AI News

DECEMBER 10, 2024

Compounding these issues is that generalist tendencies may hinder the efficiency of AI models when applied to specific tasks. For instance, in practical applications, the classification of all kinds of object classes is rarely required, explains Associate Professor Go Irie, who led the research.

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Unite.AI

DECEMBER 19, 2024

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. Lets dive into how theyre doing this.

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Unite.AI

MARCH 14, 2024

The opportunities afforded by AI are truly significant – but can we trust black box AI to produce the right results? Instead of utilizing AI systems that they cannot explain – black box AI systems – they could utilize AI platforms that use transparent techniques , explaining how they arrive at their conclusions.

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Towards AI

NOVEMBER 7, 2024

It also highlights ways to improve decision-making strategies through techniques like dynamic transition matrices, multi-agent MDPs, and machine learning for prediction. It highlights the dangers of using black box AI systems in critical applications and discusses techniques like LIME and Grad-CAM for enhancing model transparency.

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Unite.AI

APRIL 9, 2024

Several times black-box AI models have produced unintended consequences, including biased decisions and lack of interpretability. Composite AI is a cutting-edge approach to holistically tackling complex business problems. Explainability is essential for accountability, fairness, and user confidence.

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Aiiot Talk

JULY 7, 2023

Analyzing Aircraft With Digital Twins AI-powered analytics can improve safety through digital twins as well as predictive maintenance. Digital twins often use machine learning and AI to simulate the effects of operational or design changes. Black-box AI poses a serious concern in the aviation industry.

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Towards AI

DECEMBER 19, 2023

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.

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