Essays about: "oavsiktlig bias"

Found 3 essays containing the words oavsiktlig bias.

  1. 1. Mitigating Unintended Bias in Toxic Comment Detection using Entropy-based Attention Regularization

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Fabio Camerota; [2023]
    Keywords : XLNet; BERT; Toxic Comment Classification; Entropy-based Attention Regularization; XLNet; BERT; Toxisk Kommentar Klassificering; Entropibaserad uppmärksamhetsreglering;

    Abstract : The proliferation of hate speech is a growing challenge for social media platforms, as toxic online comments can have dangerous consequences also in real life. There is a need for tools that can automatically and reliably detect hateful comments, and deep learning models have proven effective in solving this issue. READ MORE

  3. 2. Biases in AI: An Experiment : Algorithmic Fairness in the World of Hateful Language Detection

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Anna Stozek; [2023]
    Keywords : machine learning; algorithmic fairness; unintended bias; sentiment analysis; automated hate detection; maskininlärning; algoritmisk rättvisa; oavsiktlig bias; sentimentanalys; automatisk hatdetektion;

    Abstract : Hateful language is a growing problem in digital spaces. Human moderators are not enough to eliminate the problem. Automated hateful language detection systems are used to aid the human moderators. One of the issues with the systems is that their performance can differ depending on who is the target of a hateful text. READ MORE

  4. 3. Understanding Automatic Speech Recognition for L2 Speakers and Unintended Discrimination in Artificial Intelligence

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Alfred Knowles; Filip Mattsson; [2022]
    Keywords : ;

    Abstract : The thesis aimed to investigate the effects of unintended bias in artificial intelligence has on society and if it was possible to improve the performance of Auto-Speech- Recognition models by training them on non-native Swedish speakers. Two Automatic Speech Recognition systems, Microsoft Azure and Google cloud speech-to-text, were used in the process. READ MORE