Personas for Artificial Intelligence (AI) an Open Source Toolbox

作者：Andreas Holzinger, Michaela Kargl, Bettina Kipperer, Peter J. Regitnig, Markus Plass, Heimo Müller · 发表于：IEEE Access · 年份：2022 · DOI：10.1109/access.2022.3154776 · 被引用次数：96 · 研究领域：Persona Design and Applications、Innovative Human-Technology Interaction、Technology Use by Older Adults

Personas have successfully supported the development of classical user interfaces for more than two decades by mapping users’ mental models to specific contexts. The rapid proliferation of Artificial Intelligence (AI) applications makes it necessary to create new approaches for future human-AI interfaces. Human-AI interfaces differ from classical human-computer interfaces in many ways, such as gaining some degree of human-like cognitive, self-executing, and self-adaptive capabilities and autonomy, and generating unexpected outputs that require non-deterministic interactions. Moreover, the most successful AI approaches are so-called “black box” systems, where the technology and the machine learning process are opaque to the user and the AI output is far not intuitive. This work shows how the personas method can be adapted to support the development of human-centered AI applications, and we demonstrate this on the example of a medical context. This work is - to our knowledge - the first to provide personas for AI using an openly availablePersonas for AI toolbox. The toolbox contains guidelines and material supporting persona development for AI as well as templates and pictures for persona visualisation. It is ready to use and freely available to the international research and development community. Additionally, an example from medical AI is provided as a best practice use case. This work is intended to help foster the development of novel human-AI interfaces that will be urgen...