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.

Black Box AI 299

Black Box AI Explainability Algorithm AI 299

Unite.AI

JUNE 26, 2023

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.

Black Box AI 297

Black Box AI Explainable AI Explainability AI 297

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.

AI Modeling 270

AI Modeling Black Box AI Big Data AI 270

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. Imagine an AI predicting home prices.

Large Language Models 208

Large Language Models Explainable AI Explainability Conversational AI 208

Unite.AI

APRIL 9, 2024

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.

Composite AI 182

Composite AI Explainability Explainable AI Black Box AI 182

Towards AI

NOVEMBER 7, 2024

Building Trustworthy AI: Interpretability in Vision and Linguistic Models By Rohan Vij This article explores the challenges of the AI black box problem and the need for interpretable machine learning in computer vision and large language models.

Black Box AI 115

Black Box AI Machine Learning AI Prompt Engineer 115

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.

Neural Network 122

Neural Network AI Modeling Black Box AI Explainability 122