The next twenty years will see teachers under increasing pressure to convincingly justify their existence. Advances in artificial intelligence (AI) technologies are already prompting calls for teaching to be automated, learner-driven and ‘teacher-proof’. While these technologies might still require non-specialised classroom facilitators and technicians, the role of the highly trained expert teacher is coming under increasing threat. There is a growing sense that “we don’t really need teachers in the same way anymore”.
Put bluntly, the entire premise of ‘the teaching profession’ faces an impending challenge. In a future where education can be reliably provided by machines, why continue to invest millions of dollars in training human experts to do the job? Given the likely trajectory of technological developments over the next few decades, is there anything that an expert teacher does that machines will never be able to do? As an education researcher and teacher, I would like to think that there is! Here, then, are six aspects of expert human teaching which are getting overlooked in the current rush toward automating the classroom:
There is clear benefit from being with someone who can pass on knowledge, especially someone who has previously been in the position of having to learn that knowledge. This latter qualification is a uniquely human characteristic. When a learner learns with an expert teacher, they are not simply gaining access to the teachers’ knowledge but also benefiting from the teachers’ memories of learning it themselves. Technology can be pre-loaded with content of what is to be learned. Yet, no AI technology is going to ‘learn’ something exactly the way a human learns it, and then help another human learn accordingly.
A human is uniquely placed to sense what another human is cognitively experiencing at any moment, and respond accordingly. In this sense, face-to-face contact with a teacher offer learners a valuable opportunity to engage in the process of thinking withanother human brain. On one hand, there is something thrilling about witnessing an expert who is modelling the process of thinking things through. Conversely, a human teacher is also able to make a personal ‘cognitive connection’ with another individual who is attempting to learn. As David Cohen puts it, teachers are uniquely able to “put themselves into learners’ mental shoes”. Despite the best efforts of computer science, many aspects of thinking cannotbe detected and modelled by machines in this way.
Teaching is a mutual obligation between teachers and learners. No teacher can stimulate the learning process without the cooperation of those who are learning. Good teachers make personal connections with their students, helping them gauge what might work best at any particular time. Before attempting to intellectually engage with a group, teachers will “take a mental pulse of students’ demeanours”. Teachers work hard to establish this mutual commitment to learning, as well as sustaining engagement through motivating, cajoling and enthusing individuals. All of these are interpersonal skills that come naturally to people rather than machines.
There is something transformative about being in the presence of an expert teacher talking about their subject of expertise. Listening to an expert talk can provide a real-time, unfolding connection with knowledge. A good speaker does not stick rigidly to a written text, but refines, augments and alters their argument according to the audience reactions. A teacher speaking to a group of learners therefore engages in a form of spontaneous revelation. Key to this is the teacher’s role in leading and supporting learners to engage in active listening. As Gert Biestareasons, being addressed by another person interrupts one’s ego-centricism – drawing an individual out of themselves and forcing them into sense-making.
The bodies of human teachers are an invaluable resource when engaging learners in abstract thought. Teachers use their bodies to energize, orchestrate and anchor the performance of teaching. Many subtleties of teaching take place through movement – pacing around a room, pointing and gesturing. Teachers make use of their ‘expressive body’ – lowering their voice, raising an eyebrow or directing their gaze. Crucially, a human will respond to the living biological body of another human in a completely different way to even the most realisticsimulation. Being looked in the eye by another person is a qualitatively different experience than being looked at by a 3D humanoid robot, let alone a 2D cartoon agent on a screen.
A key part of good teaching is the human capacity to improvise. Rather than sticking tightly to a pre-planned script, teachers will adjust what they do according to the circumstances. Like most performative events, teachers approach a session with a rough plan or structure. However, thereafter they improvise their way around these aims and objectives. Teaching requires acts of creativity, innovation and spontaneity – akin to dancing or playing jazz. Teachers and learners feel each other out, find common ground and build upon it. Teaching also demands a tolerance for imprecision, messiness and not knowing. Most human actions involve a degree of guesswork, bluff and willingness to ‘make do’. These are processes that computer systems are largely incapable of.
As these examples illustrate, an expert human teacheris able to support learning in ways that can never be fully replicated through technology. Unfortunately, these qualities remain largely unrecognised, even by teachers themselves. Many educators consider teaching to be an ‘unconscious’ act that is difficult to pin down and articulate. Yet such coyness does little to dispel the technology-driven arguments currently being made against the teaching profession. Teachers need to speak up and make an irrefutable case for the continued presence of expert professionals at the forefront of classrooms.
So how can we rehabilitate human teachers in the minds of their detractors? The uphill battle in countries like Australia is to revitalise schools and classrooms to allow teachers to work in the ways just outlined. These are all characteristics that a good teacher should have, but are considerably restricted in an era of ‘teaching out-of-field’, templated lesson plans and rigid standardised testing.
A first step in this direction might be to alter the ways that people think and talk about teaching. Teachers need to speak forcibly about these qualities – amongst themselves, within their professional associations, withparents, politicians, pundits and anyone else with influence. Teachers also need to argue directly against the tech industry and corporate reformers looking to replace them with machines. There is obvious value in the human expert teacher. Yet unless teachers are able to make a convincing case, they may well lose the argument before they even realise that there was one.
Neil Selwyn is a professor in the Faculty of Education, Monash University (Australia). He previously worked in the UCL Institute of Education, and Cardiff School of Social Science (UK). Neil is currently writing a book on the topic of robots, AI and the automation of teaching. Over the next six months he will be posting writing on the topic, hopefully resulting in: Selwyn, N. (2019) Should Robots Replace Teachers? Cambridge, Polity.
Neil can be found on Twitter @neil_selwyn
5 thoughts on “Six reasons Artificial Intelligence technology will never take over from human teachers”
At the Australian Senate Committee hearing on the Future of Work and Workers last week, I was asked what proportion of jobs AI would replace. I suggested more like 40% than 10% but no one really knows.
Artificial Intelligence technology will never take over completely from human teachers, but it will supplement their role for many routine tasks.
The teaching profession doesn’t “face” an impending change, that change has already started happening. University teaching has already flipped from being campus based to mostly online. However, most university lecturers will not admit this to themselves or to others. The higher levels of school will follow over the next few years. This is without AI, just using decades old e-learning technology.
Much of education can already be reliably provided by machines. This requires fewer, but more highly trained, teachers. What AI will not be able to do, at lest not well, is handle the exceptional situations.
Like human teachers, AI learns (that is why it is called “artificial intelligence”). Software is used to mimic human learning. Unlike a human, AI can learn from millions of cases very quickly. However, the results still need to be checked by a human as they can be unpredictable.
AI can minim a human very effectively. The ELIZA natural language program of the 1960s was able to mimic a human in a conversation. It does not take much to do this, if the topic is limited to a narrow field, such as a course.
Like human teachers, some AI can explain its chain of reasoning, allowing the student to learn not just what to think, but how to.
AI can use a virtual face and body on screen, but in most cases this is not necessary. Most university students now learn online using text based materials. Where there are videos they watch them at high speed so any person visible is little more than a blur.
This is not to say AI will, or should, replace all human teachers. But AI will be used alongside other tools, such as writing and books, for teaching. It is a long time since anyone argued seriously that students should not write notes as they would then not be able to memorize, or that students should not read books, only listen to the teacher. In a few years time arguments against AI will seem as quaint as those against writing and books.
See also my notes on Educating the Future Workforce
As a practitioner interested in this space I am not sure that the discourse is around the replacement of teachers with AI applications. In all that I have read and all that I have heard the primacy of our relational functions are never questioned. Consistently, the role of teachers in driving learning through effective and multi-faceted relationships with young people is recognised in all the debates.
The questions that continue to be raised are the degree to which AI applications will supplement or change teachers’ work in years to come. This appears to be highly contentious, in the same way that students accessing the internet in a classroom was 25 years ago. The fundamental structure of schools where a student grouped in a class, allocated a teacher and a physical space and given allocated time in a day will not see teachers replaced by AI applications, but the enduring question is how could the structures of school change if we did embrace them so that the relational roles are where teacher time dominates? However, this is not just a question of practice or learning philosophy, but a pragmatic industrial one as well.
Trent, some forms of education, such as Montessori schools, are less focused on the teacher, class and time. Perhaps AI could enhance this, at least for older students.
A few more thoughts.
1. The history of future predictions about new technologies is woeful. No shortage of examples of claims that proved to be not just wrong but so off the mark they are regularly recycled as humour.
2. AI has had a long history of over-hyping its achievements. (see, e.g. McDermott, D. (1976). Artificial Intelligence Meets Natural Stupidity. SIGART Newsletter(April), 4-9. )
3. The current boom in various, so-called machine learning (ML) approaches derives from a perfect storm of huge data sets, and sufficient computing grunt to allow various ML approaches which have been around for some time to be doable.
4. The generic use of AI in discussions like these is unhelpful.
4. Education has an awful record in making sensible use of various digital devices tracking back to the late 1970s. It has not been helped by silly research questions that concentrated on the “how” rather than the “what” and the “why”, e.g. if machines can do X what does it mean for the teaching of X in schools?
5. There is a great deal invested in keeping a lot of educational practices as they have always been. “The digital” has been largely used as window dressing. Harold Benjamin’s satire is being played out over and over: Peddiwell, J. A. (2004). The Saber-Tooth Curriculum (Classic ed.). New York, NY: McGraw-Hill.
6. One of the better analyses I have come across is: Agrawal, A., Gans, J., & Goldfarb, A. (2018). Prediction Machines: The Simple Economics of Artificial Intelligence. Boston, MA: Harvard Business Review Press. The simple economic question what happens when something becomes cheap is an elegant way through the hype and tosh around AI, jobs and futures. So the interesting question for education and all the other things humans dabble in is what happens when prediction becomes cheap?
Artificial Intelligence certainly raises many questions about the future of education. Not only will it potentially change the process of delivering content, but also the skills needed by students to adapt to the rapid changes in this technology. However, as the article pointed out, there remains some significant advantages to education when a teacher is able to adapt to the needs of the students and can impart their experience through the learning process. AI cannot fully replace the personal aspects of communication between teachers and their students. It still has limitations. However, AI technology is able to assist students with learning disabilities, and there will be continued advancements in this area in the near future. But whether mainstream or special needs, all students will still benefit greatly from the personal guidance and individual feedback of experienced teachers. Technology comes at a cost, but you can’t put a price on the the knowledge and expertise of an experienced teacher. There will still be a place for teachers in the future.
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