bias

bias

Validate Data Fairness and Privacy for Responsible AI

Stuart Battersby

November 24, 2022

What is unique about machine learning and AI compared to traditional rules-based systems?   Well, amongst various things, a key point is that AI learns from a training dataset instead of explicitly being coded with rules to follow. There is a huge focus on Responsible AI (aka Ethical or Trustworthy AI) – and rightly so.  However, […]

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Managing AI Risks. Multiple Stakeholders Need Access to the Right Data and Insights

Stuart Battersby

September 30, 2020

In a guest post on insideBIGDATA I wrote: “There is no doubt that AI is exploding across businesses, and it is not just with the moon shots that make news headlines. Due to the speed and scale at which AI can operate, it is being used across the critical operations and decision making in everyday […]

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Assessing the Fairness of an AI model

Stuart Battersby

July 9, 2020

AI models can achieve very high accuracy (this is particularly true with contemporary deep learning methods) and can churn through data at a much higher rate than is possible with humans. This has led to their deployment in decision making systems across various industries. In general, these systems are trained (that is, taught how to […]

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Addressing bias in AI needs Explainability; you can’t fix what you can’t see

Stuart Battersby

April 14, 2020

Contemporary machine learning systems are different from traditional rules-based systems. With these traditional systems a series of rules were written that matched up with the desired operation of the system. In machine learning, the system learns how to make decisions from the data that is presented to it. Whilst this has many advantages, a very […]

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