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. It achieves this by integrating multiple analytical techniques into a single solution.

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Towards AI

DECEMBER 19, 2023

Source: interpretable-ml-book The field of deep learning has grown exponentially and the recent craze about ChatGPT is proof of the same. It is very risky to apply these black-box AI systems in real-life applications, especially in sectors like banking and healthcare.

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DataRobot Blog

APRIL 29, 2022

Opening the “ Black Box AI ”: The Path to Deployment of AI Models in Banking What You Need to Know About Model Risk Management. The Framework for ML Governance. appeared first on DataRobot AI Cloud. More on this topic. Download now. The post What is Model Risk and Why Does it Matter?

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O'Reilly Media

DECEMBER 12, 2023

The problem with Lanier’s concept of data dignity is that, given the current state of the art in AI models, it is impossible to distinguish meaningfully between “training” and “generating output.” He asks, “Why don’t bits come attached to the stories of their origins?

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Mlearning.ai

DECEMBER 31, 2023

Let’s embark on this enlightening journey together, unraveling the mysteries of AI, one explanation at a time. What is Explainable AI? It is a research field on ML interpretability technique whose aims are to understand machine learning model predictions and explain them in a human understandable terms to build trust with stakeholders.

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