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A wave of technological change in the first decades of the twenty-first century is prefiguring a fundamental restructuring of society. Key among the driving forces behind such change are powerful technologies with the potential to exert major transformations on a range of human activities and, crucially, to do so without direct human intervention. The technologies collectively referred to as Artificial Intelligence, or AI represent a productive lens through which to investigate two interrelated transformations: the emergence of self-driving cars and the coming shifts in education. This is in particular because AI’s versatility has led it to be directly applied (and increasingly valued) both in new automated driving technologies, and in the development of new forms of instruction. From the educational perspective, this means that the same technologies that are transforming workforce conditions are also reshaping – directly and indirectly – the approaches, objectives, and experiences of students and educational institutions. This chapter lays out how these twin transformations are likely to play out in the case of the automotive industry and the educational pathways of two occupations closely associated with it: automotive engineers and repair technicians. Two key arguments underpin this examination. First, educational programs for these two occupations, (and beyond) should be broadened to develop versatility and adaptability through tools and perspectives that allow people to move vertically within organizations and laterally across industries in the face of rapid technological change. Second, these educational programs must explicitly tackle AI and the coming technological revolution from a variety of dimensions that connect technical skills acquisition with the context on how these technologies are incorporated in society, how they are governed, and what are the various responses to them. This will allow students and professionals to navigate a rapidly changing labor landscape better while endowing them with the vocabulary to actively participate in the debates that shape its construction.

The purpose of the chapter is to focus on the global industrial robotics market and trends of its development. In the framework of this chapter, the authors made the forecast of industrial robots' market future values in this chapter with the linear regression method and an econometric model. This analysis has provided a conclusive answer to the question about the prospects of the industrial robotics market and the leading countries. The completed forecast showed that the global robotics market will continue to grow, thanks to the wider adoption of industrial robots, which will be used in new industries, the development of contactless user interfaces, which, among other things, will be implemented in the automotive applications, the focus on predictive maintenance and remote monitoring of equipment, as well as the transition of a large number of enterprises to digital management and full automation of existing equipment to improve the quality and productivity of processes. The authors show that in 2020 the global robotics market volume decreased due to the COVID-19 pandemic and major shift in production value chains, but in 2021 the indicator will grow again, but not so rapidly, at a more moderate pace. By 2025, the global industrial robotics market may exceed $61.4 billion, with a growth rate of 8.5%.

Improved production with quality, safety, and security is the biggest challenge of the food industry. Modern technologies, including robotics and automation systems, can help to cope with such issues. This chapter gives a brief view of robotics and automation for the sustainable food industry along with packaging, warehousing, distribution, marketing, and consumer services. It describes the recently implemented solutions of robotic automation in different supply chain operations and various food commodities. The benefits of robotic and automation technology for perishable and semi-perishable items have also been covered. The present research may assist the food industry professionals, supply chain managers, and academicians in implementing automation and robotics in the food industry.

This paper is dedicated to the topic of the emerging challenges of traditional criminal law as posed by the development of modern technology. In certain parts of the world, the automotive industry has already implemented a new generation of autonomous self-driving vehicles. Moreover, there have been incidents where such vehicles have been involved in traffic accidents with deadly consequences. The use of autonomous intelligence is also emerging in other important sectors, such as in medicine and the military.

The issue of the legal liability of autonomous machines has been the subject of numerous philosophical debates and approached from the perspective of tort law. The question of criminal liability, however, has still not been debated more comprehensively. In this text, I will analyze the scope and limits of criminal liability of humans for criminal offenses “committed” by autonomous systems. Firstly, I will describe potential crimes of AI in context of intent and negligence. Secondly, I will propose the new concept of (shared) criminal liability, the concept I will name the Division of Labor theory.

Industry 4.0 has been identified as a key cornerstone to modernise economies where man and machines complement each other seamlessly to achieve synergies in decision-making and productivity for contributing to SDG 8: Decent Work and Economic Growth and SDG 9: Industry, Innovation and Infrastructure. The integration of Industry 4.0 remains a challenge for the developing world, depending on their current status in the industrial revolution journey from its predecessors 1.0, 2.0 and 3.0. This chapter reviews reported findings in literature to highlight how robotics and automated systems can pave the way to implementing and applying the principles of Industry 4.0 for developing countries like Mauritius, where data collection, processing and analysis for decision-making and prediction are key components to be integrated or designed into industrial processes centred heavily on the use of artificial intelligence (AI) and machine learning techniques. Robotics has not yet found its way into the various industrial sectors in Mauritius, although it has been an important driver for Industry 4.0 across the world. The inherent barriers and transformations needed as well as the potential application scenarios are discussed.

Purpose: To analyse the acceleration of artificial intelligence (AI) operations and robotic process automation (RPA) by comparing its market size and revenue worldwide during the pandemic and, measuring the impact of AI investment levels on jobs human resource functions, and analysing the role of AI in future work.

Design/Methodology: The archival data analysis technique is used to fetch data from sources like the Centre for Monitoring Indian Economy (CMIE), Statista, Deloitte, Mc Kinsey, Strata, Tractica, and IDC. Descriptive analysis with supporting literature has been contextually used for each objective which further establishes practical and theoretical implications of AI, intelligent process automation (IPA), and RPA in different industries during Covid-19 pandemic. This study analysed active scholarly articles from the Scopus database and presented results and findings.

Findings: The findings of the study state that emerging technologies such as AI, IPA, and RPA have a strong potential impact on market size, revenue, number of jobs, and investments levels during the pandemic. The global investment in AI is projected to witness an upsurge from 2018 to 2027, which significantly impacts the human workforce in various industries. The results of the study state that AI/RPA seems to be a crucial technological intervention, especially in times of the pandemic.

Originality/Value: This study contributes to the body of knowledge by constructing a base for understanding the pace of AI/RPA/IPA intervention and its significant impact on organisation process, structure, and people in different sectors. The timeline and forecast of this study intend to make industry consultants future to prepare to align themselves in an era of digital disruption.

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.