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The aim of this paper is twofold: to explore the significance and implications of the rise of AI technology for the field of tertiary education in general and, in particular, to answer the question of whether teachers can be replaced by intelligent AI systems such as androids, what that requires in terms of human capabilities and what that might mean for teaching and learning in higher education.

Given the interdisciplinary nature of this conceptual paper, a literature review serves as a methodological tool to access data pertaining to the research question posed in the paper.

This exploratory paper gathers a range of evidence from the philosophy of mind (the mind-body problem), Kahneman’s (2011) System 1 and System 2 models of the mind, Gödel’s (1951) Two Incompleteness Theorems, Polanyi’s (1958, 1966) theory of tacit knowing and Searle’s (1980) Chinese Room thought experiment to the effect that no AI system can ever fully replace a human being because no machine can replicate the human mind and its capacity for intelligence, consciousness and highly developed social skills such as empathy and cooperation.

AI is rising, but there are inherent limits to what machines can achieve when compared to human capabilities. An android can at most attain “weak AI”, that is, it can be smart but lack awareness or empathy. Therefore, an analysis of good teaching at the tertiary level shows that learning, knowledge and understanding go far beyond any quantitative processing that an AI machine does so well, helping us to appreciate the qualitative dimension of education and knowledge acquisition. ChatGPT is robotic, being AI-generated, but human beings thrive on the human-to-human interface – that is, human relationships and meaningful connections – and that is where the true qualitative value of educational attainment will be gauged.

This paper has provided evidence that human beings are irreplaceable due to our unique strengths as meaning-makers and relationship-builders, our capacity for morality and empathy, our creativity, our expertise and adaptability and our capacity to build unity and cooperate in building social structures and civilization for the benefit of all. Furthermore, as society is radically automated, the purpose of human life and its reevaluation will also come into question. For instance, as more and more occupations are replaced by ChatGPT services, more and more people will be freed up to do other things with their time, such as caring for relatives, undertaking creative projects, studying further and having children.

The investigation of the scope and limitations of AI is significant for two reasons. First, the question of the nature and functions of a mind becomes critical to the possibility of replication because if the human mind is like a super-sophisticated computer, then the relationship between a brain and mind is similar (if not identical) to the relationship between a computer as machine hardware and its programme or software (Dreyfus, 1979). [ ] If so, it should be theoretically possible to understand its mechanism and reproduce it, and then it is just a matter of time before AI research and development can replicate the human mind and eventually replace a human teacher, especially if an AI machine can teach just as intelligently yet more efficiently and economically. But if AI has inherent limitations that preclude the possibility of ever having a human-like mind and thought processes, then our investigation can at least clarify in what ways AI/AGI – such as ChatGPT – could support teaching and learning at universities.

Artificial intelligence (AI) is intelligence displayed by machines, in contrast with the natural intelligence (NI) displayed by humans and other animals. It is also known as machine intelligence (MI) and is used because a machine mimics the cognitive functions that humans associate with human ability, such as logical reasoning, learning, and problem-solving. From Facebook’s automatic tagging suggestions to driverless cars, AI is rapidly progressing, and therefore, the ethical and moral question now is not whether AI should exist or not. AI exists and is already helping in improving various aspects of life such as health, safety, convenience, and overall standard of living. AI can replace or substitute routine mechanical, repetitive, boring jobs to free and unleash human creative and innovative talent to big thinking projects and humanizing work and society. AI can provide digital assistance in routine day-to-day tasks, detect cancer, diagnose rare diseases, and even prevent car crashes. AI can replace jobs, however, but not human work. Work as a duty, self-actualization and destiny will always continue, if not on the shop or office floors or boardrooms, at home, gardens, places of prayer and worship, and labs of creativity and innovation, in society and civilizations. While AI may indirectly free human talent for more meaningful and creative work, it can rarely participate in higher purposes such as creating bonding and belonging groups, in creating forgiving and compassionate communities, in drumming up small business, startups and corporations, and in harmonizing and humanizing this planet and cosmos for bliss or happiness. This chapter on AI, while investigating its market turbulence, will go beyond the legal aspects to ethical, moral, and spiritual dimensions and sacred opportunities of AI.

Contemporary Anglo-American economics, which I admire, faces two major obstacles. First, in its drive at least since Milton Freedman to be a positive science free of normative issues, it ignores its own current intellectual foundations buried at the heart of its analysis of the “advantages of trade”: Fairness. Second, the major driver of economic growth in the past 50,000 years has been the explosion of goods and production capacities from perhaps 1,000 to 10,000 long ago, to perhaps 10 billion goods and production capacities today. Economics, lacking a theory for this explosion, deals with this explosion by ignoring it and treating it as “exogenous” to its theory.

The “Edgeworth Box” carries the heart of advantages of trade, demonstrating for properly curved isoutility curves a region where you and I are better-off trading some of my apples for some of your pears. The ratio of these in trade constitutes price. But spanning the region of advantages of trade is the famous CONTRACT CURVE, where we have exhausted all the advantages of trade. Different points on the curve correspond to different prices. But the Contract Curve is Pareto Optimal, motion on the curve can only make one of us better-off at the expense of the other. Critically, economics has NO THEORY for where we end up on the Contract Curve. Nor, since different points on the curve correspond to different prices, can PRICE settle the issue.

Using the Ultimatum Game I will show that FAIRNESS typically drives where we settle on the Contract Curve, as long as we do not have to trade with one another. Thus ethics enters economics at its foundation, yet cannot be mathematized, so is ignored in Freedman’s name of a positive science.

Perhaps more important, unlike physics, no laws entail the evolution of either the biosphere or the “econosphere.” There are no laws of motion whose integration would entail that evolution. Lacking an entailing theory of the growth of the economy in diversity, often of new goods and production capacities, economists ignore the most important feature of economic growth, wrongly treating it as “exogenous.”

The failures above are likely to play major roles in the lapse to mere greed in our major financial institutions, and in our inadequate capacities to help drive growth in much of the poverty-struck world.

This chapter critically reviews the literature on authentic leadership (AL) that emerged in response to scandals in private- and public-sector organisations, drawing on theories, concepts and methods from other disciplines. The author finds that AL lacks a consensus definition, and that quantitative research has largely been at the level of employees rather than executives or board members. The review reveals 12 categories of criticisms. Schaefler advocates inductive qualitative research on the major concerns of executive leaders and means of addressing them via group dynamics, maintaining that exploring processes of AL in real-world settings would complement existing quantitative research and contribute to the development and extension of AL theory.

In the last four years, since Volume I of this Bibliography first appeared, there has been an explosion of literature in all the main functional areas of business. This wealth of material poses problems for the researcher in management studies — and, of course, for the librarian: uncovering what has been written in any one area is not an easy task. This volume aims to help the librarian and the researcher overcome some of the immediate problems of identification of material. It is an annotated bibliography of management, drawing on the wide variety of literature produced by MCB University Press. Over the last four years, MCB University Press has produced an extensive range of books and serial publications covering most of the established and many of the developing areas of management. This volume, in conjunction with Volume I, provides a guide to all the material published so far.

A well known feature of insurance systems is that they reduce incentives to avoid loss. This feature is known as moral hazard. Unfortunately the term has normative overtones; this is particularly unfortunate in the present application to industrial injury insurance since the conclusions can lead to very different welfare conclusions. The term has, in fact, been used in the normative sense to describe behaviour which is considered morally improper or even illegal [l]. However, a more useful interpretation for current purposes simply describes the behavioural effects of insurance cover and their effect on loss experience. This paper examines, in the neutral sense, the disincentive effects of the National Insurance injuries scheme on absence from work.