Studying Causality in Algorithmic Decision Making: the Impact of IA in the Business Environment

Main text in Spanish at Revista Internacional y Comparada de RELACIONES LABORALES Y DERECHO DEL EMPLEO, ISSN: 2282-2313, vol. 12, num. 4..

Note: This article has been prepared within the framework of the Agreement between the public entity business Red.es M.P. and the University of Castilla-La Mancha to promote the implementation of the Digital Rights Charter in the field of digital rights in the work and business environment C039/23-OT.

Abstract

Studying Causality in Algorithmic Decision Making: the Impact of IA in the Business Environment.

One of the main applications of artificial intelligence (AI) in the workplace is the so-called ‘algorithmic management’, which involves the delegation and execution of business functions in AI systems. As labour regulations have been created and developed around individuals, not machines, algorithmic management may give rise to new problems that cannot be dealt with under current regulations. One of these new problems is the fact that these AI systems base their operation on correlations (not on causes), and labour regulations require the concurrence of causes (not correlations) in the making of some business decisions. This dichotomy can generate possible problems related to the inexistence and/or lack of sufficiency of the legally required causes, or the generation of labour discrimination that is difficult to detect. For this reason, this study will examine these issues and propose different legal solutions and give hints on technical solutions to align those systems with the regulation. Therefore, we consider that in no case could business decisions requiring concurrence of cause be automated, although [artificial intelligence] could be used as an assistant to the human controller, which is aligned with both the Laboral Law and the incoming AI regulation (AI Act).

Outline

1. Introduction.
2. Brief history of AI and its evolution.
3. Use of AI in the business field.
   1. Advantages and risks of using AI in decision making.
4. Concept of AI system. Legal aspects. Technical aspects.
   1. Concept of AI system.
   2. Legal aspects of AI systems in algorithmic management.
   3. Technical aspects of AI systems in algorithmic management.
      1. Operation of AI systems in decision making.
      2. Explanation of the correlation-causation dilemma. Examples in the workplace.
      3. Blackbox. Explainability.
5. Existence of causality in algorithmic management.
   1. Pre-contractual phase.
   2. Contractual phase.
6. Proposal of solutions.
   1. 6.1. Technical solutions.
   2. Legal solutions.
7. Conclusions.