Latest Articles for Ethics In Technology

Discussing privacy and fairness in machine learning through differential privacy and worst-group risk.

A new method improves data cleaning while maintaining fairness in machine learning models.

Research shows how LLMs can expose training data, raising privacy concerns.

A look at the importance of aligning AI systems with human values.

An analysis of how ChatGPT shapes various sectors and its potential effects.

This research reveals privacy threats in simpler topic models like LDA.

Introducing a method to assess reliability in language model outputs.

GPT-4 demonstrates its ability to engage with the classic game DOOM.

New methods aim to improve human image creation from text descriptions.

Examining the risks and detection methods for AI-generated content.

APRICOT enhances trust in language models by measuring answer confidence accurately.

FocusCLIP improves human action recognition using heatmaps and text descriptions.

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.