Latest Articles for Bias

A new method aims to improve treatment effect estimates using combined data sources.

This article discusses a focused method for identifying antisemitic hate speech online.

This article discusses the role of machine learning in engineering courses.

A look at AI decision-making in dermatology and its implications for patient care.

Analyzing dataset use in voice biometrics reveals significant bias and privacy concerns.

A new method to evaluate gender bias in image and text generation models.

A novel approach to reduce bias in AI without sensitive labels.

New methods aim to enhance image searching in histopathology and reduce AI bias.

Examining biases in air quality monitoring and their implications for public health.

This article explores how language models can analyze machine learning model performance and biases.

ULTR aims to create unbiased systems for better search and recommendations.

Introducing techniques to enhance decision-making in uncertain environments.

Examining the role of fairness in systems that recognize human emotions.

Explore the importance of fostering user trust in AI technology.

Examining how biases in AI impact healthcare outcomes and ways to address them.

Explore how attentional blink affects our focus and perception.

A method to analyze imperfect data without bias.

A new framework aims to reduce bias in healthcare ML for equitable outcomes.

Exploring fairness challenges in machine learning and the need for intersectional approaches.

Examining the impact of bias in AI and the need for fairness.

Examining racial bias in algorithmic risk assessment tools in criminal justice.

New insights from real-world datasets improve understanding of complementary-label learning.

Examining the need for fairness in medical imaging models.

Learn how auxiliary variables impact estimates in health and social research.

A look at bias in NLP and ways to create fairer systems.

This article explores the ethical issues and guidelines for using ChatGPT responsibly.

This article examines biases in job application screenings using language models.

Investigating the potential of quantum perceptrons in improving machine learning capabilities.

Study reveals significant bias in de-identification methods for clinical names.

Federated learning offers solutions for fairness in AI-driven healthcare predictions.

New dataset sheds light on bias in Chinese chatbots and seeks improvements.

A new method to reduce gender bias in language models using translation techniques.

Analyzing user interaction with public and private news posts on Facebook.

High school students learn to create and reflect on AI-generated art.

Study reveals gender and racial biases in sentiment analysis models for multiple languages.

This study examines fairness in multi-task learning using demographic data from related tasks.

A study of historical biases in Caribbean newspapers from the 18th and 19th centuries.

Exploring methods to improve fairness in detecting online toxic content.

Examining how language models reflect societal biases in math and STEM.

A critical look at the current state of bias testing in NLP.