AI and workplace relations: A WHS framework for managing relational risks in workplaces

Getting AI Right: Introductory Notes on AI & Society

Artificial intelligence (AI) has quickly become a transformational force that is reshaping several sectors and changing how work is done. Automating jobs is a crucial component of AI's effect. As artificial intelligence (AI) technology develops, it has the potential to automate operations that are now done by people, creating both possibilities and difficulties for the employment market. AI's influence on job automation has many different facets. However, automation powered by AI has the potential to improve many industries' productivity, efficiency, and accuracy. AI systems may be used to do repetitive and boring activities, freeing up human employees to concentrate on more important, creative, and strategic duties. Increased work satisfaction and creativity may result from this. Automation fueled by artificial intelligence has already had a substantial impact on sectors including manufacturing, shipping, and customer service. However, there are also worries regarding the displacement of human labor as a result of job automation. Certain predictable and regular jobs may be carried out more effectively by robots as AI technology develops. This may lead to changes in work patterns as well as job losses. Manual labor-intensive jobs and routine data processing tasks are especially susceptible to automation. Discussions regarding the future of work and the need of retraining and upskilling the workforce to stay relevant in an AI-driven economy have been triggered by concerns about widespread unemployment. While AI may automate certain employment tasks, it also increases the need for human labor and opens up new possibilities. Intelligent experts that can design, develop, and maintain these technologies are needed for the integration of AI systems. Data scientists, machine learning engineers, and AI experts are in high demand right now. New businesses and employment categories will develop as AI technology advances, highlighting the need of lifelong learning and adaptation in the workforce. Additionally, AI-driven automation may improve the quality and security of employment. Robots may be used to do hazardous and physically taxing activities, lowering workplace injury risk and creating safer working conditions for people. AI may help employees make decisions by giving them insightful information and enhancing their talents. Increased productivity and job satisfaction may result from collaborative work settings where humans and AI systems play to one other's strengths. The difficulties must be addressed by legislators, educators, and corporations in order to minimize the possible negative effects of AI-driven job automation. Investments in education and programs for lifelong learning may provide people the tools they need to adapt to a changing labor market. Governments may aid employees impacted by automation by supporting reskilling programmes and offering social safety nets. To guarantee ethical AI deployment and reduce prejudice and discrimination, laws and regulations must also be in place. In summary, the influence of AI on job automation is profound and intricate. While technology presents chances for improved effectiveness, productivity, and creativity, it also presents problems in terms of job displacement. It's critical to strike a balance between the advantages of automation and the necessity to assist and retrain the workforce. Societies can use AI to their advantage by fostering collaboration between people and AI systems, investing in education and skill development, and enacting thoughtful policies. This will result in a future where people and machines coexist peacefully and a more prosperous and inclusive economy.

Job crafting describes proactive employee behaviors to improve the design of their work and working conditions, and to adapt their job to better suit their abilities and needs. During organizational changes, employees may use job crafting to adjust to the changes in their work and protect their well-being and motivation, i.e., work engagement. However, research shows that although the effects of job crafting strategies that expand the design of work (approach job crafting) have been positive on work engagement, the effects of job crafting strategies that diminish the scope of work (avoidance job crafting) have often been negative. This study investigated the effects of the interactions between different job crafting strategies on work engagement, an aspect that has not thus far been studied. Specifically, we hypothesized that avoidance job crafting is not harmful for work engagement when it is conducted in combination with approach job crafting, particularly during times of organizational change. A two-wave, 18-month follow-up study was conducted among public sector workers who either experienced (n = 479) or did not experience (n = 412) changes in their work. Latent moderated structural equation modeling revealed that avoidance job crafting did not reduce work engagement when combined with approach job crafting behaviors. Moreover, job crafting best benefited work engagement when it was combined with these opposing strategies. However, job crafting was beneficial for work engagement only among employees who were affected by organizational changes, that is, among employees whose job design had changed. Practically, organizations implementing changes could encourage proactive job redesign approaches among their employees—particularly both approach and avoidance types of job crafting strategies.

Introduction This paper examines the major health threats and risks to employees in Ghana and some West African countries amidst the rapidly growing mining, metals, oil and gas industries. It looks at the role of key stakeholders, particularly academic health institutions in the evidenced-based management of occupational health to improve the health, productivity and performance of the working population. Methods The paper was developed from extensive literature review and interview of some industry leaders to understand some historical trends of employee occupational health promotion and protection indices and the current situation of occupational health and hygiene standards in the sub-region. Results Clearly, the present West African employee (local and expatriate) are heavily burdened with diverse kinds of health threats, both from the workplace and non-work-related sources. The threats and associated risks were noted to be hugely skewed towards infectious diseases and occupational health hazards origins. That notwithstanding, non-communicable diseases challenges, like mental health, hypertension, diabetes, cancers and musculoskeletal disorders had prominent place in the workplace health hazards and risks matrix. Discussion Academic health institutions in West Africa, despite having major roles to play in defining and managing occupational health hazards, were noted not to be actively engaged. Training of competent professionals to run workplace wellness, occupational health and hygiene programs in high-risk workplaces in developing countries, research to have evidence based problem definitions and efficient alternative solution pathways with maximum health outcome are all some of the roles falling in the domain of academic health institutions. Legislation and occupational standards development cannot be achieved without credible research evidence support – this was noted to be a huge gap in the West-Africa sub-Region. The way forward was identified as; key stakeholders working together using a systemic and systematic approach to progressively define and address workplace health problems to improve occupational health outcome. I am currently and IFAD medical advisor and have been in this role for the past 7 months as consultant. Prior to assuming this position, I was a UN volunteer as a medical officer providing occupational health, primary health and emergency medical services to the UN staff deployed in North Korea. This I did for 18 months with no salary, but only basic allowance to support my basic living allowance. Before moving to North Korea, I served in a similar capacity for 10 years in Ghana, DR Congo and Lebanon with basic remuneration. I am optimistic that, this provided valuable services to contribute to the identified and shared gap (by ICOH and ILO) of far less that 10% of developing countries employees receiving occupational health services consistent with workplace risks and hazards they face. It is out of this enormous amount of occupational health experience that I present this paper. Finally, my strive to attain the highest competence in occupational health made me register for MPH (Occupational and Environmental health) in Tulane University School of Public health and Tropical Medicine. New Orleans, USA. This is costing me over US$ 50,000.00. With this financial commitment already made, I would grately appreciate the requested waiver support to attend this all important ICOH 2018 Congress. My sharing of my over 10 years of occupational health experience in 5 different countries and 4 continents in the would add a rich flavour to the program.

PurposeThis study aims to explore the associations linking employees’ challenge-hindrance appraisals toward artificial intelligence (AI) to service performance while considering the dual mediating roles of job crafting and job insecurity, as well as the moderating role of AI knowledge.Design/methodology/approachA survey was administered to a sample of 297 service industry employees. This study examined all the hypotheses with Mplus 8.0.FindingsThis study confirms that challenge appraisal toward AI has an indirect positive influence on service performance via job crafting (motivation process), whereas hindrance appraisal toward AI has an indirect negative influence on service performance via job insecurity (strain process). Meanwhile, AI knowledge, serving as a key personal resource, could strengthen the positive impacts of challenge appraisal toward AI on job crafting and of hindrance appraisal toward AI on job insecurity.Practical implicationsOrganizational decision-makers should first survey employees’ appraisals toward AI and then adopt targeted managerial strategies. From the perspective of service industry employees, employees should adopt proactive coping strategies and enrich their knowledge of AI to meet the challenges brought by this technology.Originality/valueThe primary contribution of this study is that we enrich the literature on AI by exploring the dual mediators (i.e. job crafting and job insecurity) through which AI awareness affects service performance. Moreover, this study advances our understanding of when appraisals toward AI influence job outcomes by identifying the moderating role of AI knowledge.

Artificial intelligence in the work process. A reflection on the proposed European Union regulations on artificial intelligence from an occupational health and safety perspective

This paper examines the current state and potential future developments of Artificial Intelligence (AI) applications in Occupational Health and Safety (OHS) in Nigeria. OHS is a critical concern in the world and particularly in Nigeria, as workplace hazards pose risks to the health, safety, and well-being of workers. AI offers promising solutions to enhance hazard identification, risk evaluation, and control measures in OHS practices. The paper begins by providing an overview of AI, its subfields, and techniques commonly used in OHS. It then explores the real-time applications of AI in hazard identification, risk evaluation, and control measures, highlighting the benefits it brings to OHS practices. Furthermore, the paper discusses the challenges and considerations in adopting AI in Nigeria, including infrastructure limitations, skill gaps, and ethical concerns. Based on the analysis, four suggestion were proposed for Nigeria’s OHS context. These suggestions include investment in AI infrastructure and research, capacity building programs to develop AI expertise; collaboration between stakeholders, and the establishment of regulatory frameworks to ensure responsible AI deployment. By embracing AI in OHS, Nigeria can improve workplace safety, mitigate risks, and protect the health and well-being of its workforce.

Heat-related injuries in Australian workplaces: Perspectives from health and safety representatives

Purpose The research investigates how employees evaluate artificial intelligence (AI) technology adoption by organisations and indulge in performing innovative work behaviour (IWB) through the parallel mediation of job crafting and AI anxiety under the moderating effect of supervisor support for innovation. The study addresses a literature gap by uniting rational (job crafting) with emotional (AI anxiety) dimensions when understanding employee positive and negative reactions to AI implementation. Design/methodology/approach The research bases its findings on the transactional theory of stress and coping through a dual-mediator design. It utilises data from 308 employees selected through purposive sampling from Pakistan’s tech sector through a time-lagged survey design to interpret the results. Findings The research demonstrates that organisations must create environments that provide leadership support for innovation and the availability of appropriate resources because these reduce AI-related concerns while enhancing IWB. Challenge appraisals enable workers to actively redesign their tasks through job crafting, which improves their IWB. In contrast, hindrance AI appraisals lead to AI anxiety, which prevents risk-taking and skill development, limiting IWB. Practical implications The study provides organisations with helpful guidance about how to handle their AI-related operational changes. The research is aligned with sustainable development goals SDG 8 (decent work and economic growth) and SDG 9 (industry, innovation and infrastructure) by offering business leaders specific ways to use employees’ innovative capabilities during technological changes. Originality/value The research develops comprehensive theoretical knowledge about how cognitive and emotional aspects influence innovation in developing economies and how leaders’ support for innovation can foster employees’ IWB during AI transitions.

Artificial intelligence (AI) enhances employees’ work efficiency and significantly impacts their cognitive and psychological states. However, there remains limited research on the complex relationship between AI-driven changes in the work setting and employees’ job crafting. Therefore, this study applies the job demand–resource (JD-R) theory to test how AI awareness influences employees’ promotion- and prevention-focused job crafting. It further investigates the mediating roles of job insecurity and creative process engagement and the moderating role of AI knowledge. Based on the sample of 324 participants, the empirical results show that challenge appraisal toward AI indirectly promote promotion-focused job crafting through creative process engagement and inhibit prevention-focused job crafting through job insecurity. Conversely, hindrance appraisal toward AI indirectly promotes prevention-focused job crafting through job insecurity. Additionally, the positive effect of challenge appraisal on creative process engagement is strengthened by AI knowledge. Discussions are provided on both the theoretical and practical implications.

Artificial Intelligence (AI) is taking centre stage in economic growth and business operations alike. Public discourse about the practical and ethical implications of AI has mainly focussed on the societal level. There is an emerging knowledge base on AI risks to human rights around data security and privacy concerns. A separate strand of work has highlighted the stresses of working in the gig economy. This prevailing focus on human rights and gig impacts has been at the expense of a closer look at how AI may be reshaping traditional workplace relations and, more specifically, workplace health and safety. To address this gap, we outline a conceptual model for developing an AI Work Health and Safety (WHS) Scorecard as a tool to assess and manage the potential risks and hazards to workers resulting from AI use in a workplace. A qualitative, practice-led research study of AI adopters was used to generate and test a novel list of potential AI risks to worker health and safety. Risks were identified after cross-referencing Australian AI Ethics Principles and Principles of Good Work Design with AI ideation, design and implementation stages captured by the AI Canvas, a framework otherwise used for assessing the commercial potential of AI to a business. The unique contribution of this research is the development of a novel matrix itemising currently known or anticipated risks to the WHS and ethical aspects at each AI adoption stage.

Objective: This study investigates the mediating role of job crafting in the relationship between artificial intelligence (AI) awareness, servant leadership, and work engagement among employees.Methods: Utilizing quantitative analysis, the research involved surveying employees and employing structural equation modeling to test the proposed hypotheses regarding the influence of AI awareness and servant leadership on job crafting and work engagement.Findings: The results reveal that while servant leadership significantly enhances job crafting and work engagement, AI awareness does not positively impact job crafting. However, job crafting positively influences work engagement and mediates the effect of servant leadership on work engagement, indicating a complex interplay between leadership styles and employee engagement levels.Novelty: This study contributes to the literature by highlighting the differential impact of AI awareness and servant leadership on job crafting and work engagement, emphasizing the critical role of leadership in fostering employee motivation and productivity in the context of technological advancements.Theory and Policy Implications: The findings suggest that organizations should focus on developing servant leadership qualities among managers to promote job crafting and enhance employee engagement. Furthermore, while fostering AI awareness is essential, organizations must balance it with supportive leadership practices to prevent potential negative impacts on employee morale.

Amid the wave of digital transformation, the widespread adoption of artificial intelligence (AI) has become an unstoppable trend. An increasing number of organizations are embracing AI to boost efficiency, streamline processes, and enhance decision-making quality. However, while AI helps improve organizational performance, it also exerts a profound influence on employees’ professional attitudes and behaviors. Exploring the impact of artificial intelligence applications on employees' career commitment is crucial. Grounded in the person-environment fit theory, this study aims to investigate how AI usage influences employees' career commitment through the mediating role of job crafting and the moderating role of AI awareness. Based on an empirical analysis of two hundred and two survey responses, the study reveals that AI usage positively correlates with employees' career commitment. Job crafting mediates this relationship, enhancing the positive effect of AI usage on career commitment. Additionally, AI awareness functions as a moderator, negatively adjusting both the impact of AI usage on job crafting and the indirect effect of AI usage on career commitment through job crafting. The research findings not only deepen our understanding of the relationship between AI usage and employee career commitment, but also offer theoretical grounding and practical guidance for organizations seeking to manage employee uncertainty and negative expectations while advancing intelligent transformation.

PurposeThis study aims to explore whether, how and when leaders' artificial intelligence (AI) symbolization (i.e. the demonstration of leaders' acceptance of and support for AI by engaging in AI-related behaviors and/or displaying objects that reflect their affinity for AI) affects employee job crafting behaviors.Design/methodology/approachThe authors conducted two studies (i.e. an experiment and a multi-wave field survey) with samples from different contexts (i.e. United States and China) to test our theoretical model. The authors used ordinary least squares (OLS) and hierarchical linear modeling (HLM) to test the hypotheses.FindingsLeaders' AI symbolization is positively related to employee change readiness and, in turn, promotes employee job crafting. Moreover, employee-attributed impression management motives moderate the positive indirect effect of leaders' AI symbolization on employee job crafting via change readiness, such that this indirect effect is stronger when employee-attributed impression management motives are low (vs high).Practical implicationsLeaders should engage in AI symbolization to promote employee job crafting and avoid behaviors that may lead employees to attribute their AI symbolization to impression management.Originality/valueBy introducing the concept of leaders' AI symbolization, this study breaks new ground by illustrating how leaders' AI symbolization positively influences employees' change readiness, as well as job crafting in the workplace. Further, integrating AI as a novel and timely context for evaluating job crafting contributes to the literature where empirical research is relatively scant, particularly regarding the factors that prompt employees to engage in job crafting.

Artificial intelligence (AI) is revolutionizing occupational health and safety (OHS) by addressing workplace hazards and enhancing employee well-being. This review explores the broader context of increasing automation and digitalization, focusing on the role of human-AI interaction in improving workplace health, safety, and productivity while considering associated challenges. A narrative review methodology was employed, involving a comprehensive literature search in PubMed, Embase, and Scopus for studies published within the last 25 years. After screening for relevance and eligibility, a total of 52 articles were included in the final analysis. These publications examined various AI applications in OHS, such as wearable technologies, predictive analytics, and ergonomic tools, with a focus on their contributions and limitations. Key findings demonstrate that AI enhances hazard detection, enables real-time monitoring, and improves training through immersive simulations, significantly contributing to safer and more efficient workplaces. However, challenges such as data privacy concerns, algorithmic biases, and reduced worker autonomy were identified as significant barriers to broader AI adoption in OHS. AI holds great promise in transforming OHS practices, but its integration requires ethical frameworks and human-centric collaboration models to ensure transparency, equity, and worker empowerment. Addressing these challenges will allow workplaces to harness the full potential of AI in creating safer, healthier, and more sustainable environments.