An effective approach to AI Ethics must reckon with bias, algorithmic discrimination, and privacy. These terms have a historical context that should be understood - if we want to deploy AI ethically.

Data scientists know that artificial intelligence and predictive modeling leads to some bias in underwriting. What they don't always know are the ways and the extent of the negative impact. More ...

Statistics and science have been publicly slammed by some. The issues of climate change and COVID-19, in particular, have stirred accusations of bias, conspiracies, and even hoaxes (Philipp-Muller et ...

Please provide your email address to receive an email when new articles are posted on . There are statistical/computational, human and systemic biases in AI. Harms of ...

Vincent Violago and Nikko Quevada discuss the various types of bias in machine learning algorithms and the data used to train the algorithms. They also analyse patents directed to bias mitigation, as ...

As we enter a world of machine learning and data science, are there any gotchas or negatives? It sounds as if it is all sunshine and rainbows, but, as the title to this post alludes, I believe there ...

Statistics and science have been publicly slammed by some. The issues of climate change and COVID-19, in particular, have stirred accusations of bias, conspiracies, and even hoaxes (Philipp-Muller et ...