Welcome to the overview of our paper Investigating the Limits and Effectiveness
of Privacy Conversations, the Case of Service Robots in an Office Environment.
Robots move through space autonomously and are equipped with sensors that capture data.
This may raise privacy concerns among their users and privacy
conversations have been proposed as a means to address such concerns.
Here, we examine the potential of such privacy conversations.
We carried out an online study where we put participants in the situation
of a new employee in a company where service robots are deployed.
The scenario was introduced to the participants through text and video as you can see here.
In this video you see RobInc, your new workplace.
Mobile autonomous robots provide services to employees
like delivering coffee and delivering parcels.
They can move around and interact with people with voice.
They can do this because they have cameras, microphones, and speakers.
You are a newcomer in this workplace and here you are discussing with one of your colleagues.
This is a sensitive discussion that you would like to keep private.
You suddenly worry and wonder about the privacy of your conversations.
Following this introduction, the participants had a privacy
conversation with a conversational agent. Afterwards, they gave feedback on the
quality of the conversation and on the perceived convenience of having such a
conversation either directly with a robot, or virtually later through their phone or laptop.
We collected and analyzed the conversations and free text feedback responses of our participants.
The conversation topics were threefold, concerning the robot sensors, data transmission to the cloud,
and data aggregation, storage and access control on the cloud.
The participants attitudes were various, for example how they explored the topic
(in-depth or in-breadth), or, whether they asked rather direct or indirect
questions revealing a less trusting attitude. Concerning the impact of the conversations, most
participants said they felt more knowledgeable and more comfortable after the conversations.
Most perceived both, embodied on the spot, and, later, virtual conversations as useful.
However, we also identified issues with the conversations.
Some issues were generic and related to LLMS, such as hallucinations or
repetitive or vague answers. Some were privacy specific:
indeed, some participants would have liked more contextual answers which the
conversational agent could not provide. Others mentioned that they did not
fully trust the robot or prefer to interact face-to-face with a human.
To conclude, we found that privacy conversations have a good potential,
but conversational agent have to be adapted to the privacy domain and
remaining technical issues have to be solved to make them a viable solution.
Thank you