Latest Articles for Ethics In Technology

A new method enhances image generation accuracy and diversity.

BiasAlert enhances bias detection in language models for fairer AI outputs.

A closer look at methods to ensure LLMs are safe from misuse.

Exploring the relationship between humans and Generative AI through a natural analogy.

A new tool to assess replication in AI-made music.

Exploring privacy risks in synthetic data and introducing the Data Plagiarism Index.

This article discusses using Reinforcement Learning to reduce bias in classification tasks.

An overview of NLG progress, challenges, and future research directions.

Establishing a benchmark to evaluate fairness in graph learning methods.

Examining the significance of privacy through identity unlearning in machine learning.

J-CHAT provides a large, open-source dataset for enhancing spoken dialogue systems.

A new method enhances safety in image generation from text prompts.

A new method improves 3D human modeling from minimal photos.

Research presents a framework to reduce bias in AI-generated text.

Workshops enhance understanding of Responsible AI for industry professionals.

Research reveals how friendly prompts can mislead AI systems.

A robust dataset for training advanced chat-based AI systems.

A framework to incorporate minority voices in annotation processes.

Learn how Text Style Transfer changes text style while preserving meaning.

A new method enhances AI model alignment without retraining.

PUFFLE offers a solution for privacy, utility, and fairness challenges in machine learning.

New model efficiently creates realistic 3D human head representations.

This article discusses how LLM reasoning enhances recommendation systems and introduces Rec-SAVER.

A method to reduce bias in language models by making them forget harmful information.

Combining machine learning with automated reasoning for clearer AI explanations.

Understanding techniques to bypass safety in language models.

Exploring the use of watermarks to tackle copyright issues in language models.

A new synthetic dataset enables accurate head detection and 3D modeling.

A detailed study on how models memorize text and its implications.

An analysis of how surveys impact AI research, values, and public engagement.

This project aims to identify and reduce bias in language models across European languages.

A deep dive into the importance of interpreting NLP models.

Examining the methods for preparing data in model training.

A new approach to assess the reliability of methods explaining AI decision-making.

Examining fairness issues in anomaly detection algorithms for facial images.

Exploring machine unlearning and its role in enhancing generative AI safety and privacy.

Exploring human biases and their impact on AI fairness.

New methods detect and respond to memorization in AI-generated content.

Exploring principles for ethical relationships between people and their data.

New methods tackle issues of copying in image generation models.