Emotions are complex. They are not feelings nor are they desires. I’ll define emotions as a biopsychological process that happens inside the body and is an information-processing tool. I heard emotions being opposed to rationality—by some coincidence, pretty often in a sexist logic. But it’s quite the opposite, and emotions matter in effective decision-making. The way interactive interfaces, data visualizations, and other design systems that surround us are constructed may influence our emotional experience and processing. The ability to meaningfully experience data visualizations through emotional feedback enhances engagement.
In a design context, how we reflect on our emotional experiences can vary depending on the system architecture. That matters because we are surrounded by interactive systems, from AI-based digital products to newsroom data visualizations and train ticket machines. This is why the framework for constructing design systems that fascinates me is affective computing, a discipline researching how emotions can be detected and responded to by interactive systems. Currently, techniques such as emotion recognition via audio, speech and physiological data as well as sentiment analysis of textual evaluations and opinion mining are used to get this information. But is this factual data enough to effectively and empathetically evaluate the meaning of communication? Boehner and colleagues wrote that there are a lot of caveats to interpreting emotions, such as limitations of the given evaluation method. This means that the methods of factual evaluation should be combined with cultural understanding and nuanced assessment.