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This paper aims to specifically focus on the challenges that human resource management (HRM) leaders and departments in contemporary organisations face due to close interaction between artificial intelligence (AI) (primarily robots) and human workers especially at the team level. It further discusses important potential strategies, which can be useful to overcome these challenges based on a conceptual review of extant research.

The current paper undertakes a conceptual work where multiple streams of literature are integrated to present a rather holistic yet critical overview of the relationship between AI (particularly robots) and HRM in contemporary organisations.

We highlight that interaction and collaboration between human workers and robots is visible in a range of industries and organisational functions, where both are working as team members. This gives rise to unique challenges for HRM function in contemporary organisations where they need to address workers' fear of working with AI, especially in relation to future job loss and difficult dynamics associated with building trust between human workers and AI-enabled robots as team members. Along with these, human workers' task fulfilment expectations with their AI-enabled robot colleagues need to be carefully communicated and managed by HRM staff to maintain the collaborative spirit, as well as future performance evaluations of employees. The authors found that organisational support mechanisms such as facilitating environment, training opportunities and ensuring a viable technological competence level before organising human workers in teams with robots are important. Finally, we found that one of the toughest challenges for HRM relates to performance evaluation in teams where both humans and AI (including robots) work side by side. We referred to the lack of existing frameworks to guide HRM managers in this concern and stressed the possibility of taking insights from the computer gaming literature, where performance evaluation models have been developed to analyse humans and AI interactions while keeping the context and limitations of both in view.

Our paper is one of the few studies that go beyond a rather general or functional analysis of AI in the HRM context. It specifically focusses on the teamwork dimension, where human workers and AI-powered machines (robots) work together and offer insights and suggestions for such teams' smooth functioning.

The great filter and an unfriendly artificial general intelligence might pose existential risks to humanity, but these two risks are anti-correlated. The purpose of this paper is to consider the implications of having evidence that mankind is at significant peril from both these risks.

This paper creates Bayesian models under which one might get evidence for being at risk for two perils when we know that we are at risk for at most one of these perils.

Humanity should possibly be more optimistic about its long-term survival if we have convincing evidence for believing that both these risks are real than if we have such evidence for thinking that only one of these perils would likely strike us.

Deriving implications of being greatly concerned about both an unfriendly artificial general intelligence and the great filter.

This paper aims to analyse three decision-making approaches that involve humans and artificial autonomous agents, namely, human “in the loop”, “on the loop” and “out of the loop” and identifies the decision characteristics that determine the choice of a decision-making approach.

This is a conceptual paper that analyses the relationships between the human and the artificial autonomous agents in the decision-making process from the perspectives of the agency theory, sustainability, legislation, economics and operations management.

The paper concludes that the human “out of the loop” approach is most suitable for quick, standardised, frequent decisions with low negative consequences of a wrong decision by the artificial intelligence taken within a well-defined context. Complex decisions with high outcome uncertainty that involve significant ethical issues require human participation in the form of a human “in the loop” or “on the loop” approach. Decisions that require high transparency need to be left to humans.

The paper evaluates the decision-making approaches from the perspectives of the agency theory, sustainability, legislation, economics and operations management and identifies the decision characteristics that determine the choice of a decision-making approach.

Corporate Social Responsibility (CSR) research and practice have grown in preeminence over the past two decades. In corporations, global institutional frameworks (e.g. the Global Reporting Initiative, the United Nations Sustainable Development Goals) have guided and spurred the adoption and operationalisation of CSR strategies across industries and sectors. In academia, the business case for CSR seems to have been one of the main research foci towards the transition to more ethical and more responsible management. However, recent ecological and social disturbances (i.e. COVID-19 pandemic, global warming, etc.) have challenged our understanding of the role that CSR can play in this transition. In this chapter, we explore how the use and instrumentalisation of CSR practices in both academia and business have led not only to eroding the concept from its conceptual essence, but also to giving increased power and legitimacy to the very ailments that CSR was created to heal.

This chapter explores to what extent the Quantified Self, and in general the self-tracking culture, could be considered as a ‘technology of the self’: hermeneutical apparatuses generating new processes of subjectivation. Quantified Self, described by Wolf as a ‘self-consciousness through numbers’ (Wolf, 2010), refers both to the cultural phenomenon of self-tracking with devices and to a community of creators and users of self-tracking technologies. In this context, the author considers mainly the first aspect of this phenomenon and examines how its uses are diffused throughout the social mainstream. The author begins with the author’s own personal experience using self-tracking devices, then the author considers the phenomenon of self-tracking in relation to its historical context described by Floridi as the era of the ‘4^th Revolution’ (Floridi, 2014). The second part of the chapter deals with the theoretical framework. The author discusses the Quantified Self from the perspective of the Material Engagement Theory (Malafouris, 2013) in order to outline the genealogical and anthropological perspectives of the relationship between man and technology. The author concludes that man and technology have always had a biunivocal relation; man shapes technologies that shape man, both materially and cognitively. In the final part of the essay and through the lens of Foucault’s and Agamben’s theories, the author discusses the Quantified Self as a ‘technology of self’ to underline the ambiguous nature of the phenomenon and its social and biopolitical implication in the age of transparency (Han, 2015) and surveillance capitalism (Zuboff, 2019).

Truth matters; and the norms associated with a democratic society, such as the common good, responsibility, ethics, and civic engagement, are under attack with the emergence of the post-truth society. There are concerns worldwide that public education is failing us on pushing back on disinformation. Schools are not seen as developing skills that permit students to adequately differentiate truth from nontruths. In this context, the education system also faces some unprecedented challenges. The quality of education in most of the world is low, and only slowly improving. Also, future workers are concerned with automation's threat – or perceived threat – to jobs. In most countries, education systems are not providing workers with the skills necessary to compete in today's job markets. The growing mismatch between demand and supply of skills holds back economic growth and undermines opportunity. At the same time, the financial returns to schooling are high in most countries, and growing skill premiums are evident in much of the world. Schooling remains a good economic and social investment, and there are record numbers of children in school today. The skills that matter in the coming technological revolution are likely the same as what is needed in a media environment of disinformation. More and better education, and noncognitive skills, will not only prepare students for the future world of work; they will also prepare them to navigate the increasingly complex post-truth society. They will be able to detect fake news – or deliberate disinformation spread through news or online media. It will also allow young people to gain trust. In other words, better education is democratizing, to the extent that it promotes truth, values, and civic engagement.