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

Author:

Nowik Paweł1ORCID

Affiliation:

1. John Paul II Catholic University of Lublin, Lublin, Poland

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.

Publisher

Uniwersytet Jagiellonski - Wydawnictwo Uniwersytetu Jagiellonskiego

Reference75 articles.

1. 1. 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."

2. 2. 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).

3. 3. 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).

4. 4. 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).

5. 5. 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).

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