Toward Artificial Empathy for Human-Centered Design: A Framework

• URL: http://arxiv.org/abs/2303.10583v2
• Date: Sat, 13 May 2023 05:47:16 GMT
• Title: Toward Artificial Empathy for Human-Centered Design: A Framework
• Authors: Qihao Zhu and Jianxi Luo
• Abstract summary: This paper provides insights from artificial intelligence research to indicate the future direction of AI-driven human-centered design. We discuss the role that artificial empathy can play in human-centered design and propose an artificial empathy framework for human-centered design.
• Score: 7.807713821263175
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: In the early stages of the design process, designers explore opportunities by discovering unmet needs and developing innovative concepts as potential solutions. From a human-centered design perspective, designers must develop empathy with people to truly understand their needs. However, developing empathy is a complex and subjective process that relies heavily on the designer's empathic capability. Therefore, the development of empathic understanding is intuitive, and the discovery of underlying needs is often serendipitous. This paper aims to provide insights from artificial intelligence research to indicate the future direction of AI-driven human-centered design, taking into account the essential role of empathy. Specifically, we conduct an interdisciplinary investigation of research areas such as data-driven user studies, empathic understanding development, and artificial empathy. Based on this foundation, we discuss the role that artificial empathy can play in human-centered design and propose an artificial empathy framework for human-centered design. Building on the mechanisms behind empathy and insights from empathic design research, the framework aims to break down the rather complex and subjective concept of empathy into components and modules that can potentially be modeled computationally. Furthermore, we discuss the expected benefits of developing such systems and identify current research gaps to encourage future research efforts.

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