Dr. Hayley Hung is Associate Professor at the Technical University of Delft, working on Socially Aware Surveillance Systems. She leads the Perceptive Computing Lab, which is part of the Pattern Recognition and Bioinformatics Group.
Towards Enhancing Human Social Experience in the Wild
Humans interact with one another on a daily basis. Social bonding is a key component in human collaboration and with it, comes the possibility to achieve more as a group than as an individual. In today's society, one can consider social bonding to be important in relationships with a romantic partner, friends , and family or with professional colleagues. Studying how social interactions unfold and how these can affect or enhance social relationships taps into human's instinctive perception of the experience of social interactions. While the text above may sound like the start of a social science presentation, in this talk, I argue that in order to enhance the quality of human social experience where it could have the greatest benefit, we need an inherently interdisciplinary approach combining both social science and computer science. The drive for an interdisciplinary approach stems a lot from the idea that computational tools that could have the most impact for enhancing social experience must necessarily be embedded in people's everyday lives. Fortunately, with the rising popularity of wearable technologies, there is an opportunity to digitize momentary social experiences as they unfold in the real world.
However, when we step away from more restrictive social settings to cases where people are free to move around as they wish, most research (stemming from the ubiquitous and pervasive computing community ) have tended to apply proxies such as co-location as a measure of social interaction. This approach strips away the possibility of measuring interaction quality, pushing the research focus more towards larger scale sociological studies that try to find generalisable patterns of human behaviour and its relation with their affective experience. In this talk, I argue that human experience has an inherently personal component that should be explored if we want to close the loop on enhancing the quality of human social experience. This starts by first reconsidering traditional approaches to measuring human affective experience. Through examples from my prior work, I demonstrate that this provides intriguing new opportunities for investigating unconventional approaches to multimodal data processing which opens up a new field re-exploring phenomena from a machine perspective that goes beyond the commonly understood modalities of sight, and hearing.
I conclude the talk by discussing open opportunities regarding new directions of potential research on social experience monitoring and enhancement with respect to topics such as privacy, data labelling, personalisation, and multimodal experience enhancement.