Personas for AI

Personas have been successful for over two decades in supporting the development of classic user interfaces by mapping users' mental models to specific contexts. You can find more information about the personas method in ^[Nielsen].

However, 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, e.g., in that they acquire some degree of human-like cognitive, self-executing, and self-adaptive capabilities and autonomy, and generate unexpected outputs, requiring interactions that are non-deterministic. Furthermore, the most successful AI approaches are so-called "black-box" systems, where the technology and machine learning process are opaque to the user and the AI output is non-intuitive. Thus, when it comes to AI applications, often causability ^[1] is added to the users' needs: Specifically in high-stake domains, such as for example in medicine, users need to understand the rationale and certainty underlying the results delivered by an AI application. Therefore, in order to achieve useful AI solutions with high usability and causability, it is essential that AI applications are designed and developed with the users in mind (human-centered AI). To support such human-centered design and development of AI applications and to help foster the development of novel human-AI interfaces that will be urgently needed in the future, we provide this open available "Personas for AI toolbox".

About this Repository

In this repository we describe our approach for user persona development to support human-centered design and development of AI applications. Furthermore, based on our experience from practical implementation of the personas development process, we have created free material and tools to facilitate development of user personas for AI.

This repository "Personas for AI" contains:

A detailed step-by-step guide for developing personas for AI with clear descriptions of the recommended methods and practical hints for implementation.
Illustrative practical examples from the field of Digital Pathology.
Ready-to-use templates for visualising personas in LaTeX and MS PowerPoint.
A large set of pictures of faces, which can be used freely for persona visualisation.
RedCap questionnaire templates, which can easily be customised for collection of user information in different application fields of AI.

License

All material is made available under Creative Commons BY-NC 4.0 license by Human-Centered AI Lab / Research and Diagnostics Institute of Pathology at Medical University Graz. You can use, redistribute, and adapt the material for non-commercial purposes, as long as you give appropriate credit by citing our paper: A. Holzinger, M. Kargl, B. Kipperer, P. Regitnig, M. Plass and H. Müller, "Personas for Artificial Intelligence (AI) an Open Source Toolbox", in IEEE Access, vol. 10, pp. 23732-23747, 2022, doi: 10.1109/ACCESS.2022.3154776.

Acknowledgements

Parts of this work have received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No. 857122 (CY-Biobank), No. 824087 (EOSC-Life) and No. 874662 (HEAP). This publication reflects only the authors' view and the European Commission is not responsible for any use that may be made of the information it contains.

Parts of this work have received funding from the Austrian Research Promotion Agency (FFG) under grant agreement No. 879881 (EMPAIA) and by the Austrian Science Fund (FWF), Project: P-32554 explainable Artificial Intelligence.

human-centered-ai-lab/PERSONAS

Personas for AI

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