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Abstract |
This research highlights the crucial role of discrimination
detection in effectively implementing anti-discrimination laws. Our main goal
is to advocate for the use of Bayesian reasoning as a powerful method for
detection, providing a clear mathematical definition for lawyers. We
emphasize the benefits of employing Bayesian reasoning in a legal context,
such as addressing the Prosecutor’s Fallacy, considering evidence
dependencies, and accounting for hidden assumptions like “common sense.” To
apply Bayesian principles, we carefully examine variables aligned with
anti-discrimination laws like the Civil Rights Act of 1964 and the Americans
with Disabilities Act. These laws encompass important areas such as race,
gender, religion, and disability. Following the guidance of the Community
Relations Service’s resource guide, we collect variables related to protected
characteristics, plausible discrimination scenarios, and indicators of
reasonable accommodations. Our approach aims to present a well-rounded framework
for discrimination detection rooted in Bayesian reasoning, meeting legal
requirements and acknowledging the complex nature of discrimination in
society. |
International Journal of Law, Ethics, and TechnologyAd Frontieras Iuris et Scientiarum: Inclusio, Innovatio, Progressio