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Who Is Responsible If Healthcare AI Fails?


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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How Do Inherently Interpretable AI Models Work? — GAMINET

Towards AI

The models are becoming more and more complex with deeper layers leading to greater accuracy. It is very risky to apply these black-box AI systems in real-life applications, especially in sectors like banking and healthcare. One issue with this current trend is the focus on interpretability is lost at times.


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Is Rapid AI Adoption Posing Serious Risks for Corporations?

ODSC - Open Data Science

Bias and Inequality AI can also introduce societal issues like exaggerating bias if corporations aren’t careful. Amazon’s scrapped hiring AI model infamously penalized women’s resumes as the machine learning algorithm expanded on implicit biases within the training data.

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The future of QA is here, meet QA-GPT


In our testing, we found that QA-GPT can cover over 85% of scorecard questions out of the box without any extra configuration. Say goodbye to black-box AI models where you’re never quite sure if the AI got it right. We’re also improving the transparency of evaluations.

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Unlocking the Black Box: LIME and SHAP in the Realm of Explainable 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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What is Model Risk and Why Does it Matter?

DataRobot Blog

The new field of MLOps offers a much stronger framework for model validation, documentation, and oversight than traditional manual efforts, while more closely aligning to the ever increasing regulatory requirements and vastly reducing “model risk.”. The post What is Model Risk and Why Does it Matter? More on this topic.

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Copyright, AI, and Provenance

O'Reilly Media

What is contained in the model is an enormous set of parameters based on all the content that has been ingested during training, that represents the probability that one word is likely to follow another. The ability to emit a sonnet that Shakespeare never wrote: that’s transformative, even if the new sonnet isn’t very good.

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