Latest Articles for Ethics In Technology

Researchers are developing synthetic voice data to protect privacy in voice recognition.

Exploring the challenges and strategies for moderating hate speech online.

A new model aims to improve fairness in recommendation systems while maintaining accuracy.

CapHuman generates realistic portraits from a single image, showing diverse versions of individuals.

Explores how LLMs can improve bot detection while addressing associated risks.

This article outlines safe practices for AI use in legal guidance.

Integrating Foundation Models with Federated Learning presents both risks and benefits.

An overview of copyright issues in generative AI and its impact.

Data contamination in language models poses serious trust issues for evaluations.

Research focuses on detecting legal issues in online text using language models.

This study investigates how biases in LLMs affect human interaction simulations.

Study highlights issues affecting fairness in AI explanations across different groups.

Explore the basics and importance of self-replicating programs in computing.

Exploring the critical role of data annotation in AI development and its challenges.

Exploring the significance of intent in artificial intelligence systems.

Ensuring ethical behavior and transparency in intelligent agents is crucial for trust.

Exploring fairness issues in machine learning and federated systems.

Exploring how language models reflect personality traits in recruitment.

This article explores how causal learning enhances recommender systems' fairness and reliability.

A new method safeguards decision privacy in language models while maintaining performance.

This study examines the benefits of personalized responses in language models.

This article discusses the complexities and challenges of auditing AI systems for fairness.

A new method to improve language model behavior by reducing bias and toxic output.

Study reveals language models struggle against simple text manipulations.

A new method aims to reduce harmful outputs from AI language models.

A look at the need for fairness and clear explanations in AI systems.

Examining gender bias in T2I models through the Paired Stereotype Test.

A new approach enhances image safety in text-to-image models through prompt optimization.

Exploring methods to enhance coding task performance in language models using data.

A new method improves alignment of LLMs with minimal human feedback.

This study examines biases in masked language models and their implications.

This study examines the efficacy of multilingual models in following instructions across European languages.

A study on the role of Degenerate Knowledge Neurons in improving language model performance.

A look into the role of attention heads and neurons in language models.

Strategies to reduce bias in ML, focusing on continuous sensitive attributes.

This article examines machine unlearning in large language models.

A new approach using backtranslation aims to protect language models from harmful prompts.

Study reveals challenges and progress in chatbot memory during lengthy dialogues.

This study examines gender bias in large language models across multiple languages.

Exploring how Value Sensitive Design can enhance Responsible AI toolkits.