# Singing the Body Electric: The Impact of Robot Embodiment on User Expectations

arXiv: https://arxiv.org/abs/2401.06977 · HTML: https://mlsanity.com/paper/2401.06977/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 8 of its 31 references that are in the map.
- First posted on arXiv 13 Jan 2024.

## Builds on (most cited first, 8 of 8)

- [Aligning Books and Movies: Towards Story-like Visual Explanations by Watching Movies and Reading Books](https://mlsanity.com/paper/1506.06724/) (2015)
- [Deep Reinforcement Learning at the Edge of the Statistical Precipice](https://mlsanity.com/paper/2108.13264/) (2021)
- [Experience Grounds Language](https://mlsanity.com/paper/2004.10151/) (2020)
- [Conceptual Metaphors Impact Perceptions of Human-AI Collaboration](https://mlsanity.com/paper/2008.02311/) (2020)
- [Introducing Representations of Facial Affect in Automated Multimodal Deception Detection](https://mlsanity.com/paper/2008.13369/) (2020)
- [Four Years in Review: Statistical Practices of Likert Scales in Human-Robot Interaction Studies](https://mlsanity.com/paper/2001.03231/) (2020)
- [Embodiment in Socially Interactive Robots](https://mlsanity.com/paper/1912.00312/) (2019)
- [Using Design Metaphors to Understand User Expectations of Socially Interactive Robot Embodiments](https://mlsanity.com/paper/2201.10671/) (2022)

## Abstract (arXiv)

Users develop mental models of robots to conceptualize what kind of interactions they can have with those robots. The conceptualizations are often formed before interactions with the robot and are based only on observing the robot's physical design. As a result, understanding conceptualizations formed from physical design is necessary to understand how users intend to interact with the robot. We propose to use multimodal features of robot embodiments to predict what kinds of expectations users will have about a given robot's social and physical capabilities. We show that using such features provides information about general mental models of the robots that generalize across socially interactive robots. We describe how these models can be incorporated into interaction design and physical design for researchers working with socially interactive robots.