Model Multiplicity in Interactive Software Systems
We got a workshop paper accepted, presenting the initial work of Gilles Eerlings et al. We explore how model multiplicity can be a potential answer to reduce overtrust in AI, as well as avoid undertrust. Still a lot of work that lies ahead, but this seems like a promising direction.
Citation
@inproceedings{luyteneerlings-modelmultiplicity2024,
author = {Kris Luyten and Gilles Eerlings and Jori Liesenborgs and Gustavo {Rovelo Ruiz} and Sebe Vanbrabant and Davy Vanacken},
title = {Opportunities and Challenges of Model Multiplicity in Interactive Software Systems},
booktitle = {The Second Workshop on Engineering Interactive Systems Embedding AI Technologies},
year = {2024}
}
Abstract
The proliferation of artificial intelligence (AI) in interactive systems has led to significant challenges in model integration, but also end-user-related aspects such as over- and undertrust. This paper explores how multiple AI models with the same performance and behavior but different internal workings—a phenomenon called model multiplicity—affect system integration and user interaction. We discuss the implications of model multiplicity for transparency, trust, and operational effectiveness in interactive software systems.
Anthropomorphic User Interfaces
Together with Eva Geurts, we explored anthropomorphic UIs and more specifically a taxonomy that helps us to analyze, identify, and design appropriate AUIs. This is becoming more and more a concern given the way AI is being presented to humans nowadays, often adding too many and misleading anthropomorphic features.
Citation
@inproceedings{geurts-antropomorphic2024,
title={Anthropomorphic User Interfaces: Past, Present and Future of Anthropomorphic Aspects for Sustainable Digital Interface Design},
booktitle={ECCE 2024: European Conference on Cognitive Ergonomics},
author={Eva Geurts and Kris Luyten},
pubstate= {inpress},
year={2024},
url={https://www.ecce2024.telecom-paris.fr/organization}
}
Abstract
Interactions with computing systems and conversational services such as ChatGPT have become an inherent part of our daily lives. It is surprising that user interfaces, the gateways through which we communicate with an interactive intelligent system, are still predominantly devoid of hedonic aspects. There is little attempt to make communication through user interfaces intentionally more like communication with humans. Anthropomorphic user interfaces can transform interactions with intelligent software into more pleasant experiences by integrating human-like attributes. Anthropomorphic user interfaces expose human-like attributes that enable people to perceive, connect, and interact with the interfaces as social actors. This integration of human-like aspects not only enhances user experience but also holds the potential to make interfaces more sustainable, as they rely on familiar human interaction patterns, thus potentially reducing the learning curve and increasing user adoption rates. However, there is little consensus on how to build these anthropomorphic user interfaces. We conducted an extensive literature review on existing anthropomorphic user interfaces for software systems (past), in order to map and connect existing definitions and interpretations in an overarching taxonomy (present). The taxonomy is used to organize and structure examples of anthropomorphic user interfaces into an accessible collection. The taxonomy and an accompanying web tool provide designers with a reference framework for analyzing and dissecting existing anthropomorphic user interfaces, and for designing new anthropomorphic user interfaces (future).
