Whispering Thoughts – On This and That (No 5)

MAY 2023



Part I: Introduction to the Interface

At the outset I must start with a confession—I am not technology-oriented in my thinking although I am not technology-challenged. I lack the inherent curiosity that marks a scientific mind, my own thinking being far better aligned to the more prosaic elements such as poetry and well-written prose. A beautifully constructed sentence makes my heart burst in joy and wonderment, along with the sobering thought that it was not I who crafted that beauty. All this despite having been a professional fighter pilot for 21 years of active service; and having studied ‘Higher Maths’ successfully to keep up with the demands of the profession, competently, but without the intrinsic joy that such studies should automatically bring.

My heart has always been rooted in humanities, a stream of study within which I have revelled for the past 30 years and more, after proverbially hanging up my flying gloves. Humanities traditionally encompass those disciplines of study that treat human culture, society, experience, and perception as objects of study, while treating a human being as a knowledgeable subject. It is an expression of the human mind and its various expressions, which means that it is as inexact as any endeavour undertaken by humans.  

Being a part-time academic—with an affiliation to a renowned University as an Adjunct Professor—it seems that I have come full circle vis-à-vis technology. The latest phenomenon is the emergence of AI in teaching and learning. Ever since I first read a smartgpt generated (written?) essay, I have been thinking about its implications on the education process; on how students learn, and how institutions of higher education would have to evolve in their teaching journey.

The following analysis is not a technical take on AI but merely my personal appraisal of the concept of higher education in humanities and how it is likely to evolve with the adoption, and adaption, of new and emerging technologies into the realm of its delivery and acceptance. The other side of the coin is that it is way beyond my competence to comment on the STEM part of education, which has therefore been left untouched. I am acutely aware that this is the elephant in the room.

To start with, there is no doubt that the future progression of higher education is intrinsically connected to emerging technologies and computing capacities of the intelligent machines. Advances in AI opens new possibilities and challenges to both teaching and learning with the potential to fundamentally change the governance and internal architecture of the institutions involved. Any discussion of AI aimed at understanding its nuances and potential, invariably elicits the basic question: What is AI?  

From a philosophical standpoint, the question has been posed since the time of Aristotle and even today there is little agreement on a definition. The difficulty arises because AI cannot be equated to a purely cognitive function. Such an approach would limit the perspective of AI since it would ignore the psychological, political, moral, ethical, and myriad other elements within the concept of intelligence. Without going into the technological aspects of AI, a definition proposed by some senior researchers broadly fit its relation to higher education. They define AI as computing systems that are able to engage in human-like processes such as learning, adapting, synthesising, self-correction, and use of data for complex processing tasks.

Before going further into the AI–higher education interface it is necessary to state for the sake of clarity that, at least for the time-being AI is not general but narrow—it is task specific. Developments that are taking place are still far from creating machines that could face and carryout multiple tasks; although, considering the pace of development, for how long this status quo would remain is, itself, a matter of considerable debate.

Into the third decade of the 21st century, accelerated developments in AI have provided consistent evidence that it opens new horizons of possibilities to both teaching and learning in institutions of higher education. They bring exceptional opportunities as well as equally extraordinary risks. It is important to emphasise here that currently, and perhaps years into the future, the limits of technology will not permit AI to fully replace ‘teachers’—on the other hand, it is already on the cusp of being able to augment them. The above assertion is based on education, of all types, being a human-centric endeavour and is highly unlikely to become fully susceptible to a technology-centric solution.

In the field of higher education, despite the rapid advances being made in the field of AI, it is still accepted that the concept of sole reliance on technology is flawed, and indeed dangerous. The importance of maintaining a balanced focus on human–AI interaction and collaboration is repeatedly stressed. This means humans must identify the problems and associated risks, while posing critical questions on control of privacy and creativity. At the same time sufficient leeway must be provided for the development of new, and even unexpected, paths to teaching and learning. Building educated minds is one of the basic goals of higher education—therefore it is imperative to maintain a healthy scepticism regarding the role of AI in information recollection considered for long a cornerstone for the creation of an educated mind. The need for a ‘balanced focus’ has never been greater.

Although it has been around for more than 30 years, in the past five years or so, the use of AI in higher education has risen rapidly with the proliferation in the availability of affordable AI tools to both students and instructors alike. However, there is no clarity regarding the advantages that can accrue across the board to make its impact on higher education meaningful.

AI must enhance human thinking and augment the education process, while ensuring that the ‘whole’ is not reduced to a pre-scripted procedure for content delivery, corrections, and assessment. Institutions must be ever vigilant to ensure that AI solutions do not monopolise or corrupt the process of ‘education’. This aspect of governance assumes critical importance because the AI process, by virtue of its extreme technological sophistication, tend to unintentionally lack transparency regarding its creation and employment. Higher education institutions must ensure that transparency is not masked intentionally by treating it casually as normal, a natural arrangement to be accepted as the norm in the internet era.

Higher learning withers when freedom of thinking and inquiry is suppressed in any form. Similarly, information manipulation and knowledge limitation distort, and in extremis, negate in-depth analysis and advancement of knowledge. If institutions succumb to the repeated homily that, ‘transparency is not possible because of technological complexities’, control of higher education will shift to incompetent hands. The ethos of education and future knowledge development will become bleak. Lack of transparency in any educational process is unacceptable. The risks of accepting such a situation are far too great to be overlooked—they need careful and courageous analysis and rebuttal.  

[Part II will look at how the inevitable rise of AI can augment higher education, provided concerted attempts are put in place to mitigate and minimise the pitfalls that accompany the employment of AI.] 

Sanu Kainikara

© [Sanu Kainikara] [2023]
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About Sanu Kainikara

Sainik School Kazhakuttam (Kerala), National Defence Academy 39/A, 108 Pilot's Course IAF, fighter pilot, QFI, FCL, psc, HACC, Voluntary Retirement as Wing Commander. Canberra-based Political and Defence Analyst specialising in military strategy, national security, and international politics. PhD in International Politics from University of Adelaide Executive Masters in Public Adminsitration (ANZSOG) Adjunct Professor, University of New South Wales, Distinguished Fellow Institute For Regional Security (IFRS) Distinguished Fellow Centre for Air Power Studies (CAPS)

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