Hello my name is Haley Green.
I’m a PhD student in the Collaborative Robotics Lab at the University of Virginia, and I’m
here to talk about our recent study, in which we examined perceptions of failure in a humorous
robot partner.
I’d also like to acknowledge my co-author’s Md Mofijul Islam and Shahira Ali as well as
my co-author and advisor Tariq Iqbal.
Recent advancements in the capabilities of social robots have enabled them to engage
with humans in various environments such as healthcare, customer service, and education.
To achieve fluent human-robot interactions, efforts have been made to improve the interactive
abilities of these robots.
Specifically, robots are being designed to utilize more human-like communication strategies
to facilitate interactions with human agents.
These strategies have become increasingly useful in the domain of failure recovery.
In particular, robots are using techniques such as expressive emotions, explainability,
and personal anecdotes to recover from failures in an interaction.
However, these recovery strategies do not always engage the human agent or encourage
future interactions and communication.
As a result, we choose to explore humor, a recovery tactic commonly observed in human-human
interactions, in order to see if robots can employ human-like humor strategies to recover
from task failure.
Humor is considered an effective conflict resolution and stress relief strategy in human-human
interactions.
Humans utilize humor to show their personality and task-related competence as well as strengthen
working relationships even in cases of task failure.
We want to explore whether robots can also utilize human-like humor strategies to mitigate
negative perceptions of failure.
We conducted this study to investigate the following research questions: one, how do
perceptions of warmth, competence, and the robot as a teammate vary for a humorous and
non-humorous robot, and how do those perceptions vary with perspective?
Two, what is the effect of humor type on perceptions of warmth, competence and the robot as a teammate,
and how do those perceptions vary with perspective?
Three, what is the effect of previous robot experience on perceptions of warmth, competence,
and the robot as a teammate in a humorous and non-humorous robot?
And four, what is the effect of humor type and previous robot experience on perceptions
warmth, competence, and the robot as a teammate?
To explore our research questions we designed a study in which a NAO robot employs one of
the four humor types to recover from failure in a partnered game, modeled after the children's game iSpy.
We then conducted a pilot to first verify the funniness of the jokes used and explore
the effects of demographic features on perceptions of humor.
Next, we used the main study where we examined the effects of humor on perceptions of failure
with both a dyadic interaction partner and a bystander in the interaction.
We considered the four humor types that are most commonly observed in human-human interactions.
That is: affiliative, aggressive, self-defeating, and self-enhancing humor.
Affiliative humor is meant to amuse everyone and is typically associated with good-naturedness.
Alternately, aggressive humor is often associated with sarcasm and teasing.
Self-defeating humor sets the joke-teller as the target of derision in an attempt to
amuse others.
And finally, self-enhancing humor is good-natured like affiliative humor, however it’s more
introspective and less focused on cultivating relationships.
We used SoftBank Robotics’ NAO robot and the expressive behavior modules in the Choregraphe
suite.
We chose to use Amazon Polly’s text-to-speech platform over the option in Choregraphe because
of its robust annunciation and timing capabilities.
We conducted the pilot study to first verify that the jokes we were using were actually considered funny.
We showed fifty participants on Amazon Mechanical Turk twenty randomized clips of the robot
performing the different jokes.
There were five jokes for each of the four humor types.
We took the mean rating of funniness for the twenty jokes and selected the two highest
rated jokes for each humor category to use in our main study.
Participants were asked to rate the jokes’ funniness on a scale from one to five.
We also collected participant demographic information to examine the effects of features
such as age, gender, and previous robot experience on perceptions of the humor types.
The results did not indicate a significant effect of gender or age on how the jokes were
perceived.
However, the results did indicate a significant effect of previous robot experience on ratings
of funniness.
Specifically, participants with a higher experience with robots found the jokes to be funnier
than participants with less experience.
To examine humor as a failure recovery strategy, we had players engage with two different robots.
One robot would successfully complete the task while the other failed upon the third
task.
We counterbalanced these conditions.
The robot that experienced failure would attempt to recover from it’s mistake by using a
joke from one of the four humor types or no humor, for participants in the control case.
The robots were programmed to introduce themselves at the start of the game to further the distinction
between the two.
We chose the gender-neutral names Kris and Sam to avoid any potential bias in perceptions
of gender.
We conducted the study with thirty-two participants.
After each game, we asked participants to complete a post task survey in which they
reflected on perceptions of the robot’s warmth, competence, and ability as a teammate.
In addition, we recorded the interactions to show in the bystander condition.
Here’s a sample clip of what the bystander participants observed.
My name is Sam.
Let's begin round one.
I spy something blue.
Is it this one?
Yes.
Okay, let's begin round two.
I spy something red.
Is it this one?
Yes.
Okay, let's begin round three.
I spy something red.
Is it this one?
No.
Uh oh, I hope they don't dock my pay.
To further observe the effects of perspective on perceptions of the robot’s use of humor
in response to failure, we used Amazon Mechanical Turk to obtain bystander feedback.
256 Participants were shown one of the thirty-two previously recorded interactions.
Each video was presented in the same order it was experienced by the in-person participants.
We also used the same measures as we did for the in-person participants.
The results did not suggest an interaction between perspective and general performance
on warmth.
However, the results did suggest an interaction between perspective and general performance on competence.
Both the dyadic participants and the bystanders found the robot that did not experience failure
to be significantly more competent than the humorous and non-humorous robots.
Furthermore, the results indicated that dyadic participants found the successful robot to
be a better teammate than the bystanders.
The results did not suggest an interaction between perspective and type-specific performance
on warmth.
However for competence, the results suggest that the dyadic participants found the robot that successfully
completed the task to be significantly more competent than the robots that used affiliative,
aggressive, self-enhancing, or no-humor.
Contrarily, the bystanders found the affiliative robot and the successful robot to be significantly
more competent than the robots that used aggressive or no-humor.
For the teammate measure, the dyadic participants had significantly higher ratings of the robot
as a teammate than the bystanders for the robot that used self-defeating humor.
The results did not suggest an interaction between previous robot experience and general
performance on warmth.
However, the results did indicate that participants with less robot experience
found the successful robot to be significantly more competent than the robots that failed.
The results also suggested an interaction between perspective and general performance
on how the robot was perceived as a teammate.
Participants with expert level experience found the humorous robot to be a significantly
better teammate than the participants with less experience.
The results did not suggest an interaction between previous robot experience and type-specific
performance on warmth.
However, participants with less previous robot experience found the successful robot to be
significantly more competent than the robots that failed and used no humor or one of the
four humor types.
Furthermore, participants with moderate to no previous robot experience were more diversified
in their ratings of the robot as a teammate for the type-specific performance; whereas
participants with high levels of previous robot experience had less variation in their
ratings of the robot as a teammate.
We wanted to see if robots could use advanced, human-like humor strategies to recover from
failure.
In this study, we examined ratings of joke funniness for four different humor categories
and reported the effects of different demographic features.
We also explored the relationship between humor type, perspective, and previous robot
experience.
Notably, we observed that that dyadic participants found the robot that used self-defeating humor
to be a better teammate than the bystanders did.
We reason that the vulnerability expressed in self-defeating humor is more endearing
in intimate, dyadic interactions than in more observational, bystander interactions.
Furthermore, when it comes to previous robot experience, we reason that participants with
high levels of previous robot experience are more familiar with the robot's performance
potential and capabilities and as a result, they do not find the robot's task failure to be
as much of a negative reflection of its potential as a teammate.
We can use these findings to compare humor as a failure recovery strategy to alternative
strategies like explanations, apologies, and preemptive attempts to set expectations.
Thank you.