Part 6-Teacher-Robots: Classroom Assistants or at the front of the class?
The robots are here.
In the UK, for one, young people are already learning to work with machines using the AV1 robot. AV1 is a distance-learning robot that allows children suffering from long-term illness to attend school. It was designed in response to the 72,000 children in the UK who miss long stretches of schooling because of their illnesses. Through a 4G connection to the students’ location, AV1 acts as a proxy for the student; it can raise its hand, share with the class, or speak quietly with groupmates. It can even go out to recess.
Chinese kindergarten classes have embraced Keeko, an autonomous robot that can tell stories and pose riddles. A 2018 article from the Hong Kong Free Press painted a vivid picture of the 600 Chinese kindergarten classrooms that welcomed Keeko for trials: “Round and white with a tubby body, the armless robot zips around on tiny wheels, its inbuilt cameras doubling up both as navigational sensors and a front-facing camera allowing users to record video journals” (Law & Zhu). According to the report, when Keeko hears a correct answer to a question, its heart-shaped eyes begin to flash. Keeko instructs the children how to brush their teeth properly, reads stories while prompting them for predictions, plays educational games, recalls conversations, and recognizes faces.
Here in America, teachers are leery of robots as instructors. Education Week reports that 84% of teachers disagreed with the assertion that student learning would improve if more K-12 teachers had AI-powered robots as classroom assistants. In addition, over 90% believed student learning would not improve in classrooms where artificially intelligent robots took the place of “chronically low-performing” teachers (Bushweller, 2020).
Teachers point out that relationships are at the core of a teacher’s value to their students. True enough. But, it is clear from Keeko, the AV1 robot, and countless other AI developments that machines are able to undertake the routine instructional tasks that teachers often do. And, as outlined in the previous post, machines are increasingly undertaking more and more non-routine tasks that we long considered to be uniquely human.
In addition, the content-driven curriculum foisted upon (or embraced by) teachers is susceptible to automation. That is because computers are extremely adept at undertaking tasks that involve structured information and follow patterns with known end-states. Many materials and instructional tasks fall under this definition and thus AI-driven resources are already prevalent in American schools. Furthermore, instruction is often divided into arbitrary disciplines — history, science, math — when in actuality, the landscape of most real-like professional tasks is interconnected. Scientists need to know how to collaborate on social platforms, journalists need to know how to analyze data, and social workers need to know how to interpret emojis. The world’s most pressing problems are not neatly organized by discipline. When schools overlook the importance of honing non-routine cognitive skills— like the ability to form an interdisciplinary argument, or solve a real-world problem that defies subject boundaries — then instruction becomes vulnerable to automation.
Moreover, as students age, they and their parents often become more concerned about passing content-driven, standardized tests. Would a robot not be adept at preparing students for such a test? Machines can analyze vast amounts of exam data: What questions are asked in the tests? How frequently are they asked? How are they typically phrased? Which words, phrases, or topics appear most often? What are the highest-scored responses? What do they have in common? How are these responses typically constructed? — and so on. If curricula, instruction, and assessment are formulaic, automation is easier.
And automation won’t be faceless. Humanoid teachers are not so far into the future. Neon, the world’s first ‘Artificial Human,’ was introduced by Samsung-funded Star Labs in 2020. Neon is a photo-realistic videobot of a human being that can move, talk and smile “with such authenticity that it is impossible to tell they are computer-generated.” (See for yourself: https://www.youtube.com/watch?v=iAY2LxaFtaM) Neons can also remember, learn things about their user, and speak in any language.
Neons are not AI assistants, the company says. “Neons are more like us, an independent but virtual living being, who can show emotions and learn from experiences.” Neons are designed to converse and sympathize “like real people” to act as lifelike companions. So, how does the company market Neons? As teachers, for one.
In the years to come, machines that look and behave like humans will be able to impart vast quantities of information to students without the middleman of a human teacher. This does not necessarily mean that classrooms become “either-or” domains— either human teacher or robot teacher. The future of workforce technology is a human-machine collaboration and at the outset robots will assist human teachers. But, in the long run, educators who function uniquely as imparters of knowledge will be susceptible to automation. That said, the teacher who skillfully leverages machine data with a keen understanding of how to connect with a student on a human level is well-positioned to stave off automation.
But could the public ever accept robots at the front of the class? Culturally, Americans are becoming more and more comfortable interacting with machines. We unwittingly carry on conversations with chatbots and robocallers regularly. We encounter hologram virtual boarding agents at airports. Robots deliver room service at our hotels. Product-scanning robots at Walmart glide around us while we shop. A decade from now, will our comfort level with robots grow to the point that parents will accept robots reading to their children at the front of the class? Keeko is already doing that.
A PEW Research Center report indicated that Americans viewed teachers as the sixth most likely profession to be at risk of automation, following fast-food workers, insurance claims processors, software engineers, legal clerks, and construction workers — in that order. Technology can — and will — at least partly replace drivers, travel agents, cashiers, bookkeepers, analysts, and editors. So, how can teachers expertly leverage their humanity and continually set themselves apart from machines in a fast-moving and tech-laden professional world?
The answer requires a fundamental rethinking of our education system: what skills we hone in the classroom, how we communicate them, and how we have our students demonstrate their mastery of them. In all, it is important to remember that human creativity and social-emotional skills are aspects of our humanity that are very difficult for machines to replicate. If there is hope of students achieving job readiness in this day and age — and teachers cementing their positions— it will be to leverage creative and social-emotional competencies and learn to augment — not resist — the work of machines. And yet, teaching creativity and social emotional skills in a tech-laden world has rarely been a top priority in most American schools.
We know that machines can produce sophisticated statistical models, perform logical tasks, and accomplish routine physical activities, often more quickly and effectively than we could ever dream of doing. But we have a strong advantage over our robot counterparts: adaptability. Data inputs do not box in our thinking and actings; when faced with the complicated nuances and changing dynamics of human problems, we develop creative, human solutions. So, our way forward is focusing on what makes us distinctly human.
