of my refined research plan, rather than just pushing an existing project.
A crazy/deep overview of some of the amazing developments in machine learning in the last couple of years, especially as a medium for artistic expression and exploration.
This last year I've been getting back into machine learning and AI, rediscovering the things that drew me to it in the first place. I'm still in the "learning" and "small studies" phase that naturally precedes crafting any new artwork, and I wanted to share some of that process here. This is a fairly linear record of my path, but my hope is that this post is modular enough that anyone interested in a specific part can skip ahead and find something that gets them excited, too. I'll cover some experiments with these general topics:
We've been adapting to life in a shared, open workspace environment. Most of us in the Taylor Institute are in pods, trying to balance productivity, collaboration, distractions, competing demands for attention. It's hard to describe what it's like, but it adds overhead on top of everything. Quincy describes it well, from the perspective of s programmer, but I think it applies to the rest of us as well.
Let's talk a bit about how us humans get work done. Is it four hours of crushing it, a lunch break, then four more hours of crushing it? No. It's more like coffee, email, coffee, meeting, coffee, lunch with coworkers, coffee — OK finally time to get some work done!
via BoingBoing, this video of a presentation by Genevieve Bell from Intel at O’Reilly’s AI Conference, on how to engage the concept of AI from an anthropological and ethnographic framework.
I don’t think of AI as trying to invent an artificial human, but it’s extremely important to think about the cultural, moral, racial, and gender biases that get baked into code through histories of projects.
This is cool. Christian's lab has been producing some amazing tech for visualizing and interacting with human and cellular anatomy, including LINDSAY Virtual Human, and now this:
Christian Jacob and Markus Santoso are trying to re-create the experience of the aforementioned agents in Fantastic Voyage. Working with 3D modelling company Zygote, they and recent MSc graduate Douglas Yuen have created HoloCell, an educational software. Using Microsoft's revolutionary HoloLens AR glasses, HoloCell provides a mixed reality experience allowing users to explore a 3D simulation of the inner workings, organelles, and molecules of a healthy human cell.Jacob has plenty of experience in bioinformatics as the head of the Lindsay Virtual Human Project.
University Affairs article on active learning classrooms, with a bit about Michael Ullyot's Shakespeare course in the Taylor Institute:
He's taught courses in a similar way in regular classrooms using workarounds to deal with obstacles such stationary chairs and more rudimentary technology. "You can do this in just about any classroom, you just need enough imagination," he says, adding one stipulation: "If I had a banked lecture hall, this would not work."
I'm in the third week of a PhD program, and have had to make some adjustments to how I do things in order to be able to concentrate and actually think. I was struck by my inability to read a full paragraph without switching over to check email/calendar/twitter/slack/facebook/whatever. Mostly email and twitter.
I'm basically living in digital content - everything I do is in OneNote and Outlook, synced to every device I use. My email and calendar basically organize my day. There are people in there.
Are teacher/performer & student/audience synonymous?
(How) are all of these data + interpretations to be used to shape the current experience and future ones?
(How) can these be generalized to other contexts?
So what? Why is this useful? ā Not just scholarly navel-gazing?!
How do these support meaningful + productive reflection by instructors and students?
