Author: Cynthia C. S. Liem
Editors: Cynthia C. S. Liem, Jochen Huber
In 2018, while on a research visit to Bordeaux, I felt it would be good to connect more closely to the local community. As a consequence, colleagues convinced me to join the Femmes & Sciences movement, in which women researchers in STEM proactively did local outreach.
My French was conversational, though not stellar. But I thought it hopefully should be good enough to converse with young teenagers. Furthermore, as for ‘local community’, it would be a nice idea to both get to know colleagues and the culture of the local schools. So there I went, speaking at a countryside school in one of the many wine regions, and at a secondary school in Bordeaux where students would not trivially think of STEM university careers.
It was an amazing and enlightening experience. As soon as I started to talk about search engines, recommender systems, music and video services, a spark really ignited in the students. They knew these, and they used them daily!
But it only was because of me mentioning it, that they started realizing there was computer science technology behind all these services. Before, they had no clue.
And I think this is a real problem, that we as a community severely undervalue.
In my own family, my father (electrical engineering), sister (civil engineering & geomatics) and I (computer science) studied to become engineers. For the rest of my family, this meant we were ‘the technical people’, getting called in when computers were slow, cell phones were updated and printers started malfunctioning. This especially happened to my father and me, as we ‘were good with computers, since that was our profession’.
But I had not studied to fix printers. And, as I joked during university open days to prospective students, my sister never got asked to go fix the kitchen sink, even though she had been taught about water management.
It always has been striking to me how malfunctioning hardware and software were the first associations that laypeople outside of our field seemed to have with our work. Today, this is broadening to fears of hacking, and on the less negative side, (overblown?) hopes in AI and cryptocurrency. In all these cases, the technology is something alien, something that ‘normal’ humans do not understand and grasp well.
Yet at the same time, the technologies we build affect everyone’s lives, increasingly so. Frequently, they silently work in the back, and we indeed only visibly notice them if something goes wrong. But then, rather strange associations and dialogues emerge.
Recently, I became a member of the national Young Academy, a body of earlier-career faculty across disciplines in The Netherlands, playing a public opinion-making role on academic culture, the image of academia and its findings, and associated policy-making. Through this role, and with my background in search and recommendation, I am increasingly being invited into committees, workshops and other forms of public appearances, that involve policy-makers and laypeople concerned with the impact of AI technologies (especially: possible exclusion of humans, as a consequence of the use of AI technologies).
In these activities, it has again been striking to me how little common vocabulary is present, and how questions thus get formulated awkwardly. More than once, I get asked ‘what the algorithm exactly is doing’, when my discussion partners actually refer to broader decision-making processes, where problems may occur across the pipeline, also already before any algorithm would be deployed.
When I try to explain that much of the applications of interest focus on prioritization with a cutoff within a larger collection, and I ask how my discussion partners would prioritize, I get blank stares if I keep this story at the current, general, abstract level that would come naturally to me as a computer scientist. If I’m unlucky, I may even get an answer back that my discussion partners don’t want to take a stance themselves, as it is ‘difficult and subjective’ matter, but ‘surely AI can do this better than we humans?’. Now that will form a problem if we will frame the problem in a supervised learning setup, without a sense of solid ground truth or criteria to optimize for.
However, going through simple, concrete examples ‘close to home’ does seem to help. Here, I really benefited from the experience I had learnt while in Bordeaux and beyond, especially in setups where I had to work with children.
Try to explain concepts of information retrieval and data modelling in a non-native tongue to a 12-year old, and you are forced to ask simple questions, that will give insight into these children’s own world views and contexts. It will give them building blocks they recognize and can build on.
Working in music and multimedia has greatly helped me here; as said before, everyone is a heavy daily user of music and multimedia services, and thus (without explicitly knowing) actually has some world view ready on preferences, priorities and ways to navigate larger information collections. This will greatly help as a discussion starter, with the discussion elements remaining tangible for everyone.
I would argue that working on a better public understanding of our work is among the most societally impactful roles that we, as researchers in the field, can play. Our discussion partners are stakeholders who don’t realize they are stakeholders. And of course, in the case of children, they may at the same time be the future technologists, who in the future will build forth on our work.
It takes serious time investment and a lot of practice to get this right. I have always been puzzled at how this typically meant this would be considered too much of a time sink, and not our prime responsibility as academics. But who else would otherwise take this up?
And if I think of how much time I have been encouraged to sink into endlessly rewriting grant proposals or papers at the micro-level, just to hopefully please reviewers, something does not feel right. Any acceptances following this have arguably been good for my career. But I am not quite convinced this has been more meaningful use of the public money my contract is funded from.
Or, in a more positive interpretation: in our community, we actually care about communicating well, and are clearly willing to invest in it. But so far, we really have been focusing our attention inward, while there is a lot to gain when we’d rather look outward.
So for those who would be interested in engaging more with those outsides of our field: please do. Outreach is much more than cute PR. And with the applications that we work on being so close to people’s daily lives, we in music/multimedia hold some very important keys, and really should learn the perspectives of our end users.
So let’s use those keys, and finally, get some doors opened that have remained shut for too long.
Dr. Cynthia C. S. Liem is an Associate Professor in the Multimedia Computing Group of Delft University of Technology, The Netherlands, and pianist of the Magma Duo. Her research interests focus on making people discover new interests and content which would not trivially be retrieved, and assessing questions of validation and validity, especially in the context of music and multimedia search and recommendation. She initiated and co-coordinated the European research projects PHENICX (2013-2016) and TROMPA (2018-2021), focusing on technological enrichment of digital musical heritage, and gained industrial experience at Bell Labs Netherlands, Philips Research and Google. She was a recipient of the Lucent Global Science and Google Anita Borg Europe Memorial scholarships, the Google European Doctoral Fellowship 2010 in Multimedia, a finalist of the New Scientist Science Talent Award 2016 for young scientists committed to public outreach, and is a member of the Dutch national Young Academy.
Dr. Jochen Huber is Professor of Computer Science at Furtwangen University, Germany. Previously, he was a Senior User Experience Researcher with Synaptics and an SUTD-MIT postdoctoral fellow in the Fluid Interfaces Group at MIT Media Lab and the Augmented Human Lab at Singapore University of Technology and Design. He holds a Ph.D. in Computer Science and degrees in both Mathematics (Dipl.-Math.) and Computer Science (Dipl.-Inform.), all from Technische Universität Darmstadt, Germany. Jochen’s work is situated at the intersection of Human-Computer Interaction and Human Augmentation. He designs, implements and studies novel input technology in the areas of mobile, tangible & non-visual interaction, automotive UX and assistive augmentation. He has co-authored over 60 academic publications and regularly serves as program committee member in premier HCI and multimedia conferences. He was program co-chair of ACM TVX 2016 and Augmented Human 2015 and chaired tracks of ACM Multimedia, ACM Creativity and Cognition and ACM International Conference on Interface Surfaces and Spaces, as well as numerous workshops at ACM CHI and IUI. Further information can be found on his personal homepage: http://jochenhuber.com