These AI assistants were designed and trained predominantly using voices that reflect specific linguistic norms, leading to ...

Over the last few decades, artificial intelligence (AI) has demonstrated extraordinary ability in assessing and forecasting ...

It's on company leaders and managers to ensure AI accountability. All companies should continually consider creating policies ...

Examples include: Considering the advances already made in AI—and those yet ... larger sets of data. Biased data causes machine learning to rely on unjustified bias to discriminate against ...

Furthermore, due to the AI's inherent tendency to generate outputs that align with the "average" result, models typically ...

This bias can arise from various sources, including the quality of the data used for training, the design of the algorithms, or the way the AI system is integrated into the testing environment.

Cultural values and traditions differ across the globe, but large language models (LLMs), used in text-generating programs such as ChatGPT, have a tendency to reflect values from English-speaking and ...

As the head of Artificial Intelligence (AI ... but still unintentionally introduce bias into the results," he explains. His favourite example is facial recognition. "The first versions of facial ...

Smart manufacturing allows you to shift some of your decision-making from trained people to data analytics and software. But ...

AI bias occurs when an AI system produces prejudiced ... as current ones will not be sufficient. For example, the algorithms used in new software, particularly AI algorithms, might not be fully ...

If companies and the HR profession want to address the issue of bias in AI-based recruitment ... based on hidden data from other correlated information. For example, in countries with different ...