THE CONCEPT OF BASIC INCOME IN THE BRITISH POLITIAL CONTEXT

The article explores the current debate on basic income in the UK. The growing interest in this concept, which implies the introduction of unconditional and equal for all regular cash payments, is caused by problems common to Western European countries, i.e. an increase in income inequality, the risk of technological unemployment, as well as the need to take urgent measures to support the population at times of pandemic. In the British context, however, ideological and political factors play a significant role, such as a rich intellectual tradition of developing universal approaches to social security and the desire of a number of parties, both national and regional, to use this increasingly popular concept for their own political purposes. It is concluded that in the medium term, the UK's transition to basic income is unlikely, but the very discussion on its introduction can serve as a catalyst for serious social transformations.

Artificial Intelligence and Labor Productivity Paradox: The Economic Impact of AI in China, India, Japan, and Singapore

Artificial intelligence is designed to generate technologies that potentially increase productivity and economic welfare. This study analyzes the relationship between GDP and high-technology exports, GDP per person employed, and unemployment rate in China, India, Japan, and Singapore. Recent concerns on technological unemployment claim that artificial intelligence disrupts the labor market which decreases employment over time. Using the multiple regression analysis, this study proved that Japan comparatively has better utilization of AI and labor productivity as all independent variables show significance to the GDP. Labor productivity in all countries is positively related to GDP. However, China and India showed signs of improper AI utilization as technological unemployment occurred. The unemployment rate in China is insignificant to its GDP, while India's unemployment rate is positively related to GDP, hence the jobless growth. In Singapore, the insignificance of high-tech exports to GDP is due to its lack of R&D investments these recent years. The results suggest that AI escalates growth through proper utilization trade liberalization, as exercised by Japan, as it helps the economy to be open and flexible to various free trade agreements which facilitates technological progress and enables the opening of new markets for growth and expansion, especially of artificial intelligence, which attracts and encourage foreign direct investments that will cater technology transfer, creation of new jobs, and economic growth.

Effects of Deep Learning Technologies on Employment in the Field of Digital Communication Systems

There are significant challenges and opportunities facing the economies of the United States in the coming decades of the 21st century that are being driven by elements of technological unemployment. Deep learning systems, an advanced form of machine learning that is often referred to as artificial intelligence, is presently reshaping many aspects of traditional digital communication technology employment, primarily network system administration and network security system design and maintenance. This paper provides an overview of the current state-of-the-art developments associated with deep learning and artificial intelligence and the ongoing revolutions that this technology is having not only on the field of digital communication systems but also related technology fields. This paper will also explore issues and concerns related to past technological unemployment challenges, as well as opportunities that may be present as a result of these ongoing technological upheavals.

COMPETENCE CHALLENGES IN THE DEVELOPMENT OF ARTIFICIAL INTELLIGENCE IN POLAND

In the year 2021 we have witnessed publication of national strategy „Policy of Artificial Intelligence Development in Poland since 2020”, where it is underlined that „AI is an area where Poland has real chances to become one of leading countries at the international arena (…) main assets are: know-how, intellectual property and creative skills” (…) by the 2030 up to 40% of working time in Poland might be automated with the use of already existing technologies”. Those phenomena bring concrete challanges in order to adapt employees competences to modern, structurally changing labour market, which generates also a need for development of adequate tools to prevent „technological unemployment”. Those challanges are in particular addressed to the education system, with regard to continuing and informal areas. To meet those needs we have to take care of the competence growth (which is relatively more flexible to develop than qualifications) – both individually and in the systemic way. The aim of this article is to verify hipotesis that there is a need to change the model of shaping competencies occurring due to technological development and AI, starting from secondary schools (3, 4 NQF level), through Higher Education (5, 6 NQF) up to continuing education of employees (3–8 NQF levels). Authors, as a result of conducted theoretical analysis, propose new competence-based model called „HUN” (Hybryd&Unconventional), which can support systemic education in uncertain times.

Impact of Industry 4.0 and Digitization on Labor Market for 2030-Verification of Keynes’ Prediction

The research objective of this study is to examine the changes in technological unemployment and to evaluate Keynes’ theory based on a literature analysis concerning the fourth industrial revolution. The methodology used in this study is a literature analysis of 86 papers published between 2011 and 2020 on topics related to Industry 4.0, the labor market, and technological unemployment. The change caused by the labor market raises employment sustainability issues. Among the goals adopted at the 2012 UN Rio+20 Conference on Sustainable Development, this study is directly related to goals 8 and 9, and indirectly to goal 10. Research evidence suggests that the impact of Industry 4.0 processes will reduce the amount of labor needed, bringing us closer to Keynes’ vision of three hours a day. The analysis suggests that reduced working hours will increase economic efficiency through more intensive work. The literature is used to determine whether the trend of reduced working hours can be interpreted as a positive or negative phenomenon. The extent of technological unemployment is determined by the digitalization strategy of each country and the speed of its introduction, as well as the readiness of the education system in a given country to retrain vulnerable groups in the labor market. However, the overall picture is positive: on the one hand, digital transformation opens up a wide range of opportunities for a more human life, and on the other hand, from an economic point of view, digitalization will become an inescapable element of competition by reducing marginal costs. The study’s novelty is that the effects of Industry 4.0 and technological unemployment on the labor market are analyzed in the context of Keynes’ theory.

Visions of Automation: A Comparative Discussion of Two Approaches

In recent years, fears of technological unemployment have (re-)emerged strongly in public discourse. In response, policymakers and researchers have tried to gain a more nuanced understanding of the future of work in an age of automation. In these debates, it has become common practice to signal expertise on automation by referencing a plethora of studies, rather than limiting oneself to the careful discussion of a small number of selected papers whose epistemic limitations one might actually be able to grasp comprehensively. This paper addresses this shortcoming. I will first give a very general introduction to the state of the art of research on potentials for automation, using the German case as an example. I will then provide an in-depth analysis of two studies of the field that exemplify two competing approaches to the question of automatability: studies that limit themselves to discussing technological potentials for automation on the one hand, and macroeconomic scenario methods that claim to provide more concrete assessments of the connection between job losses (or job creation) and technological innovation in the future on the other. Finally, I will provide insight into the epistemic limitations and the specific vices and virtues of these two approaches from the perspective of critical social theory, thereby contributing to a more enlightened and reflexive debate on the future of automation.

Understanding Technological Unemployment: A Review of Causes, Consequences, and Solutions

Many studies have focused on estimating the impact of automation on work around the world with results ranging widely. Despite the disagreement about the level of impact that automation will have, experts agree that new technologies tend to be applied to every economic sector, thus impacting work regardless of substituting or complementing it. The purpose of this study is to move on from the discussion about the size of the impact of automation to understanding the main social impacts that automation will cause and what actions should be taken to deal with them. For this purpose, we reviewed literature about technological unemployment found in Scopus and Web of Science published since 2000, presenting an academic view of the actions necessary to deal with the social impact of automation. Our results summarize causes, consequences, and solutions for the technological unemployment found in the literature. We also found that the literature is mainly concentrated on the areas of economy, sociology, and philosophy, with the authors situated in developed economies such as the USA, Europe, and New Zealand. Finally, we present the research agenda proposed by the reviewed papers that could motivate new research on the subject.

Against robot taxes: scrutinizing the moral reasons for the preservation of work

A recent political proposal to address the challenge of technological unemployment suggests that the state should impose a tax on labor-replacing technologies. The idea is to preserve jobs by disincentivizing automation. In this article, I critically assess the proposal from an ethical perspective. I show that, with respect to conceptions of distributive justice, it is unclear that precluding consumers’ potential real-income gains from automation can be justified. But foremost, I examine the moral ideal behind the normative claim to preserve labor. I show that the arguments in favor of a robot tax rely on doubtful moral convictions on the value of work and I conclude that a moral basis for imposing a robot tax is subject to justified scrutiny.

Two sides, but not of the same coin: digitalization, productivity and unemployment

PurposeThis paper aims to examine how input from the digital restructuring of the workplace and productivity affects the risk of job loss and unemployment.Design/methodology/approachRelying on the concepts of technological unemployment and the productivity paradox as well as the theory of skills-biased technological change, the analysis incorporated micro-level individual determinants of job loss, macro-level economic determinants of input and the contribution from traditional (machinery and equipment) vs innovative (ICT) factors of production. The model has been also controlled for “traditional” indicators of “outsiderness” in the labour market. The Quality of Work Life Survey, which is a broad-based national interview survey produced by Statistics Finland, for 2018, the latest year available (N = 4,110) has been used in the analysis. Binomial logistic regression has been applied in order to estimate the effects of individual- and macro-level factors on the risk of job loss.FindingsThe results support arguments for the divergence between effects from labour- vs total-factor productivity on the risks of job loss, as well as the divergence between effects for temporary (layoff) vs permanent job loss (dismissal or unemployment). While the contribution from “traditional” factors of production to labour productivity potentially decreases the risk of permanent job loss, input from “innovative” factors of production on total-factor productivity potentially causes adverse effects (e.g. growing risks of permanent job loss).Originality/valueThe paper contributes to the theoretical discussion about technological unemployment and productivity by means of including two different concepts into a single econometric model, thus enabling examination of the research problem in an innovative way.