Abstract
Neurotechnology promises cognitive enhancement as a way for humanity to extend its information-processing capability without invasive brain surgeries and pharmacological side effects. Notable advancements in this field have achieved high-bandwidth wireless communication interfaces between human brains and computers. Human-centered design proposes that human-technology experiences should focus on human needs. This paper explains how design thinking has been applied as a methodology to design the user experience of an attention-based neurotechnology solution that leverages artificial intelligence (AI) to enhance the flow performance and cognitive well-being of knowledge workers (KWs). Using the d.school design thinking process, we started with a mindset that favored empathy, creative confidence, and ambiguity to discover and define the problems confronting KWs. After diverging with deep empathy and converging on user personas and problem definition, the design thinking process branched into an iterative prototyping cycle that transformed our initial ideas into a human-centered AI-powered neurotechnology. We utilized the functional prototypes for testing assumptions and performing a comprehensive design evaluation. Our final solution incorporated a gamified user interface with visual elements, affordances, and a coherent human-AI experience. Expert software evaluators conducted a series of cognitive walkthroughs and heuristic evaluations by simulating the user personas and performing an end-to-end user scenario with the prototype. The design thinking process generated a neurotechnology service with a human-AI experience that enables KWs to achieve healthy flow performance while enhancing cognitive well-being.
Supported by L3 Harris Institute for Assured Information.
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Weekes, T.R., Eskridge, T.C. (2022). Design Thinking the Human-AI Experience of Neurotechnology for Knowledge Workers. In: Kurosu, M., et al. HCI International 2022 - Late Breaking Papers. Multimodality in Advanced Interaction Environments. HCII 2022. Lecture Notes in Computer Science, vol 13519. Springer, Cham. https://doi.org/10.1007/978-3-031-17618-0_37
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