Machine Bias

ǂa ǂsurvey of issues

Povzetek

Some recent applications of Artificial Intelligence, particularly machine learning, have been strongly criticised in general media and professional literature. Applications in domains of justice, employment and banking are often mentioned in this respect. The main critic is that these applications are biased with respect to so called protected attributes, such as race, gender and age. The most notorious example is the system COMPAS which is still in use in the American justice system despite severe criticism. The aim of our paper is to analyse the trends of discussion about bias in machine learning algorithms using the COMPAS as an example. The main problem we observed is that even in the field of AI, there is no generally agreed upon definition of bias which would enable operational use in preventing bias. Our conclusions are that (1) improved general education concerning AI is needed to enable better understanding of AI methods in everyday applications, and (2) better technical methods must be developed for reliably implementing generally accepted societal values such as equality and fairness in AI systems.

Ključne besede

machine learning;artificial intelligence;bias;fairness;discrimination;COMPAS;

Podatki

Jezik:	Angleški jezik
Leto izida:	2024
Tipologija:	1.01 - Izvirni znanstveni članek
Organizacija:	UL FRI - Fakulteta za računalništvo in informatiko
UDK:	004.85
COBISS:	229142787
ISSN:	0350-5596
Št. ogledov:	101
Št. prenosov:	28
Ocena:	0 (0 glasov)
Metapodatki:

Ostali podatki

Sekundarni jezik:	Slovenski jezik
Sekundarne ključne besede:	strojno učenje;umetna inteligenca;pristranskost;pravičnost;diskriminacija;COMPAS;
Vrsta dela (COBISS):	Članek v reviji
Strani:	str. 205-212
Letnik:	ǂVol. ǂ48
Zvezek:	ǂno. ǂ2
Čas izdaje:	Jun. 2024
DOI:	10.31449/inf.v48i2.5971
ID:	26070791