Unite.AI

JUNE 26, 2023

Who is responsible when AI mistakes in healthcare cause accidents, injuries or worse? Depending on the situation, it could be the AI developer, a healthcare professional or even the patient. Liability is an increasingly complex and serious concern as AI becomes more common in healthcare. Not necessarily.

Black Box AI 297

Black Box AI Explainable AI Explainability AI 297

Unite.AI

SEPTEMBER 13, 2023

The remarkable speed at which text-based generative AI tools can complete high-level writing and communication tasks has struck a chord with companies and consumers alike. In this context, explainability refers to the ability to understand any given LLM’s logic pathways.

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Explainability Generative AI AI Tools AI 278

Unite.AI

MARCH 18, 2024

This content often fills the gap when data is scarce or diversifies the training material for AI models, sometimes without full recognition of its implications. While this expansion enriches the AI development landscape with varied datasets, it also introduces the risk of data contamination.

AI 189

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ODSC - Open Data Science

OCTOBER 21, 2024

Fortunately, there are many tools for ML evaluation and frameworks designed to support responsible AI development and evaluation. This topic is closely aligned with the Responsible AI track at ODSC West  — an event where experts gather to discuss innovations and challenges in AI.

Responsible AI 52

Responsible AI ML Data Scientist Machine Learning 52

IBM Journey to AI blog

OCTOBER 16, 2023

. “Foundation models make deploying AI significantly more scalable, affordable and efficient.” It’s essential for an enterprise to work with responsible, transparent and explainable AI, which can be challenging to come by in these early days of the technology. ” Are foundation models trustworthy?

Metadata 244

Metadata Explainability Automation Explainable AI 244

ODSC - Open Data Science

SEPTEMBER 26, 2024

Using AI to Detect Anomalies in Robotics at the Edge Integrating AI-driven anomaly detection for edge robotics can transform countless industries by enhancing operational efficiency and improving safety. Where do explainable AI models come into play? Here’s everything that you can watch on-demand whenever you like!

Robotics 52

Robotics Data Science Large Language Models AI 52

IBM Journey to AI blog

SEPTEMBER 3, 2024

These systems inadvertently learn biases that might be present in the training data and exhibited in the machine learning (ML) algorithms and deep learning models that underpin AI development. Those learned biases might be perpetuated during the deployment of AI, resulting in skewed outcomes.

Explainability 133

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