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 ...

The instructor is Animesh Mukherjee whose research has tackled some of the pressing challenges in AI ethics, from bias ...

As artificial intelligence (AI) usage has grown, the potential of bias in AI has gained more attention, as evidenced by Google Trends data (Figure 1). A recent study 1 by Herrera-Berg et al. (2023) ...

The scenario: You're preparing for a job interview. The stakes feel high. You want — you need — this job. So you do what millions of people now do: you ask an AI chatbot for advice on salary ...

While the technological hype of AI is seemingly endless and ripe with possibilities, what this excitement hides is a darker side: The ethics and bias of AI, and the harmful outcomes as a result of ...

Using generative AI to design, train, or perform steps within a machine-learning system is risky, argues computer scientist Micheal Lones in a paper publishing April 22 in the Cell Press ...

CAMBRIDGE, MA — Machine-learning models can fail when they try to make predictions for individuals who were underrepresented in the datasets they were trained on. For instance, a model that predicts ...

Using generative AI to design, train, or perform steps within a machine-learning system is risky, argues computer scientist Micheal Lones in a paper appearing in Patterns. Though large language models ...