Stereotypes in language refer to the biases and generalizations embedded in linguistic expressions, which can perpetuate societal prejudices based on factors like gender, race, ethnicity, or social status. Computational language models, such as OpenAI's G...
The AI community has been focusing on developing fixes for harmful bias and discrimination, through so-called ‘debiasing algorithms’ that either try to fix data for known or expected biases, or constrain the outcomes of a given predictive model to produce...
Biases in data can be both explicit and implicit. A simple two-word phrase can carry strong contestations, and entire research fields, such as post-colonial studies, are devoted to them. However, these sometimes subtle (and sometimes not so subtle) differ...
Synthetic media, encompassing technologies like deep learning and computer vision, has emerged as a transformative concept with profound implications for the news industry. While it offers exciting opportunities for immersive storytelling and creative inn...
This study investigates the ethical implications of AI.
The goal of this document is to provide more information on the Readiness Assessment Methodology, lay out its various dimensions, and detail the work plan for the implementing countries, including the type of entities tha...
1st European Summer School on Artificial Intelligence (ESSAI) & 20th Advanced Course on Artificial Intelligence (ACAI), organised jointly as 3rd TAILOR Summer School on Trustworthy AI.
This toolkit is designed to help companies develop trustworthy artificial intelligence for children and youth (World Economic Forum).