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#48 Interpretability Might Not Be What Society Is Looking for in AI

Towards AI

This week, we are diving into some very interesting resources on the AIblack box problem’, interpretability, and AI decision-making. Parallely, we also dive into Anthropic’s new framework for assessing the risk of AI models sabotaging human efforts to control and evaluate them. Enjoy the read!

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How Do Inherently Interpretable AI Models Work? — GAMINET

Towards AI

Source: interpretable-ml-book The field of deep learning has grown exponentially and the recent craze about ChatGPT is proof of the same. The models are becoming more and more complex with deeper layers leading to greater accuracy. One issue with this current trend is the focus on interpretability is lost at times.

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Copyright, AI, and Provenance

O'Reilly Media

Another group of cases involving text (typically novels and novelists) argue that using copyrighted texts as part of the training data for a Large Language Model (LLM) is itself copyright infringement, 1 even if the model never reproduces those texts as part of its output. In the future, AIs may be included among those ghostwriters.

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Unlocking the Black Box: LIME and SHAP in the Realm of Explainable AI

Mlearning.ai

Principles of Explainable AI( Source ) Imagine a world where artificial intelligence (AI) not only makes decisions but also explains them as clearly as a human expert. This isn’t a scene from a sci-fi movie; it’s the emerging reality of Explainable AI (XAI). Present the model’s predictions to stakeholders.

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The Daunting Influence of A.I.- Shaping a New World Order Revealed!

Artificial Corner

Throughout history, religions have claimed that their holy books were authored by non-human intelligence. While this assertion was unsubstantiated in the past, the rise of AI presents the possibility of it becoming a real reality. Often referred to as the “black box,” AI algorithms can be complex and difficult to comprehend fully.