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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