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Introduction
Significant advancements in smart technology, AI, robotics, and algorithms (STARA) have created considerable interest among organisations and today’s workforce. Understanding the implications of STARA on work attitudes and behaviours is gaining the attention of scholars and practitioners (e.g., Tang et al., 2023; Yan et al., 2023), with existing findings highlighting the varied and significant effects that different types of new technologies can have on people’s work and wellbeing. New technologies have the potential to be disruptive in diverse ways, thereby shaping working roles, organisational contexts, and people’s working lives and careers (e.g., Selenko et al., 2022). Most existing reviews on STARA’s role in organisational behaviour and personnel management (cf. Bankins et al., 2023; Köchling & Wehner, 2020) focus on changes to work tasks and organisational systems, while also pointing to the essential role that humans play in the adoption of new technologies. What has so far garnered less attention is the examination of these technological innovations and how they are shaping workers’ careers in both standard and non-standard work settings. Whether STARA will shape people’s career paths, plans, decision-making, and employability perceptions and how it will disrupt – or progress – existing career pathways require systematic investigations. Questions remain open regarding whether these effects will be distributed evenly across different occupational and employment segments.
Previous studies that have examined STARA’s role in career decision-making (Gati & Kulcsar, 2021; Bartosiak & Modlinski, 2022) underline the importance of understanding the impact of STARA more holistically to explore its influences on careers. Such work will require a focus on the diversity of technologies that encompass STARA while zooming out from the effects of these technologies upon work tasks and job designs to examine their influence across the broader span of individuals’ careers.
This special issue invites such research that investigates the effects of STARA in the context of careers and recognises how the broad spectrum of technologies that encompass STARA will shape the future of careers (Tang et al., 2022). This special issue will offer important insights for both workers and organisations to adapt to these transformative technologies by showcasing studies that highlight STARA's implications for career development. Bankins et al. (2023) emphasise the need for multilevel thinking in STARA and careers research. Therefore, this special issue aims to examine the implications of STARA on the career development of workers in (non-)standard work from a multilevel perspective. Specifically, we aim to attract submissions that capture how macro (such as labour market) and meso (such as organisational structures and supports) factors may influence individuals' careers and labour market trends. This broad aim will generate wide and varied topics for this emerging research space, as careers literature has yet to unpack the extent and driving mechanisms of these technological advancements' effect on career outcomes.
The core aim of this special issue is to gain insight into the career implications of STARA for workers. Papers that make explicit attempts to capture the career-related consequences and experiences of workers in professions affected by STARA are specifically invited. The special issue is centred strongly on careers, and submissions should reflect this focus. To do this, we encourage authors to connect their work clearly and meaningfully to career theories, or career-related mechanisms, or career-related outcomes and be explicit about their level of theorising and analysis. We also invite interdisciplinary research that bridges the gap between AI research and career research and encourages submissions by scholars from varied disciplines, such as applied psychology, information systems, human resource management, and sociology. We also encourage submissions that consider a variety of ontological and methodological approaches (e.g., critical, and qualitative perspectives). We also seek papers representing a variety of worker populations, including workers in non-standard work (e.g., platform workers, contractors, multiple job holders) across a variety of occupations, industries, nationalities, and tenure status.
Overall, we encourage submissions that reflect novel, interdisciplinary research that connects STARA technologies (i.e., an aspect of smart technology, AI, robotics, or algorithms) to careers across a diversity of occupational contexts. Submissions that account for the multilevel effects of these technologies are particularly encouraged.
List of Topic Areas
Our main aim in this Special Issue is to draw together a collection of high-quality papers investigating the impact of STARA on careers. Submitted papers might focus their enquiry on the extra organisational context, the organisational level, the group level and the individual level (see Bankins et al., 2023). Suggested contributions to this special issue may focus their enquiry on the themes identified above, as well as the following:
A) Extra-organizational context, STARA and careers Papers focusing on the extra-organisational context may focus on questions such as:
- Which work and occupational contexts, government policy and practices, and new forms of labour legislation concerning STARA will affect workers’ careers? How can third sector, union, and other collective voice initiatives assist workers in light of STARA, to ensure healthy working lives in the future?
- How do career changes due to STARA affect the actions and attitudes of people in broader society, towards unions, towards policy making?
B) Organizational level, STARA and careers Example research questions may be:
- How do new forms of organisations linked to STARA and their strategies and systems affect people’s careers in those organisations?
- What does STARA mean for career interventions, HR planning and recruitment, organisational ethical AI climate and fairness, and trust?
- Which new occupations are emerging due to STARA implementation, and how will they affect future workforce planning, jobs in specific industries, and work types?
C) Group level, STARA and careers specific research questions may be:
- How does STARA affect the management of teams and team processes toward career outcomes?
- How does STARA affect team composition and career opportunities within the team?
- How does working with robots as team members affect careers?
- How does AI-supported leadership, such as using AI for team control, skill sharing and knowledge transfer, team collaboration and communication, and project management, impact the careers of team members?
- How do cross-functional and multi-disciplinary teams develop and use STARA, and how does this influence their career trajectories?
D) Individual level, STARA and careers Potential research questions at this level of analysis include:
- How are STARA technologies influencing career competencies and career resources?
- Are STARA technologies heightening or lessening career (un)decidedness, career inaction, and career insecurity?
- How is STARA (re)shaping objective and subjective career success indicators, maintaining sustainable careers (across happiness, health, and productivity), and skill development?
Submissions Information
Submissions are made using ScholarOne Manuscripts. Registration and access are available here.
Author guidelines must be strictly followed. Please see here.
Authors should select (from the drop-down menu) the special issue title at the appropriate step in the submission process, i.e. in response to ““Please select the issue you are submitting to”.
Submitted articles must not have been previously published, nor should they be under consideration for publication anywhere else, while under review for this journal.
Key Deadlines
Opening date for manuscripts submissions: 01/03/2024
Closing date for manuscripts submission: 02/10/2024
References
Bankins, S., Ocampo, A. C., Marrone, M., Restubog, S. L. D., & Woo, S. E. (2023). A multilevel review of artificial intelligence in organizations: Implications for organizational behavior research and practice. Journal of Organizational Behavior. https://doi.org/10.1002/job.2735
Bartosiak, M. L., & Modlinski, A. (2022). Fired by an algorithm? Exploration of conformism with biased intelligent decision support systems in the context of workplace discipline. Career Development International, 27(6/7), 601–615. https://doi.org/10.1108/CDI-06-2022-0170
Gati, I., & Kulcsar, V. (2021). Making better career decisions: From challenges to opportunities. Journal of Vocational Behavior, 126, 103545. https://doi.org/10.1016/j.jvb.2021.103545
Köchling, A., & Wehner, M. C. (2020). Discriminated by an algorithm: a systematic review of discrimination and fairness by algorithmic decision-making in the context of HR recruitment and HR development. Business Research, 13(3), 795–848. https://doi.org/10.1007/s40685-020-00134-w
Selenko, E., Bankins, S., Shoss, M., Warburton, J., & Restubog, S. L. D. (2022). Artificial intelligence and the future of work: A functional-identity perspective. Current Directions in Psychological Science, 31(3), 272–279. https://doi.org/10.1177/0963721422109182
Tang, P. M., Koopman, J., Mai, K. M., De Cremer, D., Zhang, J. H., Reynders, P., Ng, C. T. S., & Chen, I-H. (2023). No person is an island: Unpacking the work and after-work consequences of interacting with artificial intelligence. Journal of Applied Psychology, 108(11), 1766–1789. https://doi.org/10.1037/apl0001103
Tang, P.M., Koopman, J., McClean, S. T., Zhang, J. H., Li, C. H., De Cremer, D., Lu, Y. & Ng, C. T. S. (2022). When conscientious employees meet intelligent machines: An integrative approach inspired by complementarity theory and role theory. Academy of Management Journal, 65(3), 1019–1054. https://doi.org/10.5465/amj.2020.1516
Yam, K. C., Tang, P. M., Jackson, J. C., Su, R., & Gray, K. (2023). The rise of robots increases job insecurity and maladaptive workplace behaviors: Multimethod evidence. Journal of Applied Psychology, 108(5), 850–870. https://doi.org/10.1037/apl0001045
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