Sobre fairness y machine learning: el algoritmo, ¿puede (y debe) ser justo?

  1. Belloso Martín, Nuria
Zeitschrift:
Anales de la Cátedra Francisco Suárez

ISSN: 0008-7750

Datum der Publikation: 2023

Titel der Ausgabe: Inteligencia Artificial y Derecho

Nummer: 57

Seiten: 7-38

Art: Artikel

DOI: 10.30827/ACFS.V57I.25250 DIALNET GOOGLE SCHOLAR lock_openOpen Access editor

Andere Publikationen in: Anales de la Cátedra Francisco Suárez

Ziele für nachhaltige Entwicklung

Zusammenfassung

The increasingly frequent use of Artificial Intelligence in the field of law, forces us to consider whether automated decisions can, and should, be fair. The algorithm, in Machine Learning, has the potential to learn, which gives it a certain degree of autonomy. Biases, discriminations and inequalities that derive from automated decisions show the myth of the fair algorithm. The standard of justice that is required in the analogical conception of Law must also be required in the digital dimension. In this paper, from the initial difficulty of a lack of agreement on what fairness is, I examine how to incorporate fairness into the algorithm. This will require a previous analysis of the legal philosophical foundations and some of the theories of justice (utilitarians, contractualists, communitarians, egalitarians) from which parameters, correctors and guarantees can be established to achieve the essential correlation between artificial fairness and legal fairness.

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