As artificial intelligence pioneer Geoffrey Hinton strode across a Stockholm stage to receive his Nobel Prize for physics, ...

A new MIT technique improves machine learning by removing key biased data points, boosting model performance for minority ...

Machine-learning models can fail when they try to make predictions for individuals who were underrepresented in the datasets ...

Researchers developed an AI debiasing technique that improves the fairness of a machine-learning model by boosting its performance for subgroups that are underrepresented in its training data, while ...

AI biases can lead to unfair outcomes, perpetuate stereotypes and, ultimately, compromise the integrity of AI systems.

One of the biggest barriers to using AI successfully is bias, which is one of the terms we defined last time, as follows: Bias, in a general ...

HR and technology leaders want to grow in their understanding of the potential for bias in employee benefits technology.

AI decision-making systems show promise but lack consistent evidence for improving patient-relevant outcomes like mortality and quality of life. Rigorous harm-benefit assessments and transparency are ...

A new study by the Harvard GenderSci Lab in the British Journal of Sports Medicine reveals systematic biases in a key metric used in estimates of sex disparities in ACL injury rates in sports. The ...

Christian Pulisic said he believes there is a bias against U.S. men's national team players in Europe, adding that he has experienced that stigma firsthand during his career. The AC Milan man is ...

Negative feedback networks are employed at both stages of the proposed LNA to expand bandwidth. Furthermore, source adaptive bias networks is designed in the first stage and combined with a ...