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Technology unions and automation of labour


Dr. Tamaro J. Green

TJG News:

2021-02-08 11:35:33 viewed: 599


Technology unions may be a response to shifts in labour caused by automation (Dahlin, 2019; Frank et al., 2019).   Compa (2014) explains the transition in history from laws that restricted to laws that permitted collective bargaining.  Collective bargaining regulations began in the transportation sector and then traveled to the private and public sectors (Compa, 2014).  A view of labour unions is that they are not needed in the society of today because management has enlightened past exploitation of workers (Compa, 2014). 

Automation such as industrial robots has created new trends in the labour force (Frank et al., 2019).  New demands in labour and emerging labour markets allow for shadow economies and informal firms to develop.  Němec, Kotlánová, Kotlán, and Machová (2021) explore capital accumulation in shadow economies.  Floridi, Demena, and Wagner (2020) review policies that governments have established to informal employment and economies and to formalize informal firms.

Without unions, shadow economies and informal firms may have the potential to have less protection for the rights of workers.  Harassment may persist in shadow economies or informal firms.   Wylie (2018) defines “academic mobbing” as a process for bullying a person from an organization on the pretext that they are a threat to the organization with tactics such as excluding them from participation or targeting their reputation.  Harassment such as academic mobbing may take place in a shadow economy or informal firm.

Technology workers in shadow economies or informal firms are in their right to form unions.  Levine (2001) explains that federal law authorizes the right to join unions, unions are exempt from antitrust law, and closed and genuine union shops are illegal.  The union may support regulators in legitimizing informal firms and lead to full-time employment opportunities.  McCausland, Summerfield, and Theodossiou (2020) suggest that full-time workers improve productivity for an industry more than part-time workers as they are more likely to receive training and work more hours.

Research continues on how to improve labour markets and make them fair and equitable.  Bun and Huberts (2018) compare compensation based on productivity and performance.  Automation continues to be a force that has to be addressed for the shift of labour markets.  Dahlin (2019) provide a regression model estimation of whether automation will affect the prevalence of certain jobs.  Frank et al. (2019) describes how artificial intelligence shifts demands for specific skills and influences the economy in education and career development requirements.  As labour markets shift, new ways for rewarding employees may also need to be developed for human capital to compete with robots.  Berlinski and Ramos (2020) evaluate the effects that public announcements of professional awards can have on the applications for awards.




Berlinski, S., & Ramos, A. (2020). Peer effects in the decision to apply for a professional excellence award. Labour Economics, 67, 101934. doi:

Bun, M. J. G., & Huberts, L. C. E. (2018). The impact of higher fixed pay and lower bonuses on productivity. Journal of Labor Research, 39(1), 1-21. doi:10.1007/s12122-017-9260-9

Compa, L. (2014). An overview of collective bargaining in the United States. Faculty Publications - International and Comparative Labor, 91-98.

Dahlin, E. (2019). Are robots stealing our jobs? Socius, 5, 2378023119846249. doi:10.1177/2378023119846249

Floridi, A., Demena, B. A., & Wagner, N. (2020). Shedding light on the shadows of informality: A meta-analysis of formalization interventions targeted at informal firms. Labour Economics, 67, 101925. doi:

Frank, M. R., Autor, D., Bessen, J. E., Brynjolfsson, E., Cebrian, M., Deming, D. J., . . . Rahwan, I. (2019). Toward understanding the impact of artificial intelligence on labor. Proceedings of the National Academy of Sciences, 116(14), 6531. doi:10.1073/pnas.1900949116

Levine, P. (2001). The legitimacy of labor unions. Hofstra Labor and Employment Law Journal, 18(2).

McCausland, W. D., Summerfield, F., & Theodossiou, I. (2020). The effect of industry-level aggregate demand on earnings: Evidence from the US. Journal of Labor Research, 41(1), 102-127. doi:10.1007/s12122-020-09299-z

Němec, D., Kotlánová, E., Kotlán, I., & Machová, Z. (2021). Corruption, taxation and the impact on the shadow economy. Economies, 9(1). doi:10.3390/economies9010018

Wylie, P. (2018). My campus administration, faculty association and me: Academic mobbing and sweetheart unionism. Workplace, 31, 31-41.


Dr. Tamaro Green is a computer science researcher and the founder of TJG Web Services.  TJG Web Services, LLC is a consulting firm in the field of information technology.  Dr. Green writes on topics of privacy, security, and ethics in information technology and computer science.

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