Bias Detection in Large Language Models - Techniques and Best Practices - Holistic AI

Описание: Large Language Models (LLMs) are powerful AI systems trained on extensive text data to generate and predict human-like language. Their applications span numerous fields, including software development, scientific research, media, and education. However, the widespread use of these models has raised concerns about inherent biases that can lead to skewed language generation, unfair decision-making, and perpetuation of systemic inequalities. Early detection of these biases is crucial to ensure that LLMs contribute positively to society.

This webinar will explore bias assessment in traditional machine learning and the specific challenges posed by LLMs. We will discuss policy requirements for bias assessment, such as those outlined in NYC Bias Local Law 144. The session will also cover various types of bias in LLMs and how these biases manifest in different downstream tasks, both deterministic and generative. Additionally, we will introduce several research papers published by Holistic AI. Register now to secure your spot and be part of the conversation on shaping the future of ethical AI.

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