Abstract
AI systems are increasingly being adopted across various domains and application areas. With this surge, there is a growing research focus and societal concern for actively involving humans in developing, operating, and adopting these systems. Despite this concern, most existing literature on AI and Human–Computer Interaction (HCI) primarily focuses on explaining how AI systems operate and, at times, allowing users to contest AI decisions. Existing studies often overlook more impactful forms of user interaction with AI systems, such as giving users agency beyond contestability and enabling them to adapt and even co-design the AI’s internal mechanics. In this survey, we aim to bridge this gap by reviewing the state-of-the-art in Human-Centered AI literature, the domain where AI and HCI studies converge, extending past Explainable and Contestable AI, delving into the Interactive AI and beyond. Our analysis contributes to shaping the trajectory of future Interactive AI design and advocates for a more user-centric approach that provides users with greater agency, fostering not only their understanding of AI’s workings but also their active engagement in its development and evolution.
| Original language | English |
|---|---|
| Article number | 103301 |
| Number of pages | 20 |
| Journal | International journal of human-computer studies |
| Volume | 189 |
| Early online date | 23 May 2024 |
| DOIs | |
| Publication status | Published - Sept 2024 |
Bibliographical note
Publisher Copyright:© 2024 Elsevier Ltd
Funding
We would like to extend our gratitude to our colleagues at Sappi, Markie Janse van Rensburg, and Marjorie Boles for their continued support in the context of the Sappi-RIT Digital Innovation Lab at Golisano College of Computing and Information Sciences, RIT. Any explanations, findings, or conclusions expressed in this work are those of the authors and do not necessarily reflect the views of Sappi.
| Funders |
|---|
| Sappi-RIT Digital Innovation Lab |
| Golisano College of Computing and Information Sciences, Rochester Institute of Technology |
| Rochester Institute of Technology |
Keywords
- Collaboration
- Explainability
- Human-centered AI
- Interactivity
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