Conversation analysis of video from an office experiment with ten pairs of strangers. In each pair, one person searched in person while the other drove a telepresence robot from another room.
Ten pairsTwenty strangers aged 25 to 54, paired so that one was local and one remote.
Timed searchEach pair had three minutes to find five items each in offices, with the remote partner driving a Beam robot.
Robot condition onlyOnly the robot sessions of a larger experiment were analysed, at a global technology organisation's regional site.
Close analysisEvery attempt to get help was sorted by method and success, and selected moments were analysed turn by turn.
BWhat the study found
How remote pilots got helpways of recruiting assistance
•In these sessions, no remote pilot asked outright for help.Remote pilots reported trouble, such as saying 'I can't get round', or local partners anticipated it.
•Local partners often cleared obstacles before being asked.Local partners anticipated the robot's limits, for example by pulling a chair out of its path.
•Remote pilots also narrated trouble aloud without expecting help.Running commentary such as 'It's kinda slow backwards' is extra work that makes up for what the local partner cannot see.
What got in the waygaps in mobility and perception
•Getting around caused most of the trouble that led to help.The robot is slow, too bulky for narrow gaps and cannot move objects. The paper notes this can make remote users dependent on partners.
•In one case, a remote pilot's hint for help went unheard.With a narrow camera view and no sense of how loud she sounded, the pilot could not tell the hint had failed, so did not adjust it.
•Despite the robot's body, each side stayed unsure what the other could see and hear.Local partners asked 'can you hear me?' and raised a hand to be seen.
•The paper cautions that a timed experiment with strangers limits broad conclusions.In a rewarded task, helping was the obvious strategy. Colleagues who know each other might seek and give help differently.
CKey takeaway
Telepresence robot drivers can succeed at recruiting assistance by hinting at trouble, and local partners often step in unasked. Asymmetry in what each side can see, hear and do may leave hints unanswered.
Made for this site with AI assistance from the verified research brief. It is not the paper's own figure.
Abstract
Via audiovisual communications and a controllable physical embodiment, Mobile Robotic telePresence (MRP) systems aim to support enhanced collaboration between remote and local members of a given setting. But MRP systems also put the remote user in positions where they frequently rely on the help of local partners. Getting or ‘recruiting’ such help can be done with various verbal and embodied actions ranging in explicitness. In this paper, we look at how such recruitment occurs in video data drawn from an experiment where pairs of participants (one local, one remote) performed a timed searching task. We find a prevalence of implicit recruitment methods and outline obstacles to effective recruitment that emerge due to communicative asymmetries that are built into MRP design. In a future where remote work becomes widespread, assistance through remote work technology like MRPs needs close examination at a fundamental interactional level, taking into account how communicative asymmetries are at play in everyday use of such technologies.
Research brief
By Andriana Boudouraki, Joel E. Fischer, Stuart Reeves, and Sean Rintel.
Takeaway: People using telepresence robots often recruit help implicitly (voicing trouble or steering at an obstacle), and locals often clear the way unasked. But communicative asymmetries of mobility and perception can leave such hints unanswered, because remote users get little feedback on whether locals saw or heard them.
Why this matters
What was known
Conversation analysis has mapped how people recruit help face to face, and CSCW has studied communicative asymmetries in video, but how help is sought through mediating technologies had not been examined. (§1, p. 2)
What this paper adds
We apply a framework built for face-to-face help-seeking (Kendrick and Drew's continuum from explicit requests to troubles others anticipate) to moment-by-moment video of robot-mediated collaboration. We also catalogue the asymmetries that get in its way. (§1, p. 2)
Who it matters to
Designers of telepresence systems, the CSCW research community, and workplaces where some colleagues join remotely. there is scope for wide-ranging changes to reduce the impact of asymmetries for MRP users(§6, pp. 19–20)
Research questions
Given these issues, what do we need to know about recruiting assistance, from its practical methods to its micropolitics, to enable an effective and inclusive workplace?
How do remote users of mobile robotic telepresence recruit assistance from local participants, and how is this shaped by the asymmetries introduced by the medium?
Method and data
Design
Ethnomethodological and conversation-analytic study of video from a within-subjects experiment. Only the MRP condition of a timed search task is analysed. Each pair had one local participant in person and one remote participant on a Beam MRP.
Setting
Offices at a regional site of a global technology organisation. An experimenter was present with the robot.
Participants / data
Ten pairs of participants (aged 25-54, eight female and twelve male). None of the pair members knew each other beforehand.
Duration
Three minutes per pair to find five items each.
Analysis
All instances of assistance recruitment were isolated and categorised by success and by Kendrick and Drew's methods (with new categories such as status reporting). Selected fragments were analysed in detail.
Findings
Nobody asked outright. Ten pairs of strangers did a timed search of an office, one in person and one driving a telepresence robot from another room. The remote pilots got help by reporting trouble ('I can't get round'), or their partners anticipated it. Nobody explicitly asked for help. #
(§5.4, pp. 17–18)
Partners helped before being asked. Local partners often anticipated the robot's limits, such as an obstacle in its path, and dealt with them in advance, for example by pulling a chair out of the way. #
(§5.4, p. 18)
Getting around caused most trouble. Most of the trouble that led to help came from moving around, because the robot is slow, too bulky for narrow gaps, and cannot move objects out of its way. #
“This may be seen to create a dependency for the remote user, perhaps creating an awkward dynamic for the dyads, especially for participants simply not very familiar with each other.”
Hints went unheard. In one case, a remote pilot had a narrow camera view and no sense of how loud she sounded. She could not tell whether her partner had heard her hint, so she did not adjust it, and the attempt to get help failed. #
(§5.2, p. 16)
Narrating trouble without asking. Remote pilots also voiced troubles as running commentary ('It's kinda slow backwards') without expecting help. This is extra work that makes up for what the other person cannot see. #
(§4.3, p. 13)
A body did not close the gaps. Although the robot gave remote participants a physical presence they could turn and drive, each side stayed unsure of what the other could see and hear. Locals asked 'can you hear me?' and raised a hand to be seen. #
“But our findings show that asymmetries nevertheless stubbornly persist in MRP.”
Questions this paper answers
How do people using telepresence robots ask for help?
Mostly indirectly. People driving a robot remotely described the trouble ('I can't get round') or drove toward the obstacle rather than asking. That left their partner to work out a fix, and partners often stepped in before anything was said. (See §5.4, pp. 17–18; §5.4, p. 18.)
Why do telepresence robot users sometimes fail to get help?
Because the person driving the robot sees and hears the room only partially and gets no feedback on how they come across. A hint for help could go unheard without the driver knowing, so they did not adjust it, and some attempts simply failed. (See §5.2, p. 16; p. 15.)
Do people hint at problems instead of asking for help just to be polite?
Not only, we argue. Politeness theory says hinting spares both helper and helped from losing face. But remote robot users showed no sign of embarrassment. Their indirectness may instead reflect gaps in what each could see and hear, or a low sense of entitlement. More evidence is needed. (See §5.4, pp. 17–18; §5.2, p. 16; p. 15.)
Do telepresence robots put remote workers on an equal footing with people in the office?
Not yet. Even with a body they could drive, remote users depended on local partners to get around. Each side stayed unsure what the other could see and hear. These asymmetries persisted despite the robot's physical presence. (See §5.1, p. 15; p. 15.)
Contributions and implications
Reduce asymmetries through better MRP features, information for people near the robot, etiquette campaigns, workaround tutorials and conduct guidelines.
Consider the micropolitics of help, so that being helped does not harm remote workers' standing. care should be taken, not only to ensure that remote workers can receive help, but also that doing so does not harm their position(§6, pp. 19–20)
Repeated unsolicited help may become patronising in long-term collaborations. sustained incidents of unsolicited help such as this in long-term collaborations may be heard as patronising(§4.2, p. 11)
Assistance should be considered before MRPs are recommended for equitable remote work. before MRP can be whole-heartedly recommended as a solution for equitable remote working(§5.5, p. 18)
Limitations
An experimental, timed, rewarded task with an experimenter present, which made helping each other the obvious strategy. The experimental situation in which our data was produced cautions us against drawing broad conclusions.(§5.5, p. 18)
Pairs were strangers. Colleagues who know each other might recruit and give help differently. Colleagues who work together regularly, know each other better, and are motivated to maintain a good relationship might have used different strategies(§5.6, p. 19)
Asymmetries may partly depend on users' familiarity with the MRP. Interpersonal and cultural factors were out of scope. the observed asymmetries might be to some degree situational, depending on the users' familiarity with the MRP(§5.6, p. 19)
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Concepts
Mobile Robotic telePresence (MRP)
The technology studied, piloted by a remote user from a computer or smartphone: MRPs generally consist of a video conferencing system mounted on a remotely-controlled mobile base.(§1, p. 1)
Recruitment of assistance
Kendrick and Drew's term, with forms ranging on a continuum from explicit requests through reports of trouble, alerts and embodied displays to projectable troubles. It covers: how people recruit others to assist them in their courses of action using a variety of linguistic and embodied actions(§1, p. 2)
Communicative asymmetry
Imbalances in what each party can see, hear and do because they take part through different media. Heath and Luff's example from video calls: gazing at a co-located person will usually get their attention, but this does not happen in video resulting in the person staring at their intended co-participant without result(§2.2, p. 4)
Compensation work
From earlier CSCW work: extra work people do to cover gaps caused by asymmetries, such as narrating their own actions and limitations. (§2.2, p. 4)
How to cite
Andriana Boudouraki, Joel E. Fischer, Stuart Reeves, and Sean Rintel. 2020. “I can’t get round”: Recruiting Assistance in Mobile Robotic Telepresence. CSCW 2020. https://doi.org/10.1145/3432947
This brief was prepared with AI assistance and published by Sean Rintel. It is not the authors' published text. Page numbers refer to this PDF.
BibTeX
@inproceedings{boudouraki2020i,
author = {Boudouraki, Andriana and Fischer, Joel E. and Reeves, Stuart and Rintel, Sean},
title = {“I can’t get round”: Recruiting Assistance in Mobile Robotic Telepresence},
organization = {ACM},
booktitle = {CSCW 2020},
year = {2020},
month = {August},
url = {https://doi.org/10.1145/3432947},
doi = {10.1145/3432947},
}