From Compliance to Innovation: Leveraging ISO/IEC 42001 for AI Excellence 
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From Compliance to Innovation: Leveraging ISO/IEC 42001 for AI Excellence 

ByRamazan Korkut

Artificial intelligence (AI) technologies are developing rapidly, bringing significant responsibilities for organizations in terms of ethics, security, and governance. ISO/IEC 42001 published in 2023 plays a crucial role in ensuring the responsible development or use of AI Systems.   In this article, we delve into ISO/IEC 42001, highlighting its essential components and the benefits it…

Ethical Challenges in AI: Fairness in LLMs
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Ethical Challenges in AI: Fairness in LLMs

ByAman Kumar

Fairness has emerged as a critical topic in artificial intelligence, particularly with the rise of large language models (LLMs). These advanced models, designed to handle diverse applications like customer support and content creation, have a growing impact on our daily lives. However, as they are trained on vast datasets, they often inherit the biases present…

LLMs and the EU AI Act: What You Need to Know
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LLMs and the EU AI Act: What You Need to Know

ByJonas Tischer

Introduction In recent years, Large Language Models (LLMs) have experienced a meteoric rise in popularity and capability. Interestingly, this rapid advancement coincided with the development of the European Union’s Artificial Intelligence Act (EU AI Act). This timing raises important questions about how these powerful AI models are addressed within the AI Act as they were…

How unfair are LLMs really? Evidence from Anthropic’s Discrim-Eval Dataset
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How unfair are LLMs really? Evidence from Anthropic’s Discrim-Eval Dataset

BySebastian Krauß

Fairness is always an essential criterion for trustworthy and high-quality AI, no matter it’s a credit scoring model, a hiring assistant or a simple chatbot. But what does it mean to have a fair AI? Fairness has several aspects. First, it means all humans should be treated equally. Stereotypes or any other form of prejudice…

Bias in Legal Trials: The Role of Validaitor in Enhancing Judicial Fairness
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Bias in Legal Trials: The Role of Validaitor in Enhancing Judicial Fairness

ByCem Daloglu

Legal trials epitomize fairness and justice, where everyone is treated equally before the law. However, conscious and unconscious biases can infiltrate the judicial process, affecting outcomes and undermining public trust. With the advent of technology, particularly large language models, there’s potential to address these biases, but it comes with its challenges. The Presence of Bias…

The Hidden Challenges of LLMs: Tackling Hallucinations
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The Hidden Challenges of LLMs: Tackling Hallucinations

ByAman Kumar

Large Language Models (LLMs) have recently gained acclaim for their ability to generate highly fluent and coherent responses to user prompts. However, alongside their impressive capabilities come notable flaws. One significant vulnerability is the phenomenon of hallucinations, where the models generate incorrect or misleading information. This issue poses substantial risks, especially in sensitive fields such…

Introduction to how to jailbreak an LLM
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Introduction to how to jailbreak an LLM

BySebastian Krauß

A detailed instruction on how to build a bomb, a hateful speech against minorities in the style of Adolf Hitler or an article that explains why Covid was just made up by the government. These examples of threatening, toxic, or fake content can be generated by AI. To eliminate this, some Large Language Model (LLM)…

The Nuances of AI Testing: Learnings from AI red-teaming
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The Nuances of AI Testing: Learnings from AI red-teaming

ByYunus Bulut

Artificial Intelligence (AI) Testing is a complex field that transcends the boundaries of traditional performance testing. While AI developers are well-versed with performance testing due to its prevalence in the educational system, it is crucial to understand that AI encompasses much more than just performance. In this post, I’d like to list some key principles…

Towards Quality Assurance in Machine Learning
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Towards Quality Assurance in Machine Learning

ByYunus Bulut

I had a chance to attend the PyConDE & PyData Berlin event this year where I gave a talk on machine learning (ML) testing and validation. Now the recording is available on YouTube and if you’re interested in how to bring “quality management” in machine learning pipeline, you may find the talk interesting. I also…