| Naslov: | Adaptive boosting method for mitigating ethnicity and age group unfairness |
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| Avtorji: | ID Colakovic, Ivona (Avtor)
ID Karakatič, Sašo (Avtor) |
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| Datoteke: |  s42979-023-02342-7.pdf (1,66 MB)
MD5: D69BBDAE109AEDCF92A3DFE01958F4BB
 https://link.springer.com/article/10.1007/s42979-023-02342-7
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| Jezik: | Angleški jezik |
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| Vrsta gradiva: | Članek v reviji |
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| Tipologija: | 1.01 - Izvirni znanstveni članek |
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| Organizacija: | FERI - Fakulteta za elektrotehniko, računalništvo in informatiko
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| Opis: | Machine learning algorithms make decisions in various fields, thus influencing people’s lives. However, despite their good quality, they can be unfair to certain demographic groups, perpetuating socially induced biases. Therefore, this paper deals with a common unfairness problem, unequal quality of service, that appears in classification when age and ethnicity groups are used. To tackle this issue, we propose an adaptive boosting algorithm that aims to mitigate the existing unfairness in data. The proposed method is based on the AdaBoost algorithm but incorporates fairness in the calculation of the instance’s weight with the goal of making the prediction as good as possible for all ages and ethnicities. The results show that the proposed method increases the fairness of age and ethnicity groups while maintaining good overall quality compared to traditional classification algorithms. The proposed method achieves the best accuracy in almost every sensitive feature group. Based on the extensive analysis of the results, we found that when it comes to ethnicity, interestingly, White people are likely to be incorrectly classified as not being heroin users, whereas other groups are likely to be incorrectly classified as heroin users. |
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| Ključne besede: | fairness, boosting, machine learning, classification |
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| Status publikacije: | Objavljeno |
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| Verzija publikacije: | Objavljena publikacija |
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| Poslano v recenzijo: | 05.11.2022 |
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| Datum sprejetja članka: | 20.09.2023 |
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| Datum objave: | 15.11.2023 |
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| Založnik: | Springer Nature |
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| Leto izida: | 2024 |
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| Št. strani: | 9 str. |
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| Številčenje: | Vol. 5, article no. 10 |
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| PID: | 20.500.12556/DKUM-88791  |
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| UDK: | 004.8 |
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| COBISS.SI-ID: | 172430083 |
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| DOI: | 10.1007/s42979-023-02342-7 |
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| ISSN pri članku: | 2661-8907 |
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| Avtorske pravice: | © The Author(s) 2023 |
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| Datum objave v DKUM: | 24.05.2024 |
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| Število ogledov: | 283 |
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| Število prenosov: | 17 |
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| Metapodatki: |    |
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| Področja: | Ostalo
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