New Challenges for Trade Unions in the Face of Algorithmic Management in the Work Environment

Paweł Nowik

New Challenges for Trade Unions in the Face of Algorithmic Management in the Work Environment

Publication date: 21.07.2022

Studies on Labour Law and Social Policy, Volume 29 (2022), Volume 29 Issue 2, pp. 121 - 143

https://doi.org/10.4467/25444654SPP.22.011.15685

Authors

Pobierz pełny tekst

PDF

Titles

New Challenges for Trade Unions in the Face of Algorithmic Management in the Work Environment

Abstract

Algorithmic management is the subject of numerous scientific studies. This article attempts to answer the question of what kinds of new competencies and skills should be acquired by trade unions in the face of challenges related to algorithmic management. The author indicates two main areas of trade union activities: The first concerns the challenges associated with the process of explaining and transplanting artificial intelligence. The second concerns participation in the AI certification process. Considering that artificial intelligence algorithms’certification process is an entirely new undertaking, it should be based on a pragmatic search for peaceful solutions, encourage compliance with the law and limit the possibility of stiff administrative and criminal sanctions. For this purpose, the author considers using the theory of responsive regulation as a pragmatic approach for certification agencies and trade unions. The author considers the cooperation of artificial intelligence to be the main principle. In the working environment, there should be a principle of human importance—the focus of personalism.

ASJC: 3308, JEL: H55, K31

Keywords

artificial intelligence, algorithmic management, AI certification, Explainable AI, trade unions, responsive regulation; sztuczna inteligencja, zarządzanie algorytmiczne, certyfikacja AI, związki zawodowe, elastyczna regulacja

artificial intelligence, algorithmic management, AI certification, Explainable AI, trade unions, responsive regulation

References

Download references

Adams-Prassl J. (2020) When Your Boss Comes Home: Three Fault Lines for the Future of Work in the Age of Automation, AI, and COVID-19, “Ethics of AI in Context.”

AI HLEG [High-Level Independent Group on Artificial Intelligence] (2019a) Ethics Guidelines for Trustworthy AI, https://digital-strategy.ec.europa.eu/en/library/ethics-guidelinestrustworthy-ai (access: 18 December 2020).

AI HLEG (2019b) A Definition of AI: Main Capabilities and Disciplines, https://digital-strategy.ec.europa.eu/en/library/definition-artificial-intelligence-main-capabilities-and-scientificdisciplines (access: 18 December 2020).

AI HLEG (2020) Assessment List for Trustworthy AI (ALTAI), https://digital-strategy.ec.europa.eu/en/library/assessment-list-trustworthy-artificial-intelligence-altai-self-assessment (access: 18 December 2020).

Amyx S. (n.d.) Wearing Your Intelligence: How to Apply Artificial Intelligence in Wearables and IoT, Wired. Com, https://www.wired.com/insights/2014/12/wearing-your-intelligence/ (accessed: 2 December 2020).

Aneesh A. (2009) Global Labor: Algocratic Modes of Organization, “Sociological Theory,” Vol. 27, Issue 4.

Barocas S., Selbst A.D. (2016) Big Data’s Disparate Impact, “California Law Review,”Vol. 104, No. 671.

Barredo A.A., Diaz-Rodriguez N., Del Ser J., Bennetot A., Tabik S., Barbado A., Garcia S. et al. (2020) Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI, “Information Fusion,”Vol. 58.

Beer D. (2017) The Social Power of Algorithms, “Information, Communication & Society,” Vol. 20, Issue 1.

Benjamins R., Barbado A., Sierra D. (2019) Responsible AI by Design in Practice, ArXiv, no. Ec.

Bhatt U., Xiang A., Sharma S., Weller A., Taly A., Jia Y., Ghosh J., Puri R., Moura J.M.F., Eckersley P. (2020) Explainable Machine Learning in Deployment [in:] FAT* 2020: Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency, New York.

Braithwaite J. (2011) The Essence of Responsive Regulation, Fasken Lecture, “University of British Columbia Law Review,”Vol. 44, Issue 3.

Braithwaite J. (2013) Relational Republican Regulation, “Regulation and Governance,”Vol. 7, Issue 1.

Braithwaite V., Braithwaite J. (2001) An Evolving Compliance Model for Tax Enforcement [in:] N. Shover, J.P. Wright (eds.), Crimes of Privilege: Readings in White-Collar Crime, New York. Brandy J.L. (2018) Artificial Intelligence (‘AI’) in the Legal Profession, “Law Audience Journal”, Vol. 2, Issue 3.

Buchanan B.G., Duda R.O. (1983) Principles of Rule-Based Expert Systems, “Advances in Computers”22(C).

Carabantes M. (2020) Black-Box Artificial Intelligence: An Epistemological and Critical Analysis, “AI and Society”, Vol. 35 (2).

Cherry M. (2016) Beyond Misclassification: The Digital Transformation of Work, “Comparative Labor Law and Policy Journal”, Vol. 37, No. 3.

Dameski A. (2018) A Comprehensive Ethical Framework for AI Entities: Foundations, “Lecture Notes in Computer Science”, Vol. 10999 LNAI.

Davidow B. (2014) Welcome to Algorithmic Prison: The Use ofBig Data to Profile Citizens is Subtly, Silently Constraining Freedom, Washington, DC.

De Stefano V. (2020a) Algorithmic Bosses and What to Do About Them: Automation, Artificial Intelligence and Labour Protection, “Studies in Systems, Decision and Control”, https://doi.org/10.1007/978-3-030-45340-4_7.

https://doi.org/10.1007/978-3-030-45340-4_7.

De Stefano V. (2020b) ‘Master and Servers’: Collective Labour Rights and Private Government in the Contemporary World of Work, “International Journal of Comparative Law Law and Industrial Relations,”Vol. 4, Issue 36.

Deloitte (2020) Trustworthy AI™: Bridging the ethics gap surrounding AI, https://www2.deloitte.com/us/en/pages/deloitte-analytics/solutions/ethics-of-ai-framework.html (access: 18 December 2020).

European Parliament (2017) European Parliament resolution of 16 February 2017 with recommendations to the Commission on Civil Law Rules on Robotics (2015/2103(INL)).

Ferraris V., Bosco F., D’Angelo E. (2013) The Impact of Profiling on Fundamental Rights, Working Paper No. 3, https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2366753.

Finn E. (2017) What Algorithms Want: Imagination in the Age of Computing. What Algorithms Want: Imagination in the Age of Computing. The MIT Press.

Gillespie T (2014) The Relevance of Algorithms [in:] T. Gillespie, P.J. Boczkowski, K.A. Foot KA (eds.), Media Technologies: Essays on Communication, Materiality and Society, 167–194. MIT Press: Cambridge, MA.

Goldstein B., Laurenand D., Nemani (eds.) (2013) Beyond Transparency: Open Data and the Future of Civic Innovation. AI Matters, “AI Matters,”Vol. 5, Issue 2.

Grabosky P. (n.d.) Meta-Regulation [in:] Regulatory Theory, https://about.jstor.org/terms (access: 18 December 2020).

Guo W. (2020) Explainable Artificial Intelligence for 6G: Improving Trust between Human and Machine, “IEEE Communications Magazine,”Vol. 58, Issue 6.

Hamon R., Junklewitz H., Sanchez I. (2020) Robustness and Explainability of Artificial Intelligence, https://doi.org/10.2760/5749.

https://doi.org/10.2760/5749.

High-Level Independent Group on Artificial Intelligence (AI HLEG) (2019) A Definition of AI: Main Capabilities and Disciplines, “European Commission,”7, https://ec.europa.eu/digital-single-.

High-Level Independent Group on Artificial Intelligence (AI HLEG) (2020) Assessment List for Trustworthy AI (ALTAI), https://ec.europa.eu/digital-single-market/en/news/assessmentlist-trustworthy-artificial-intelligence-altai-self-assessment (access: 18 December 2020).

How J.P. (2017) Ethically Aligned Design: A Vision for Prioritising Human Well-Being with Autonomous and Intelligent Systems–Version 2, “IEEE Control Systems Magazine,”Vol. 38, Issue 3.

ICO (n.d.) Guidance on AI and Data Protection, https://ico.org.uk/for-organisations/guide-todata-protection/key-data-protection-themes/guidance-on-ai-and-data-protection (access: 18 December 2020).

IEEE (n.d.) IEEE Ethics In Action in Autonomous and Intelligent Systems, https://ethicsinaction.ieee.org/ (access: 18 December 2020).

ILO (2018) Digital Labour Platforms and the Future of Work: Towards Decent Work in the Online World. International Labour Office, https://www.ilo.org/wcmsp5/groups/public/---dgreports/---dcomm/---publ/documents/publication/wcms_645337.pdf, (access: 18 December 2020).

Irani L. (2015) The Cultural Work of Microwork, “New Media & Society,”Vol. 17, Issue 5.

Kaminski M.E. (2018) The Right to Explanation, Explained, “SSRN Electronic Journal,” https://doi.org/10.2139/ssrn.3196985.

https://doi.org/10.2139/ssrn.3196985.

Karanasiou A., Pinotsis D. (2017) Towards a Legal Definition of Machine Intelligence: The Argument for Artificial Personhood in the Age of Deep Learning [in:] Proceedings of the International Conference on Artificial Intelligence and Law, New York.

Khaleghi B. (2019) The How of Explainable AI: Explainable Modelling, Medium, https://medium.com/towards-data-science/the-how-of-explainable-ai-post-modelling-explainability-8b4cbc7adf5f (access: 18 December 2020).

Kim N. (2014) The Wrap Contract Morass, “Southwestern University Law Review.”

Lee M.K., Kusbit D., Metsky E., Dabbish L. (2015a) Working with Machines: The Impact of Algorithmic and Data-Driven Management on Human Workers [in:] CHI ‘15: Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems, New York.

Lee M.K., Kusbit D., Metsky E., Dabbish L. (2015b) Working with Machines: The Impact of Algorithmic and Data-Driven Management on Human Workers [in:] CHI ‘15: Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems, New York.

Leslie D. (2020) Understanding Artificial Intelligence Ethics and Safety: A Guide for the Responsible Design and Implementation of AI Systems in the Public Sector, “SSRN Electronic Journal,” https://doi.org/10.2139/ssrn.3403301.

https://doi.org/10.2139/ssrn.3403301.

Maltseva K. (2020) Wearables in the Workplace: The Brave New World of Employee Engagement, “Business Horizons,”Vol. 63, Issue 4.

Mann G., O’Neil C. (2016) Hiring Algorithms Are Not Neutral, “Harvard Business Review.” Mateescu A., Nguyen A. (2019) Algorithmic Management in the Workplace, “Data & Society Research Institute.”

Mazmanian M., Orlikowski W.J., Yates J.A. (2013) The Autonomy Paradox: The Implications of Mobile Email Devices for Knowledge Professionals, “Organization Science,”Vol. 24, Issue 5.

Mittelstadt B.D., Allo P., Taddeo M., Wachter S., Floridi L. (2016) The Ethics of Algorithms: Mapping the Debate, “Big Data and Society,”Vol. 2, Issue 2.

Moore Ph.V. (2020) Data Subjects, Digital Surveillance, AI and the Future of Work.

Moore Ph.V., Upchurch M., Whittaker X. (2018) Humans and Machines at Work: Monitoring, Surveillance and Automation in Contemporary Capitalism, Cham.

Murray W.C., Rostis A. (2007). ‘Who’s Running the Machine?’ A Theoretical Exploration of Work Stress and Burnout of Technologically Tethered Workers, “Journal of Individual Employment Rights,”Vol. 12, Issue 3.

Noto La Diega G. (2018) Against the Dehumanisation of Decision-Making: Algorithmic Decisions at the Crossroads of Intellectual Property, Data Protection, and Freedom of Information, “Journal of Intellectual Property, Information Technology and Electronic Commerce Law,” Vol. 9, Issue 1.

Page T. (2015) A Forecast of the Adoption of Wearable Technology, “International Journal of Technology Diffusion,”Vol. 6, Issue 2.

Parker Ch. (2002) The Open Corporation: The Open Corporation.

Pasquale F. (2015) THE BLACK BOX SOCIETY The Secret Algorithms That Control Money and Information, http://raley.english.ucsb.edu/wp-content/Engl800/Pasquale-blackbox.pdf (access: 18 December 2020).

Preece A., Harborne D., Braines D., Tomsett R., Chakraborty S. (2018) Stakeholders in Explainable AI, ArXiv.

Renan Barzilay A., Ben-David A. (2018) Platform Inequality: Gender in the Gig-Economy, “Seton Hall Law Review,”Vol. 47, No. 393.

Ribeiro M.T., Singh S., Guestrin C. (2016) ‘Why Should i Trust You?’ Explaining the Predictions of Any Classifier [in:] Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, New York.

Rogers J., Ayres Y., Braithwaite J. (1993) Responsive Regulation: Transcending the Deregulation Debate, “Contemporary Sociology,”Vol. 22, No. 3.

Rosenblat A., Stark L. (2016) Algorithmic Labor and Information Asymmetries: A Case Study of Uber’s Drivers, “International Journal of Communication,”Vol. 10.

Rudin C. (2018) Please Stop Explaining Black-Box Models for High Stakes Decisions, NIPS.

Schubert C., Hutt M.T. (2019) Economy-on-Demand and the Fairness of Algorithms, “European Labour Law Journal,”Vol. 10, Issue 1.

Sileno G., Boer A., van Engers T. (2019) The Role of Normware in Trustworthy and Explainable AI [in:] CEUR Workshop Proceedings.

Spreeuwenberg S. (2020) Choose for AI and for Explainability [in:] Ch. Debruyne, H. Panetto, W. Guedria, P. Bollen, I. Ciuciu, G. Karabatis, R. Meersman (eds.), On the Move to Meaningful Internet Systems: OTM 2019 Workshops, Cham (series: “Lecture Notes in Computer Science,”Vol. 11878).

Stanford J. (2017) The Resurgence of Gig Work: Historical and Theoretical Perspectives, “The Economic and Labour Relations Review,”Vol. 28, Issue 3.

Stewart A., Stanford J. (2017) Regulating Work in the Gig Economy: What Are the Options?, “The Economic and Labour Relations Review,”Vol. 28, Issue 3.

Stone P., Brooks R., Brynjolfsson E., Calo R., Etzioni O., Hager G., Hirschberg J. et al. (2016) Artificial Intelligence and Life in 2030: One Hundred Year Study on Artificial Intelligence, “Stanford University,”Vol. 52.

Till A.L., Ratcheva V.S., Zahidi S. (2018) Future of Jobs Report 2018, “World Economic Forum:,” http://reports.weforum.org/future-of-jobs-2018/ (access: 18 December 2020).

UNI Global Union (2017) Top 10 Principles for Ethical Artificial Intelligence, 10, www.uniglobalunion.org.

van der Heijden J. (2020) Responsive Regulation in Practice, “Regulatory Governance Research.”

van den Heuvel S., Bondarouk T. (2017) The Rise (and Fall?) Of HR Analytics, “Journal of Organizational Effectiveness: People and Performance,”Vol. 4, No. 2.

Winfield A.F., Michael K., Pitt J., Evers V. (2019) Machine Ethics: The Design and Governance of Ethical Ai and Autonomous Systems, “Proceedings of the IEEE,”vol. 107, Issue 3.

World Economic Forum (2018) http://reports.weforum.org/future-of-jobs-2018/shareableinfographics/2018.

Yeung K. (2018) Algorithmic Regulation: A Critical Interrogation, “Regulation and Governance,” Vol. 12, Issue 4, https://doi.org/10.1111/rego.12158.

https://doi.org/10.1111/rego.12158.

Zuiderveen Borgesius F.J., Poort J. (2017) Online Price Discrimination and EU Data Privacy Law, “Journal of Consumer Policy”, Vol. 40.

Information

Information: Studies on Labour Law and Social Policy, Volume 29 (2022), Volume 29 Issue 2, pp. 121 - 143

DOI: https://doi.org/10.4467/25444654SPP.22.011.15685

Article type: Original article

Titles:

Polish:

New Challenges for Trade Unions in the Face of Algorithmic Management in the Work Environment

English:

New Challenges for Trade Unions in the Face of Algorithmic Management in the Work Environment

Authors

Paweł Nowik

https://orcid.org/0000-0002-1824-0884

John Paul II Catholic University of Lublin
Poland

Published at: 21.07.2022

Article status: Open

Licence: CC BY

Percentage share of authors:

Paweł Nowik (Author) - 100%

Article corrections:

Publication languages:

English

View count: 1003

Number of downloads: 633

<p> New Challenges for Trade Unions in the Face of Algorithmic Management in the Work Environment</p>

Download xml