This year at CHI 2022 we (my awesome Data Cloud Research Teammates and I) presented a case study in the technical program and participated in a workshop.
Our Case Study
Our case study is titled: The BLUE Framework: Designing User-Centered In-Product Feedback for Large-Scale Applications. Within the case study, we describe our process and lessons learned. In the end, we present a framework that aims to assist others in navigating a similar objective. Big shout out to my colleague Samira Jain who presented the work at CHI.
Here’s the 8-minute overview of the talk: The BLUE Framework: Designing User-Centered In-Product Feedback for Large Scale Applications – YouTube
For more details check out the full paper here: The BLUE Framework: Designing User-Centered In-Product Feedback for Large Scale Applications | CHI Conference on Human Factors in Computing Systems Extended Abstracts (acm.org)
Collaborating with a colleague we also submitted a workshop position paper to attend the Dreaming Disability Justice Workshop. Here’s the position paper we submitted.
The workshop was an excellent opportunity for me to personally just listen and learn. Specifically, I enjoyed the intro of the workshop that reviewed the History of Disability Justice and the reflection on intersectionality. I believe the final count for the workshop was around ~45 attendees. This was a bit shocking to me as in the past the workshops I have attended at CHI are usually around a dozen participants. Kudos to the organizers!!!
After the Workshop, the discussion was continued into sessions at CHI, where I was able to attend the session: Social Justice – Towards a collective manifesto. This session along with the workshop was inspirational. Some key takeaways that really resonated with me and I look forward to noodling over within our research team were:
- We need to normalize repeat work with new audiences, not dismiss them as unnecessary for pub.
- It is conceded for us to think we can save these communities, and bring social justice into our fields. Less about how we save the work, more about how we can save ourselves.
- We must not study down. How do we connect and learn from these communities?
- Resist the urge to just get stuff out there and see what breaks because it breaks for the same people every time.
- We are training future researchers, what are we teaching in HCI? Trauma-informed? Social justice-focused?
My top 5 CHI-lights:
Here are a few sessions that really took me back, in terms of quality, message, and overall insightfulness.
- Black Feminist and Transformative Justice approach to online harassment
- I particularly enjoyed the thoughtfulness of the methodology presented in the paper, it really went beyond identifying insight around unwanted behavior and harassment of Black women online, but also focused on how they can (re)claim their experiences to cope, heal, and experience joy <3. The positivity and community approach were particularly strong and inspiring. Here is the recorded video for this paper: Experiences of Harm, Healing, and Joy among Black Women and Femmes on Social Media – YouTube
- Supporting Accessible data visualization through audio data narratives
- Coming into the conference I had no experience with audio data narratives. In general, I just really enjoyed learning that this is a thing and how sonification is used to convey data narratives. Here is the recorded video for this paper: Supporting Accessible Data Visualization Through Audio Data Narratives – YouTube
- Building a community of practice (CoP) with Bloomberg UX
- The Bloomberg UX team did a nice job presenting Community of Practice ideas and lessons learned during their CoP session, providing practical initiatives teams could try out. I also appreciated the representation around different levels of tenure, including not just veteran staff on the panel but also those that just joined Bloomberg in the last month. I felt this brought an interesting lens to the discussion. There is no public video of the session, so here is a quick recap of some of the ideas teams could try out to build a CoP: training series, weekly research training, sharing conference takeaways (like this blog post), weekly book club, and dives into team members’ specializations to train and teach each other. Their objective with the CoP of making research a company thing vs a design thing was also super relatable.
- VisGuide: User Orientated Recommendations for Data Event Extraction
- The authors look at supporting a smooth and continuous exploration of data and satisfying the users’ preferences to gain meaning from the data. The idea of visualizing the data exploration process through a step-by-step recommendations engine came off as novel and an interesting topic to explore further. Here is the recorded video for this paper: VisGuide: User-oriented Recommendations for Data Event Extraction – YouTube
Hopefully, I’ll see you in Germany, where I will swap out this old-timey barbershop hat for some lederhosen.