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This paper explores the question of whether the identification of many wrongdoings in an organisation requires knowledge of the technical and operating mechanisms of that organisation. If such is the case, many ethical problems cannot be resolved by a generalist. They must be left to people with knowledge of that industry. In attempting to answer the question, the paper examines 11 different types of organisations. It then asks how the ethical issues in those organisations might be resolved. The organisations are veterinarians, pharmacies, media companies, engineering firms, doctors, general businesses, including two sub disciplines, marketing and accounting organisations, nursing institutions, political parties, scientific research organisations, legal firms and information technology companies. Each can be a small professional company, locally based, or a large organisation, possibly international. Each exhibits one or more ethical problems that are not easily resolved by accepted ethical theory. Accepted theory, as further defined in the text, is the mainline ethical theories that would be core components of most ethics texts or courses. The question arises then on how would ethics be taught if the ethical issues require specialised knowledge of that industry sector. After examining the 11 industries, the paper puts forth two views. One is that a number of wrongs can be identified in industries and organisations where the ethical problems are complex and difficult to resolve, and where the standard ethical theories are of little or no help. Resolving these issues requires action from the organisation, or from the industry association encompassing all companies within that sector. A further complication has developed in the near explosive growth in whistleblower protection systems. These systems, now introduced in close to 30 countries around the world, have their own lists of wrongdoings for which the whistleblower will receive administrative and legal support. These lists of wrongs are distinct from any moral theory One conclusion to be drawn is that new methods possibly need to be found for teaching the identification and resolution of ethical issues. A second is a consequence of the first – that the teacher of ethics in these courses has to be drawn from within the industry. Further questions then arise: One is whether this demand then requires that this industry specialist learn moral theory? A second is then how would generalist applied ethics causes be taught (in humanities departments for instance)? Alternate viewpoints on joint teaching by a moral specialist and an industry specialist have been put forward. The paper puts forward one possible approach for the industry courses – that the industry specialist has to present the course, with new methods and content, but that a theoretical content is taught by someone knowledgeable in ethical theory. For generalist courses, the moral theorist has to include a sufficiently wide sample of industry and organisational ethical issues to ensure that students are aware of the wide range of ethical concerns that can arise, as well as approaches to resolving them.

Background: Artificial intelligence (AI) is a booming sector that has profoundly influenced every walk of life, and the education sector is no exception. In education, AI has helped to develop novel teaching and learning solutions that are currently being tested in various contexts. Businesses and governments across the globe have been pouring money into a wide array of implementations, and dozens of EdTech start-ups are being funded to capitalise on this technological force. The penetration of AI in classroom teaching is also a profound matter of discussion. These have garnered massive amounts of student big data and have a significant impact on the life of both students and educators alike.

Purpose: The prime focus of this chapter is to extensively review and analyse the vast literature available on the utilities of AI in health care, learning, and development. The specific objective of thematic exploration of the literature is to explicate the principal facets and recent advances in the development and employment of AI in the latter. This chapter also aims to explore how the EdTech and healthcare–education sectors would witness a paradigm shift with the advent and incorporation of AI.

Design/Methodology/Approach: To provide context and evidence, relevant publications were identified on ScienceDirect, PubMed, and Google Scholar using keywords like AI, education, learning, health care, and development. In addition, the latest articles were also thoroughly reviewed to underscore recent advances in the same field.

Results: The implementation of AI in the learning, development, and healthcare sector is rising steeply, with a projected expansion of about 50% by 2022. These algorithms and user interfaces economically facilitate efficient delivery of the latter.

Conclusions: The EdTech and healthcare sector has great potential for a spectrum of AI-based interventions, providing access to learning opportunities and personalised experiences. These interventions are often economic in the long run compared to conventional modalities. However, several ethical and regulatory concerns should be addressed before the complete adoption of AI in these sectors.

Originality/Value: The value in exploring this topic is to present a view on the potential of employing AI in health care, medical education, and learning and development. It also intends to open a discussion of its potential benefits and a remedy to its shortcomings.

Various achievements of Australia in the field of applied ethics from the 1980s to 2016 are outlined. The review covers academic scholarship, research and teaching; the ethics of business and actions to build ethics into the structures of enterprises. This follows the 3-fold categorization developed by De George (2012). A brief account of the formation and history of the Australian Association for Professional and Applied Ethics is included, as is a selection of scandals involving Australian organisations. Australia is shown to have made a significant contribution to the academic discipline of applied ethics and to have been aware of its position, distant from the English-speaking West and in the midst of nations of the global south.

Although risks are present in any organisation and the importance of their study is obvious, the authors find that risk analysis is an area still in its infancy, as reflected in the small number of existing publications on this topic. Human resources tend to understand risk in an elementary way. The ability of human resources to perceive risk is the ability and competence to identify a potential threat that does not always appear.

Aim: The aim of the this chapter was to provide additional knowledge on human resource competencies, in order to avoid the emergence and spread of risks at the organisational and cyber level.

Methodology: The authors used the quantitative–comparative analysis, by presenting all the details regarding the competencies of the human resource in order to manage the risks at organisational and cybernetic level.

Findings: The findings of this chapter show that the compulsory competencies of the human resource influence both the general competencies and the special competencies: information technology and communications, security ethics and economic ones. These, in turn, can improve or diminish cyber security competencies by almost 50%.

Originality of the Study: This study is highlighted by results obtained from the analysis of the capacity of human resources, to integrate theoretical knowledge and practical competencies on the perception of cyber risk. Of particular importance for this research are the analysis of data and the interpretation of results on human resources competencies. In this sense, throughout the chapter are assessed the skills of human resources, necessary for the management of cyber risks at the organisational level. In terms of future research implications, it could be important research to identify a method of assessing the competencies acquired by human resources applied from the perspective of cyber risk.

A Novartis social business in India completely separated the activities of its social and business units—the former engaging in raising the health awareness of villagers and encouraging them to visit free health camps, while the latter developed affordable medicine delivered directly to village pharmacies. Connections between these units were made through open and fluid market-type mechanisms, and by appealing to the needs and interests of villagers with incentives. This synchronized business model was developed partly because Novartis believed in villagers' self-initiated behavior for health improvements, which made it not interfere into marginalized institutions, and more significantly because it used its internalized control and coordination systems with clear goals of social contribution in operating the business unit. Consequently, Novartis achieved economies of scale, business sustainability, and social contribution.