(p.4) The history of technology is not only about the displacement of human labor by automation technologies. If it were, we would be confined to a shrinking set of old tasks and jobs, with a steadily declining labor share in national income. Instead, the displacement effect of automation has been counterbalanced by technologies that create new tasks in which labor has a comparative advantage. Such new tasks generate not only a positive productivity effect, but also a reinstatement effect—they reinstate labor into a broader range of tasks and thus change the task content of production in favor of labor. The reinstatement...

(p.10) [C]ontrary to a common presumption in popular debates, it is not the “brilliant” automation technologies that threaten employment and wages, but “so-so technologies” that generate small productivity improvements. This is because the positive productivity effect of so-so technologies is not sufficient to offset the decline in labor demand due to displacement.

(p.27) contrary to popular claims that the future of labour is threatened by “brilliant” new technologies, the greater danger for labour comes from technology that is not raising productivity sufficiently. In particular, if new automation technologies are not great but just “so-so” (just good enough to be adopted but not so much more productive than the labour they are replacing), there is a double jeopardy for labour—there is a displacement effect, taking passed away from labour, but no powerful productivity gains redressing some of the decline in labour demand generated by the displacement effects.

(p.29) Most AI researchers and economists studying its consequences view it as a way of automating yet more tasks. No doubt, AI has this capability, and most of its applications to date have been of this mould—for example, image recognition, speech recognition, translation, accounting, recommendation systems and customer support. But we do not need to accept this as the primary way that AI can be and indeed ought to be used. [...] Since AI is not just a narrow set of technologies with specific, pre-determined applications and functionalities but a technology platform, it can be deployed for much more than automation;...

(p.34) Overall, we cannot assess the net effect of artificial intelligence on labor as a whole, even in the short run. Instead, most applications of artificial intelligence have multiple forces that impact jobs, both increasing and decreasing the demand for labor. The net effect is an empirical question and will vary across applications and industries.

(p.47) For any given worker, a key predictor of whether artificial intelligence will substitute for their job is the degree to which the core skill they bring to the job involves prediction. Transcription jobs are being automated as the core skill of that labor is predicting which words to type upon hearing a recording. For London taxi drivers, when artificial intelligence was employed to predict the optimal route through the city’s streets, their jobs were put at risk (though other drivers’ labor became augmented). Artificial intelligence does not fit easily into existing analyses of the effect of automation on labor markets....

(p.4) Whether technological progress ultimately proves employment- or labor-share-displacing depends proximately on two factors: how technological innovations shape employment and labor’s share of value-added directly in the industries where they occur; and how these direct effects are augmented or offset by employment and labor-share changes elsewhere in the economy that are indirectly spurred by these same technological forces. The first of these phenomena—the direct effect of technological progress on employment and labor-share in the specific settings in which it occurs—is often readily observable, and we suspect that observation of these direct labor-displacing effects shapes theoretical and empirical study of the aggregate...

(p.6) Given that these technologies demonstrably succeed in their labor saving objective and, moreover, that we invent many more labor-saving technologies all the time, should we not be somewhat surprised that technological change hasn’t already wiped out employment for the vast majority of workers? Why doesn’t automation necessarily reduce aggregate employment, even as it demonstrably reduces labor requirements per unit of output produced? These questions underline an economic reality that is as fundamental as it is overlooked: tasks that cannot be substituted by automation are generally complemented by it. Most work processes draw upon a multifaceted set of inputs: labor and...

(p.26) Major newspaper stories offer fresh examples daily of technologies that substitute for human labor in an expanding—although still circumscribed—set of tasks. The offsetting effects of complementarities and rising demand in other areas are, however, far harder to identify as they occur. My own prediction is that employment polarization will not continue indefinitely (as argued in Autor 2013). While some of the tasks in many current middle-skill jobs are susceptible to automation, many middle-skill jobs will continue to demand a mixture of tasks from across the skill spectrum. For example, medical support occupations—radiology technicians, phlebotomists, nurse technicians, and others—are a significant...

(p.2) The fear of technological unemployment has been accompanying the great innovative waves. However, in the history of humanity, periods of intensive automation have often coincided with the emergence of new jobs, tasks, activities and industries. Indeed, the challenging question is related to the overall sign of the relationship between technological change and labor: is technology labor-friendly or is it labor-threatening?

(p.316) The underlying issue explored here concerns the implications of precarious work for individual workers – their physical, mental and social well-being and also, more broadly, their agency and the way in which they integrate paid work into other domains of social life. To what extent is the precariousness of work transmitted to the worker? This difficult but important area requires careful conceptualisation in order to extend research on precarious work and develop policies to combat its effects.

(p.6) As time progresses, artificial intelligent systems should become better and more flexible by incorporating changes in the academic culture and learning preferences of new generations of students (Baker, 2016). Robots are developing their human touch too. Robots that can recognize emotional states are currently in development (Azuar et al., 2019; Yu and Tapus, 2019). Only time will tell what robots with deep learning ability will be capable of, and whether they will be artificially intelligent and we anatomists remain naturally stupid. It is too early to say that anatomy educators are safe from losing their jobs to robots. However, this...

(p.2) This does not mean that machines will replace all labor or that wages will plummet across the board. Computers based on AI are remarkably effective in conducting specific tasks rather than replicating human intelligence. The early attempts to imitate humans in the 1970s derailed AI for decades. By contrast, the recent success of AI has been based on an algorithmic approach that uses neural networks and deep learning for well-defined and limited tasks.

(p.55) The enactment of some form of regulation to establish the proposed portability of benefits would already represent a positive step forward to ensure more dignified conditions for workers in digital labour markets; various analysts, however, consider it insufficient in view of the facts that earnings are at times too low in the absence of any minimum wage rules, the flow of work is unstable and no employment benefits exists, there are clear information and power asymmetries, no protection against privacy violations, and various forms of information or reputation-based ethnic and gender discriminatory mechanisms occur unregulated.

(p.116) AI software was developed to make computers that think logically and behave like humans. HRM has witnessed the efficiency and benefits of AI in the recruitment and hiring processes the ability of AI to adapt to the recruitment has increased rapidly over the last two decades. Recruitment still occurs through traditional methods but is assisted by AI tools and applications. The system helps automate different processes, making decision-making more effective and efficient. The use of AI has improved the hiring process for better quality. Now, HR managers have time to explore HR's bigger picture. Despite advances in technology, however, a...

(p.6535) Recent studies show that historical technology-driven trends may not capture the AI-driven trends we face today. Consequently, some have concluded that AI is a fundamentally new technology (3, 65). If the trends of the past are not predictive of the employment trends from current or future technologies, then how can policy makers maintain and create new employment opportunities in the face of AI? What features of a labor market lead to generalized labor resilience to technological change?

(p.6536) The impact of AI and automation will vary greatly across geography, which has implications for the labor force, urban–rural discrepancies, and changes in the income distribution. The study of AI and automation are largely focused on national employment trends and national wealth disparity. However, recent work demonstrates that some places (e.g., cities) are more susceptible to technological change than others. Occupations form a network of dependencies which constrain how easily jobs can be replaced by technology. Therefore, the health of the aggregate labor market may depend on the impact of technology on specific urban and rural labor markets.

(p.125) the rapidly growing lousy jobs are all ones where it has proved difficult to substitute machines or computers for human labor.

(p.8) Income inequality is not directly affected by technology, but it is a combination of both technology changes and the working position of the workers. The relationship between AI and income distribution has always been considered negative and this is what has been observed in this study and it directly affects the distribution of income and jobs. Due to automation, low and medium skill jobs are declining, and unemployment rate is increasing and the income gap between middle and high skill labor is increasing. Gini-coefficients of developing nations are higher than in developed nations, indicating that income inequality in developing nations...

(p.322) Many participants in recent public discussions about the coming workforce transformation focus only on the economic sustenance of displaced workers in our envisioned future society; there is a consensus on the need for a proper (re)distributive scheme to ensure societal stability. This will be some form of a basic income guarantee, usually defined as “an income paid by a political community to all its members on an individual basis, without means test or work requirement” (Van Parijs 2004, p. 8). In a similar manner, a “negative income tax” (people whose income is below some amount receive cash from the government...

(p.223) Again, workload and conditions (time schedule) as well as appreciations from managers, customers, fellow workers, and traffic participants are important for drivers.This could lead to the proposition that positive human–artificial collaboration may even be easier if AI application learn to accolade and praise human co-workers in any form in order to show some appreciation for their input. This could be implemented for example within voice communication between drivers and Ai applications

(p.226) Between ever-increasing expectations and requirements and real human competence levels a ‘gap’ is developing as required training for humans has for each and every person to start anew – learning cannot be automated for human workers: Longer education and training programmes are needed in order to arrive at required higher competence levels for a modern-day logistics and business environment. This constitutes a knowledge accumulation gap (grey field in Figure 2) that arises due to the fact that humans are not able to accumulate knowledge over generations – as opposed to machines and computers which are able to do so.

(p.350) measured productivity has increased rather slowly in recent years, even as the world seems to be captured by AI fever. If AIr elated innovations enter the economy at the same slow pace as suggested by recent productivity statistics, then the transition will be slower than, for example, the wave of mechanization in the 1950– 1970s, and the resulting disruptions may not be very significant. However, there are three possible alternatives: First, some suggest that productivity is significantly undermeasured, for example, because quality improvements are not accurately captured. The best available estimates suggest that this problem is limited to a few...

(p.353) In 1930 Keynes wrote an essay on the “Economic Possibilities of our Grandchildren,” in which he described how technological possibilities may translate into utility possibilities. He worried about the quality of life that would emerge in a world with excess leisure. And he thought all individuals might face that quandary. But what has happened in recent years has raised another possibility: innovation could lead to a few very rich individuals— who may face this challenge—whereas the vast majority of ordinary workers may be left behind, with wages far below what they were at the peak of the industrial age.

(p.185) Another key theme gleaned from the analysis was the psychological impact of technology adoption, particularly AI as it can be at the expense of people. A manager provides some further insight into the psychological elements management encounter: ‘They amass experience which gives them the edge, ability of a TM to look at a warehouse full of pallets to say, I need 15 people and 3 h to shift that… that is purely experience. We put a system in and a report can tell you that. That’s a massive hit for someone. That first barrier is biggest’. If AI and automation...

(p.10) Artificial intelligence has the power to change the nature of work for many people, but the pace of adoption and the extent of the disruption are still the subject of debate. A rapid adoption of autonomous self-driving vehicles, for instance, could dramatically displace millions of workers, but a more gradual and partial adoption, especially in a growing economy, will have far less impact on drivers.

(p.376) There is thus an issue of realizing the future and what form that future reality will really take. Futurists have adopted more and less positive accounts.10 The fourth industrial revolution too, includes a range of approaches. As we shall argue, however, there are significant commonalities and limits to the range. The important point at this stage is that positions are not irrelevant for how the future becomes the present, since they affect how the future will be shaped from the present. Clearly, this applies also to work and the future of work is a major focus of fourth industrial revolution...

(p.377) Formerly, automation and computerization had their greatest impact on Fordist continuous flow mass production lines and on clerical and secretarial work. That is, work that could be reduced to strictly repetitive actions or multiply reproducible essentially identical forms – some kinds of work whose primary task base could be expressed in simple routines. However, the new technology introduces combinations of mobility, monitoring/surveillance, discrimination, multi-functionality, language and effectively more complex decision making capacity (which is not to suggest this requires an AI be conscious). This greatly extends the range of tasks that could be duplicated by technology and thus the types...

(p.379) At root, Keynes highlights but does not resolve a tension based on two different framings of ‘need’. The need to interact, work and create as self-expression may be intrinsic to what it is to be human, but this is not the same as the need to earn a wage income in order to survive within a division of labour that operates according to disciplining principles or mechanisms. In this latter sense, labour is compelled and profit and accumulation drive the capitalist system. Historically, there is no simple relation where greater use of technology and higher productivity have continuously reduced hours...

(p.380) it is important to note that the world of tomorrow that Keynes is focused on in his essay is not ours. That world is not just one that has achieved technological wonders, it is one that has implicitly transitioned to a radically different socio-economic form of organization.

(p.390) Whilst a sense that technology can liberate the worker from work may now be on the agenda of left accelerationists at such venues as Labour Party fringe conference events (e.g. The World Transformed), the main policy focus remains 390 Economy and Society dominated by a more business oriented and conventional set of capitalist concerns with the growth and profitability of the firm. From this perspective, the concerns of workers, the sociology of work and the broader issues of technology in society, are peripheral or additional.

(p.391) The framing of policy, therefore, is not neutral. It absorbs the fourth industrial revolution concept according to market conforming logics that allow government to limit its responsibility for shaping the future, even as it continues to herald the potential. And this, of course, segues easily into the kinds of concerns and foci that consultancies, such as McKinsey, necessarily find most conducive to explore: investment as a corporate wealth generating and protecting exercise. To be clear, we by no means wish to suggest that a technological future will be dystopian nor that the future of work involves worse-case outcomes of rapid...

(p.109) Technological breakthroughs occur at an ever-increasing rate thereby revolutionizing human health and wellness care. Technological advancements have drastically changed the structure and organization of the healthcare industry. McKinsey Global Institute estimates that 800 million workers worldwide could be replaced by robots by the year 2030. There is already a robotic revolution happening in healthcare wherein robots have made tasks and procedures more efficient and safer. Locsin and Ito has addressed the threat to nursing practice with human nurses being replaced by humanoid robots. Routine nursing care dictated solely by prescribed procedures and accomplishment of nursing tasks would be best performed...

(p.366) In an adaptation of the orthodox Marxist understanding of the unfolding of capitalist development, the ‘human machines’ Hardt and Negri see as ‘put to work’ in contemporary capitalism represent what might be characterised as the ‘forces of production’ which push against the ‘relations of production’, namely, the property relations that conflict with the common, cooperative basis of value production in the digital age. As Hardt and Negri write, ‘Private property appears increasingly as a fetter to social productivity both in the sense that it blocks the relationships of cooperation that generate production and that it undermines the social relations that...

(p.367) The difference between Hardt and Negri’s negated dialectic of forces and relations and that found in orthodox Marxism is that, for the former, there is no promise of resolution or unification out of the social conflict and resistance that powers it, only ‘permanent crisis and continual imbalance’. This, it is fair to say, fool-proofs what was formerly, in Empire and Multitude, the sense that a new world was being built in the shell of the old, and were only it to be liberated from the relations constraining it, all would be well. Moreover, Hardt and Negri appear keen to distance...

(p.47) The question of working time has been central to the debate around the emergence and development of modern industrial society casting a mask of progress over our perception of the historical. Such a linear temporality appears reflected in Marx’s view of history as progression through the development of modes of production: primitive communism through feudalism and capitalism to communism. It may also be represented by the centrality of ‘labour time’ within his analysis where moves to a reduction of the working week – as in some general ethos of social progress - might seem the measure of improvement in working...

(p.49) The analysis of labour time as a commodity opens areas of understanding of conflicts and tensions made transparent through the idea of partial commodification with a different articulation of the subordination of labour to capital taking shape in the encroachment of the demands of commodified time into free time. In beginning to address this contradiction, we must note that a feature of the emergence of industrial capitalism – in the commodification of labour - took labour outside the domestic setting placing it spatially within the factory and in the office. It also located that labour temporally in the construction of...