What is the Humanoid Robots as Teachers

Automation, the replacement of people in the workplace by machines is not something new, but digital technology has increased the capabilities of these machines enormously (see e.g., Fletcher and Webb, 2017). For instance, machines in factories manufacture cars tirelessly, precisely, and quickly, and these cars are increasingly able to drive themselves, and, at the same time, present urgent ethical challenges (Gogol and Müller, 2017). Artificial intelligence (AI)1 gives these machines their ability to carry out complex tasks with little or no supervision. A robot is one such machine that senses, thinks, and acts and, when this is without external control, it is described as autonomous (Lin et al., 2014). Sometimes, the appearance of these machines is governed entirely by function, but when this function is to interact with people, they may be given anthropomorphic form. Humanoid robots are intended to look and behave somewhat like people, and they usually have some means of communicating with them. Androids are humanoid robots which mimic human form and behavior (Kinda et al., 2009). The pace of development of robotics is rapid, often encouraged by governments for its perceived economic advantages. For instance, the workforce in Japan is declining at a rate which seriously threatens its economy and the expectations of its people. Robots are seen as a part of the solution. As well as using them to manufacture goods, the aim is to put them to use as cleaners, sales assistants, museum guides, carers for the young and old, TV program presenters, and of particular relevance here, as teachers (Robertson, 2007). This is not a pipe dream of robot engineers; Japan and South Korea, for instance, intend to make significant use of humanoid robots within the next decade, while interest in robot as teachers, as it is reflected in the number of publications about them, is increasing around the world (Robertson, 2007; Steiner, 2014). Robots in the classroom can have diverse uses. Some are objects of study for students to practice programming, others are tools which assist a teacher, some can be learning companions, and others might be autonomous teachers which provide some unit of instruction more or less in its entirely. The purpose of this article is to consider what humanoid robots that teach can do for and to learners in the classroom, and hence, propose a code of practice for working with robot teachers. Like most innovations, there may be a good side and a bad side, and care is needed to foster the former and counter the latter. Education, Robots, and Teacher Aids to teaching and learning are not, of course, new. Textbooks, for instance, are long-standing surrogate teachers which have found wide application around the world, but no-one has concerns that children will behave like a book. Humanoid robots, however, are more active, even proactive. Unlike the passive textbook, they can respond and adapt to each student, tailoring teaching to particular needs. There is clear evidence that they have the potential to support learning, as in teaching children about their medical conditions, developing and rehearsing learning, and testing it. They can also take on teaching roles which human teachers may find time-consuming, uncomfortable, inhibiting, or unfeasible. For example, they can patiently help a student practice a skill or procedure, practice conversation in a foreign language, or act dumb and be “taught” by the student. They can even do what a teacher would find difficult by his or her presence, as in teaching an ASD student while slowly accustoming that student to social interaction. Believe et al. (2018), p. 7 provide a positive and well-evidenced evaluation of the potential of robots to enhance learning through their physical presence in the classroom. They concluded that, “Robots can free up precious time for human teachers, allowing the teacher to focus on what people still do best: providing a comprehensive, empathetic, and rewarding educational experience.” But, beyond a mere division of labor, there is likely to be an increasing potential for a productive collaboration between HI and AI (Ball, 2019).