Latest Articles for Ethics In Technology

An overview of the challenges in using RLHF for AI alignment.

Examining how to ensure AI aligns with human interests.

Examining how machines learn to form complex outcomes from simple parts.

Exploring how trust and responsibility differ in India and OECD nations regarding AI.

A new method to trace harmful use of large language models.

New tools aim to enhance fairness in AI by providing access to diverse datasets.

Addressing dataset biases to promote equitable outcomes in medical imaging.

Examining how changes in data influence algorithm performance and societal outcomes.

A new framework to ensure fairness in AI systems while in operation.

Researchers develop methods to identify text created by machines versus humans.

Examining how biases differ across languages and their impact on language models.

Exploring how biases affect image models and strategies for mitigation.

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.