Latest Articles for Ethics In Technology

A study on the fairness of privacy policies and their impact on user trust.

This study addresses challenges in editing language models and mitigating unwanted ripple effects.

New methods aim to enhance data removal in language models while preserving performance.

Exploring new privacy concerns in the use of diffusion models.

Examining issues of memorization in AI-generated images and its implications.

SelfIE helps LLMs explain their thought processes clearly and reliably.

Exploring the balance between model compression and trustworthiness in AI.

A new method addresses harmful content generation in AI models.

A new framework improves the detection of altered digital images through advanced techniques.

A new method integrates constraints into probabilistic circuits for better predictions.

A study reveals new techniques for backdoor attacks on language models with minimal impact.

Examining the role of communication in fairness decisions within AI systems.

A new approach to reduce bias in AI models and improve predictions.

A method to approximate fairness-accuracy trade-offs for machine learning models.

Innovative methods improve 3D facial expressions for realistic digital characters.

This article explains how Deep Support Vectors improve understanding of AI decision-making.

A study on bias in Russian language models using a new dataset.

A framework for automatically generating rules to align LLM outputs with human expectations.

Introducing DeNetDM, a technique to reduce biases in neural networks without complex adjustments.

Diverse samples enhance the effectiveness of machine learning model theft.

A new way to animate portraits with changing expressions and angles.

Introducing a model to improve safety in language generation and reduce risks.

A study on using the MGS dataset to identify AI-generated stereotypes.

Integrating human reasoning into AI training enhances model explanations and builds trust.

This study enhances logical reasoning skills in language models through understanding logical fallacies.

A new method enhances text-to-image models for better identity representation.

This study analyzes the effectiveness of synthetic images in face recognition systems.

A new metric to assess the accuracy of AI model explanations.

A look at the competition on synthetic datasets for face recognition technology.

This article discusses a method for identifying non-factual content in AI responses without human labels.

Exploring how generative models can subtly infringe copyright laws.

A new method enhances caption quality for 3D objects.

Adaptive Fair Representation Learning offers fair and accurate recommendations tailored to individual user needs.

Researchers aim to generate balanced synthetic data to prevent bias in machine learning.

A new method aims to improve fairness in machine learning without sacrificing performance.

Examining how AI influences human judges in bail decisions.

Developers must prove AI systems are safe to manage risks effectively.

A new tool offers flexible definitions of fairness for machine learning analysis.

Enhancing face images while keeping the person's identity intact.

AdvisorQA evaluates language models' ability to provide personal advice effectively.