Human-Animal Teaming as a Model for Human-AI-Robot Teaming: Advantages and Challenges

Abstract

Humans and animals have co-evolved for millions of years. The animal connection began with the exploitation and observation of animals by humans. Over time, regular social interactions were incorporated into the animal connection. This connection has also allowed us to utilize humans to help support and augment our skills and abilities; physically, emotionally, and cognitively. Of course, this relationship has changed over time as our connection and understanding of these animals’ capabilities has evolved as well as through the co-evolution of our species. At the same time, the future of human-autonomy teams shows a strong trend toward incorporating features to allow the human to engage with their robotic counterparts in a more natural way. Norman (2004) suggests that “products and systems that make you feel good are easier to deal with.” As the interfaces of robots, computers, and inanimate objects are designed to be more “intelligent,” humans may adapt the way they interact with, communicate, and think about such technology, treating objects more like humans. Humans (and many other animals) display a remarkably flexible and rich array of social competencies, demonstrating the ability to interpret, predict, and react appropriately to the behavior of others, as well as to engage others in a variety of complex social interactions. Developing computational systems that have these same sorts of social abilities is a critical step in designing robots, animated characters, and other computer agents that appear intelligent and capable in their interactions with humans (and each other), that can cooperate with people as capable partners, that are able to learn from natural human instruction, and that are intuitive and engaging for humans to interact with. Yet, today, many current technologies (animated agents, computers, etc.) interact with us in a manner characteristic of socially impaired people. In the best cases they know what to do, but often lack the social intelligence to do it in a socially appropriate manner. As a result, they frustrate us, and we quickly dismiss them even though they can be useful. It may instead be more useful to look at how humans interact and work with their animal counterparts. Like anthropomorphism, zoomorphism centers on attributing qualities to non-sentient beings; but in this case; it focuses on animal-like characteristics (Karanika & Hogg, 2020). In many contexts, teams are capable of solving complex problems well beyond the capacity of any one individual team member (Salas, Rosen, Burke, & Goodwin, 2009). However, not all teams are successful, and failures often come at a high cost. Why this is important is that humans often do not ascribe the same intelligence, consciousness, or abilities to animals as they do to humans and therefore may be less apt to get frustrated when it does not perform as expected. Also, understanding what different strengths and weaknesses each team member possesses will ultimately allow that team to be more successful. While animal-inspired designs have aided in improved robotic movement and manipulation, we maintain that design inspired by human-animal teaming can provide similar gains in robotic development, especially as it concerns improved human-robot interaction and teaming. As most people have far more experience interacting with animals than with robots, they are generally more able to recognize limitations in an animal’s ability to complete a task (Phillips, Ososky, Swigert, & Jentsch, 2012). In consequence, robotic designs inspired by human-animal relationships can lead to faster acceptance while fostering more effective interactions between humans and robots, as humans tap into well-established mental models, promote better understanding of near-future robots, and thus appropriately calibrate trust in near-future robotic teammates.