R2D2 as a model for AI collaboration
By: Alexis Lloyd
Tags: AI, Robots, Design, UX

This essay is about the way we design relationships between humans and machines — and not just how we design interactions with them (though that is a part of it), but more broadly, what are the postures we have towards machine intelligences in our lives and what are their postures toward us? What do we want those relationships to look and feel like?

As I’ve been thinking through these ideas, science fiction characters are one of the lenses I’ve been finding helpful as a way of thinking about different models for our relationships with machines. Specifically, I’ve been using these three — C3PO, Iron Man, & R2D2 — as notable archetypes that describe different approaches to how we might design machine intelligences to engage with humans.

C3PO

C3PO is a protocol droid; he’s supposedly designed to not only emulate human social interaction, but to do so in a highly skilled way such that he can negotiate and communicate across many languages and cultures. But he’s really bad at it. He’s annoying to most of the characters around him, he’s argumentative, he’s a know-it-all, he doesn’t understand basic human motivations, and often misinterprets social cues. In many ways, C3PO is the perfect encapsulation of the popular fantasy of what a robot should be and the common failures inherent in that model.

Now this idea didn’t emerge in 1977. The idea of a mechanical person, a humanoid robot, has been around since at least the 1920s. Eric the Robot, or “Eric Robot” as he was more commonly known, was one of the earliest humanoid robots. He was pretty rudimentary, as you can see from the kind of critique that was leveled at Eric by The New York Times in the above quotes — it critiques his social demeanor and also questions his utility — why is a robot that moves and converses better that the one that can tell when the water levels in Washington are too high? Is this the best form or use for a robot?

But despite these criticisms, people were fascinated by Eric, as well as by the other early robots of his ilk, because it was the first moment that there was this idea, this promise, that machines might be able to walk among us and be animate. We’ve had this idea in our social imagination for nearly a century now—the assumption that, given sophisticated enough technology, we would eventually create robotic beings that would converse and interact with us just like human beings.

Our technology today is many orders of magnitude more sophisticated than Eric’s creators could have imagined. And we are still trying to fulfill this promise of a humanoid robot. We see the state of the art today with robots like Sophia.

This is so much closer to that humanoid ideal than Eric was, but it falls so short and just feels awkward and creepy.

On the software side (“bots” vs. “robots”), we have examples of the failure of the C3PO model in the voice assistants we use every day. They’ve gotten pretty “good”, but still can’t understand context well enough to respond appropriately in a consistent way, and the interactions are far from satisfying. It turns out that even with incredibly rich computational and machine learning resources, interacting like a human is really hard. It’s hard to program a computer to do that in any satisfying way because in many ways it’s hard for humans to do successfully either. We get it wrong so much of the time.

Interacting like a human is hard (even for humans).

We don’t all talk to each other the same way. We don’t all have the same set of cultural backgrounds or conversational expectations. Below are charts created by British linguist Richard Lewis to show the conversational process of negotiating a deal in different cultures.

These challenges have come to the fore lately with everyone from search engines to banks trying to create convincing conversational interfaces. We see companies struggling with the limitations of this approach. In some cases they have addressed those challenges by hiring humans to either support the bots or in some cases actually pose as chatbots.

Welcome to 2020, where humans pretend to be bots who are in turn pretending to be human.

Stop trying to make machines be like people

Obviously, the ideal of creating machines that interact with us just like people do is incredibly complicated and may actually be unattainable. But more importantly, this isn’t actually a compelling goal for how we should be implementing computational intelligence in our lives. We need to stop trying to make machines be like people and find some more interesting constructs for how to think about these entities.

The reason people started with the C3PO model is because human conversation is the dominant metaphor we have for interacting and engaging with others. My hypothesis is that this whole anthropomorphic model for robots is fundamentally just a skeuomorph because we haven’t developed new constructs for machine intelligence yet, in the same way that desks and file drawer metaphors were the first attempts at digital file systems, and when TV first emerged, people read radio scripts in front of cameras.

Instead, a more compelling approach would be to exploit the unique affordances of machines. We already have people. Humans are already quite good at doing human things. Machines are good at doing different things. So why don’t we design for what they’re good at, what their unique abilities are and how those abilities can enhance our lives?