Latest Articles for Ethics In Technology

A study on improving AI decision-making by analyzing human patterns.

This article discusses the need for diverse datasets in AI to ensure fairness.

Research highlights significant racial bias in emotion recognition systems.

Creating diverse images of children's faces to enhance recognition systems.

A novel approach to reduce bias in image recognition models using synthetic data.

A framework to improve user interaction in recommendation systems.

A new algorithm helps detect AI-generated publications to combat misinformation.

A new method improves fairness in generative models without requiring original datasets.

Agencies focus on human impacts of climate events to improve disaster readiness.

This framework combines fairness and robustness for responsible AI systems.

Explore how IML transforms data analysis into clear insights.

New methods improve identity recognition over time despite clothing changes.

This article discusses fairness in clustering, focusing on the Minimum Bisection problem.

Learn the importance of high-quality data for responsible AI systems.

A review of ChatGPT and GPT-4 strengths and weaknesses across various tasks.

A new method minimizes bias while maintaining privacy in machine learning.

Neural networks improve face morphing for smoother and more realistic transitions.

A new approach ensures AI-generated images are safe and appropriate.

A novel approach reduces harmful text generation in large language models.

Examining the impact of AI on society and its potential risks.

Explore how sample size impacts AI explanations and transparency in decision-making.

A new framework tackles fairness challenges in machine learning with limited data samples.

Explore the workings and applications of GANs in various fields.

A new tool measures gender representation in multilingual datasets.

Research reveals neural networks can disrupt human image categorization more than previously thought.

This research examines how artificial text affects language model performance.

This article discusses the impact of biases in code generated by large language models.

Focusing on simplicity can improve software model understanding and effectiveness.

Language agents merge AI and decision-making for real-world tasks.

Research highlights bias in AI affecting underrepresented groups in New Zealand.

A method to remove toxic behaviors in language models while maintaining performance.

Counterfactual explanations clarify AI predictions by showing possible input changes.

A framework for measuring and improving fairness in AI systems.

A study on the impact of debiasing techniques in language models.

This research addresses bias in document retrieval systems using uncertainty estimates.

Exploring how ChatGPT is shaping learning in engineering colleges in India.

Languini Kitchen supports researchers in language modelling with fair comparisons and better datasets.

PROPLACE enhances the reliability of counterfactual explanations in machine learning.

A new method allows RL agents to change body shapes for better task adaptation.

Research on identifying AI-generated text across different models without extra training.