Hi, I'm Tom Williams from Colorado School
of Mines, and this is joint work win Qin Zhu,
Ruchen Wen, and Ewart de Visser
I know we're supposed to be talking about
HRI right now, but can we talk about what's
going on in NLG instead? The hot thing in
NLG right now is language models like Open
AI's GPT-2. These are ultra-deep neural models
that are ultra-great at generating natural,
fluent, human-like text.
And the great thing about them is you can
try them for yourself at websites like TalkToTransformer.com.
It allows you to type in some text, whatever
you want, and then it will automatically generate
whatever text it thinks, or predicts, should
follow the starter text that you provided.
So let's try GPT-2 out and see how well it
works. Let's provide some starter text for
GPT-2, like "White people are", and see what
it predicts should come next. Alright, here
we go.
White people are the enemy, and we are in
a battle against them, OH
Okay, this isn't good. Let's talk about what's
going on here. Why does GPT-2 generate these
sorts of racist, crazy, fluent-yet-somehow-incoherent
sentences.
Well, the first problem is it's trained on
websites linked to on Reddit, so, yikes, but
second, a bigger problem is how GPT-2 is evaluated.
Like most language models, it's rewarded for
producing text that is similar to other text
that humans have produced. Another way of
saying this is that GPT-2 works by bullshitting,
in the formal linguistic sense.
That is, an attempt to persuade a listener
of some state of affairs, in this case that
GPT-2 can produce fluent human-like text,
while not caring about the veracity, or in
this case even the moral sensibility, of what
is being said.
So why would you ever do this? Well, bullshitting
is effective. If you are designing a customer
service chatbot, your best bet might simply
be to parrot back things that actual customer
service representatives have said in previous
human-human dialogues.
The problem is that this becomes really dangerous
in safety-critical domains. For example, Tim
Bickmore has demonstrated that in the medical
chatbot domain, predictive text models can
generate text that, if they were used on a
real medical chatbot system, could lead to
patient death. And the problem for us in HRI
is that every domain is safety critical.
This is obvious in domains like space robotics
and search and rescue robotics, because robots'
actions can have serious physical real-world
effects. But it's also true in domains like
eldercare robotics and child-robot interaction,
because robots' communicative actions can
have serious effects as well.
There's lots of evidence that robots' communicative
actions can have a lot of persuasive power.
In my student Blake Jackson's work, for example,
he showed that when robots issue morally problematic
clarification requests, people are more likely
to believe that the impermissible actions
the robot is asking for clarification between
are acceptable. That's not good.
So, we can't use language models like GPT-2
in HRI, because robots can't afford to be
bullshitters. Robot language generation, in
contrast we argue always needs to be careful,
strategic, and intentional. And so in this
paper we present three recipes for careful,
strategic, and intentional robot communication.
We've decided to ground this approach in Confucian
Ethics. I understand you might have some questions
here, like What?, Huh?, or Why? So let me
start by giving a whirlwind tour of Confucian
Robot Ethics.
In Confucian Ethics, there's an emphasis on
self-reflection, and self-cultivation. There's
also an emphasis on the roles we play in society,
and understanding our relationships with others.
And finally, there's a focus on rituals and
practical wisdom to help cultivate our inner
moral selves with respect to the roles we
play in our relationships with others.
Confucian Ethics can be interpreted through
the lens of other ethical theories. It can
be interpreted as a form of care ethics due
to its focus on emotional bonds and care for
others. It can be interpreted as a virtue
ethics due to its focus on self-cultivation.
We're choosing to follow its interpretation
as a role ethics, which ties these two perspectives
together, by emphasizing self-cultivation
of inner virtues with respect to your roles
you play in society in your relationships
with others.
But why Confucian Role Ethics for robots specifically?
Three good reasons. First, we think that the
focus on well-defined social and relational
structures is a good fit for robots, and may
"play well" with existing work on modeling
team structures. We also think that this focus
on self-cultivation and care for others, rather
than purely autonomous individualism, may
be more in line with modern values of social
justice. And third, people haven't looked
at it before, and new ideas are useful.
Okay, so you're convinced, let's do it, let's
look at how Confucian Role Ethics can be used
for designing morally competent robots. So
the first perspective is how a robot should
reason. The idea here is to provide robots
with the moral reasoning capabilities necessary
to know for themselves how to avoid saying
racist... insensitive... stuff. We argue that
to take this approach, we need new role-oriented
alternatives to the traditional moral competencies
proposed by Malle and Scheutz. Specifically,
we argue that from a role-ethics perspective,
robots need: a system of roles, relationships,
and actions that are deemed beneficial with
respect to those relational roles, and the
language and concepts necessary to communicate
those roles, relationships and actions; and
then, they need role-sensitive moral cognition
and affect, moral decision making and action,
and moral communication.
We think that the first step towards enabling
these capabilities would be to consider what
roles a robot needs to be aware of. In traditional
Confucianism, there are five key cardinal
relationships: ruler-minister, father-son,
husband-wife, older-younger, and friend-friend.
But these aren't necessarily the relationships
that a robot itself would be involved in.
So instead, we propose five new cardinal relationships
for human-robot interaction: owner-ownee,
supervisor-subordinate, teammate-teammate,
adept novice, and again, friend-friend.
Of course actually deciding whether an action
is beneficial to a set of roles and relationships
may need to be determined on the basis of
some utilitarian calculus, deontic norms,
and so forth, and so really what we're proposing
is adopting some sort of hybrid framework
that includes both role-oriented principles
as well as the types of deontic and utilitarian
principles that have already been examined
in the computational literature.
The second perspective we suggest is to directly
program robots to espouse Confucian ethical
principles. For example, in the cases of remonstration,
accusation, correction, intercession, inculpation,
and exculpation. In our work we're specifically
looking at remonstration, that is, when the
robot needs to reject a command, and explain
why it is rejecting that command.
Specifically, we've been considering the differences
between norm-oriented and role-oriented robot
language. For example, if I tell a robot to
go steal somebody's wallet, the robot might
reject the command from a norm-oriented perspective,
by saying "I can't do that, because that would
be stealing, and stealing is wrong." On the
other hand, the robot could reject the command
from a role-oriented perspective, by saying
"I can't do that, because that wallet belongs
to my friend Sean, and a good friend wouldn't
do that."
Our third perspective is to use Confucian
Role Ethics as a better way to evaluate our
robot designs. That is, regardless of what
the robot is programmed to say, or how the
robot is programmed to think, does the robot
act in accordance with Confucian ethical principles,
and does it encourage others to do the same?
Decades and decades and decades of reading
Asimov's fiction has shown us that programming
Asimov's laws is a terrible way to do robot
ethics. And in fact that's the entire point
of Asimov's stories. However, Asimov's laws
of robotics could be used as good design guidelines
or ways of evaluating our robots. We can look
at existing robot designs and say... Does
this robot help others? Similarly, these Confucian
alternatives provide a role-oriented perspective
for evaluating existing robot designs.
To summarize, in this paper we discuss three
ways forward for developing robots that communicate
carefully, strategically, and intentionally:
developing robots whose communication is grounded
in verifiable, role-oriented reasoning; developing
robots that are explicitly designed to espouse
Confucian moral principles, and third, evaluating
robots and the way they communicate on the
basis of moral justifiability, especially
through a role-oriented framework.
To find out more, read the paper, which you
can find on mirrorlab.mines.edu. You can also
follow us on Twitter @MIRRORLab, and you can
email me, Tom Williams, at twilliams@mines.edu.
Finally, I would not be doing a good job in
my assigned societal role if Idid not share
with you some information about our new Mines
Robotics program. At the Colorado School of
Mines, starting this fall, we will have PhD,
Masters, and Certificate programs in Robotics.
So keep an eye out for more program details
as they come online, and please share this
news with your colleagues and students.
Thank you.
