# Considerations for Developing Robot-Assisted Crisis De-Escalation Practices
## 4 Integrating the De-Escalation Process into Human-Robot Interactions
### Actions to Support De-Escalation
#### 4.3.2 Non-Verbal Communication Principles  
Non-verbal communication principles that should be integrated throughout de-escalation interactions include the use of an appropriate tone of voice, appearing calm, engaging in slow and predictable movements, making appropriate, non-provocative eye contact, being non-threatening, maintaining appropriate personal space and physical positioning, exhibiting slow and simple pacing, showing congruence between words and actions, showing concern, and matching agitated individuals to reduce perceived power differentials. Robot tone of voice can be manipulated using features including volume, speaking speed, and pitch. The pacing of the de-escalation interaction can also be controlled using speaking speed along with the amount of speech. Studies examining the impact of tone of voice on the perception of robot personality suggest that humans are sensitive to these features and use them to attribute different characteristics to robots. For example, research indicates that robots who speak at a higher volume, with fast speed, higher and more varied pitch, and a larger amount of speech are typically perceived as being more extraverted e.g., [29; 30]. [PERSON] et al. [31] found that robot voice volume was negatively related to perceived friendliness. The de-escalation literature offers little insight into what specifically constitutes an appropriate tone of voice in the context of de-escalation. Presumably however, the tone of voice of crisis responders should be calm, empathic, warm, firm, and non-threatening. Future research could elucidate which configurations of a robot's tone of voice are most likely to be perceived as having these qualities. There is a large body of research on the gaze behaviour of robots (see [PERSON] and [PERSON] [32] for a review). First and foremost, design choices dictate the type of gaze behaviours of which robots are capable. Virtual agents (i.e., avatars) can allow for fine-tuned control over the appearance and timing of gaze behaviour, incorporating subtle eyelid, eyebrow, and eyeball movements. Such small and subtle movements are difficult to achieve with physical motors on embodied robots. Virtual agents can mimic human eye movements with greater precision than physical robots because they are animated; however, it should be noted that encoding realistic gaze behaviour is an ongoing area of research [33]. Furthermore, although devices such as the Furhat [34], with a rear-projected head-shaped projection surface, can provide a head-shaped avatar, it is unclear whether projected avatar displays are as effective as physical structures. Given that de-escalation invariably requires a physically embodied robot, designs merging embodied robots with virtual agents (e.g., a robot body with a screen displaying an avatar face) may enable more realistic gaze behaviour. Second, humans appear to respond differently to robot gaze than human gaze. A test of reflexive cueing (the tendency of humans to shift their attention in the direction of another person's averted gaze) found that robots failed to elicit this response in people, suggesting that humans process robot gaze more as directional arrows than as faces [32; 35]. Further, eye-tracking studies with infants have found that anticipatory eye gaze does not shift in response to a human-robot referential gaze as it typically does with humans [36]. Though humans may respond differently to robot gaze, research suggests that humans are sensitive to the interplay between their own gaze and a robot's gaze. Robots that convey joint attention and mutual gaze that is responsive to human interactional partners induce greater self-reports of the \"feeling of being looked at\" compared with robots with gaze behaviour that is unresponsive to and independent of humans' gaze [37, 38]. The context of human-robot interactions has been found to influence which type of gaze behaviour is best. When conversational topics are emotionally neutral, robots that make eye contact are perceived as more sociable and intelligent.