The future of learning is unpredictable and can best be described as a mirage. It is constantly changing and therefore the best we can do now is to look at what learning currently looks like.

In this article, we examine one aspect of technology-enabled learning and the challenges it posed. Among all the factors that go into shaping the educational system, we appear to be reaching a critical point where technology is the most talked about factor but is also the factor that is changing the fastest.

The topic that is being examined today is 'Machine-led teaching'. This encompasses any form of teaching that is not delivered directly by humans. While the topic under examination is yet to gain mainstream attention and therefore the evidence for or against its application is still not fully available, we will look at the potential challenges and how to overcome them.

According to Sir Anthony Seldon, vice-chancellor of the University of Buckingham, UK, "intelligent machines that adapt to suit the learning styles of individual children will soon render traditional academic teaching all but redundant".

Edwards et al (2018) have already talked about the changing role of teachers from experts to overseers. The resulting loss of jobs is another major issue. While a whole host of issues can present itself in this plausible new scenario, the one we are concerned about is the 'social and emotional' aspect of education.

While prediction models on when we will have a system in place where machines replace traditional teachers in the classrooms vary from five to 20 years, what is worth observing is where this is currently taking place.

Omar et al (2013) noted that "it has been shown that young children performed better on post-learning examinations and generated more interest when language learning took place with the help of a robot as compared to audiotapes and books."

A report in Reuters (March 2018) goes on to elucidate the benefits of having robots in the classroom as trialled in a Finnish setting.

The robot, for languages and Math, seemed to improve students cognitive development by identifying the gaps in skills and providing timely feedback to the teachers. It concludes by saying that the robots were ineffective at classroom management and therefore, teachers jobs are safe. But that is just one aspect. Imagine a learner growing up being educated by robots. How will they learn the nuances of regulating their emotions?

A robot, at least in its current version, is incapable of demonstrating the wide range of emotions that humans possess. It is not going to be frustrated if a learner were to ask the same question two dozen times nor will it be thrilled if the learner grasped a concept in the first instance. What will our learners take away from this 'social' experience? At best, they will inherit the trait of indifference and in a worst case scenario, they will grow up to be big babies believing the world revolves solely around them.

In a world that is in desperate need of individuals with a sense of compassion and developed emotional quotient, we would be perpetuating the status quo of mindless self-indulgence.

Another aspect that has to be considered, and is the focus of this paper is the social implication. Can a robot or a machine add value to the social interactions a learner experiences? Or are we running backwards in this regard to the medieval ages where students believe that they have at their disposal an object that caters to their whims and fancies? How will that shape their interactions in life outside the classroom?

In this new context, what does socialisation mean? To comprehend this challenge better let us imagine two contrasting scenarios. In the first, in a conventional classroom, the teacher sets a task for a group of students. They follow the instructions and go about working collaboratively to fulfil that task. The teacher facilitates the task ensuring that all students are active participants and that by the end of it, most of them have met the learning outcomes intended. In this instance, while the stated outcome is the acquiring of the knowledge associated with the task, there are a set of non-explicit skills that are being acquired by the students – namely – collaboration, communication and regulation of emotions to name a few. In the second scenario, which is much harder to fathom because it does not fully exist as yet, a machine has donned the mantle of the teacher. In this case, it could be possible that the machine is capable of advanced analysis and able to figure out what input each student needs and at what point. It is able to offer effective interventions at very strategic points to ensure that each learner has understood the stated outcomes. In a best-case scenario, the machine could assign the learner to be a part of a group activity. Or, it could decide that the learner needs a certain intervention which it can provide and bypass the group task. Either way, the chances of the learner missing out on the socio-emotional aspect of learning is fairly high. Therefore, in the second instance, the learners' cerebral development goals are being met but at the cost of possibly ignoring the other crucial areas of development.

The situation posited above may appear far-fetched but if one were to factor in the reality that some schools in Europe and Asia are already using robots as add-ons to the learning process. Many schools across the world are using Virtual and Augmented reality to teach specific concepts or explore far-flung places. While it may seem 'cute' at this point, this author wishes to remind the reader of the unanticipated consequences this could result in if not carried out in a thoughtful manner. One possible solution could be to structure the curriculum to factor in areas that go beyond cerebral development that a learner needs to be adept at to thrive in the technological era. After all, we are preparing our students for careers and lifestyles that probably do not exist as of yet.