Abstract Chat Generative Pre-trained Transformer (ChatGPT) has gained significant interest
and attention since its launch in November 2022. It has shown impressive performance in …

Abstract ChatGPT (Chat Generative Pre-trained Transformer) has garnered the interest of
numerous segments of society since its inception in November 2022. It has already shown …

The problem of bias in facial affect recognition tools can lead to severe consequences and
issues. It has been posited that causality is able to address the gaps induced by the …

Missing diversity, equity, and inclusion elements in affective computing datasets directly
affect the accuracy and fairness of emotion recognition algorithms across different groups. A …

Emotion recognition is relevant for human behaviour understanding, where facial
expression and speech recognition have been widely explored by the computer vision …

Algorithmic audits of industry face recognition models have recently incentivized companies
to diversify their data collection methods, which in turn has reduced error disparities along …

In recent years, the affective computing (AC) and human-robot interaction (HRI) research
communities have put fairness at the centre of their research agenda. However, none of the …

We address the challenges and implications of ensuring fairness in algorithmic decision-
making (ADM) practices related to ethnicity. Expanding beyond the US-centric approach to …

Building systems for predicting human socio-emotional states has promising applications;
however, if trained on biased data, such systems could inadvertently yield biased decisions …

Speaker recognition technology, deployed in sectors like banking, education, recruitment,
immigration, law enforcement, and healthcare, relies heavily on biometric data. However …