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Having covered the importance of defining algorithmic fairness in an earlier article, I would now like to discuss the factors that can lead to model unfairness in more detail. Data and Bias Data coll...
As the use cases for AI in financial services continue to grow and deliver value for organizations and customers alike, I’d like to provide some insight on where I think the technology is delivering m...
Defining fairness is a problematic task. The definition depends heavily on context and culture and when it comes to algorithms, every problem is unique so will be solved through the use of unique data...
An important consideration for data scientists, businesses, and society as a whole, today centres on how we might establish AI as an indisputable and indispensable force for good in the world. For yea...
Benchmarking is an incredibly useful tool. It allows organizations to measure themselves against their main competitors and identify key areas they thrive in as well as areas in which they are lacking...