Remove AI Modeling Remove Black Box AI Remove Explainability
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Machine unlearning: Researchers make AI models ‘forget’ data

AI News

Researchers from the Tokyo University of Science (TUS) have developed a method to enable large-scale AI models to selectively “forget” specific classes of data. Progress in AI has provided tools capable of revolutionising various domains, from healthcare to autonomous driving.

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How Large Language Models Are Unveiling the Mystery of ‘Blackbox’ AI

Unite.AI

Thats why explainability is such a key issue. People want to know how AI systems work, why they make certain decisions, and what data they use. The more we can explain AI, the easier it is to trust and use it. Large Language Models (LLMs) are changing how we interact with AI. Thats where LLMs come in.

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The Hidden Risks of DeepSeek R1: How Large Language Models Are Evolving to Reason Beyond Human Understanding

Unite.AI

This success, however, has come at a cost, one that could have serious implications for the future of AI development. The Language Challenge DeepSeek R1 has introduced a novel training method which instead of explaining its reasoning in a way humans can understand, reward the models solely for providing correct answers.

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Who Is Responsible If Healthcare AI Fails?

Unite.AI

At the root of AI mistakes like these is the nature of AI models themselves. Most AI today use “black box” logic, meaning no one can see how the algorithm makes decisions. Black box AI lack transparency, leading to risks like logic bias , discrimination and inaccurate results.

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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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Enhancing AI Transparency and Trust with Composite AI

Unite.AI

The adoption of Artificial Intelligence (AI) has increased rapidly across domains such as healthcare, finance, and legal systems. However, this surge in AI usage has raised concerns about transparency and accountability. Composite AI is a cutting-edge approach to holistically tackling complex business problems.

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How Do Inherently Interpretable AI Models Work? — GAMINET

Towards AI

It is very risky to apply these black-box AI systems in real-life applications, especially in sectors like banking and healthcare. For example, a deep neural net used for a loan application scorecard might deny a customer, and we will not be able to explain why. arXiv: 2003.07132 where n is the sample size.