Bias in AI (Supported) Decision Making: Old Problems, New Technologies

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14220%2F25%3A00141064" target="_blank" >RIV/00216224:14220/25:00141064 - isvavai.cz</a>

Výsledek na webu

<a href="https://iacajournal.org/articles/10.36745/ijca.598" target="_blank" >https://iacajournal.org/articles/10.36745/ijca.598</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.36745/ijca.598" target="_blank" >10.36745/ijca.598</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Bias in AI (Supported) Decision Making: Old Problems, New Technologies

Popis výsledku v původním jazyce

Recently different regulations and recommendations for the use of AI-based technology, especially in the judiciary, have become more prevalent. One major concern is addressing bias in such systems. In 2016, ProPublica published a damning report on the use of AI-based technology in making decisions about people’s rights and obligations, revealing that such systems tend to replicate and amplify existing biases. The problem arises from the extensive need for training data in machine learning, which is often based on previous data, such as court decisions. For example, the bail system in the US was found to be alarmingly biased against African Americans. Even efforts to avoid mentioning protected characteristics have been shown to be insufficient, as so-called “fairness through unawareness” has been undermined by proxy characteristics. Addressing the bias of AI systems is a crucial issue for the increased involvement of automated means in judicial settings. The following paper examines various biases that might be introduced in AI-based systems, potential solutions and regulations, and compare possible solutions with current approaches of the European Court of Human Rights (ECtHR) towards biases in human judges. The aim is to confront the question of how to approach current bias in judges compared to approaching bias in future AI-based judicial decision-making technology.

Název v anglickém jazyce

Bias in AI (Supported) Decision Making: Old Problems, New Technologies

Popis výsledku anglicky

Recently different regulations and recommendations for the use of AI-based technology, especially in the judiciary, have become more prevalent. One major concern is addressing bias in such systems. In 2016, ProPublica published a damning report on the use of AI-based technology in making decisions about people’s rights and obligations, revealing that such systems tend to replicate and amplify existing biases. The problem arises from the extensive need for training data in machine learning, which is often based on previous data, such as court decisions. For example, the bail system in the US was found to be alarmingly biased against African Americans. Even efforts to avoid mentioning protected characteristics have been shown to be insufficient, as so-called “fairness through unawareness” has been undermined by proxy characteristics. Addressing the bias of AI systems is a crucial issue for the increased involvement of automated means in judicial settings. The following paper examines various biases that might be introduced in AI-based systems, potential solutions and regulations, and compare possible solutions with current approaches of the European Court of Human Rights (ECtHR) towards biases in human judges. The aim is to confront the question of how to approach current bias in judges compared to approaching bias in future AI-based judicial decision-making technology.

Druh

J_SC - Článek v periodiku v databázi SCOPUS

CEP obor

—

OECD FORD obor

50501 - Law

Projekt

—

Návaznosti

N - Vyzkumna aktivita podporovana z neverejnych zdroju

Rok uplatnění

2025

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

International Journal for Court Administration

ISSN

2156-7964

e-ISSN

2156-7964

Svazek periodika

16

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

30

Strana od-do

1-30

Kód UT WoS článku

—

EID výsledku v databázi Scopus

2-s2.0-105004307989