A machine learning (ML) model incorporating both clinical and genomic ... retrospective data analysis, and potential referral bias associated with specialized cancer centers. To address these ...

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 systems, including large language models (LLMs), exhibit "social identity bias," favoring ingroups and disparaging ...

MIT researchers developed a groundbreaking method to improve fairness in machine learning by identifying and removing biased ...

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

From the early days of mechanical automatons to more recent conversational bots, scientists and engineers have dreamed of a ...

Sora has been available mainly to a small group of safety testers, or “red-teamers,” who test the model for vulnerabilities ...

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 ...

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 ...

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

We list the best virtual machine software, to make it simple and easy to setup and run a new operating system virtually on your existing computer. Virtualization has become an increasingly ...

MacDonald’s core insight is that present bias makes clients prioritize immediate needs at the expense of future requirements. “It comes from a good place,” said MacDonald. “It means that people don’t ...