Overcoming AI’s transparency paradox

Transparency paradox

AI has a well-documented but poorly understood transparency problem. 51% of business executives report that AI transparency and ethics are important for their business, and not surprisingly, 41% of senior executives state that they have suspended the deployment of an AI tool because of a potential ethical issue. In order to fully understand why AI transparency is such a challenging issue, we first ought to reconcile with some common misconceptions and their realities within AI transparency to gain a better view of the problem and the best way to address transparency within the context of the current ML tools in the market. 

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Operationalizing AI ethics, no longer an option but an imperative

Reid Blackman - CEO Virtue

A Virtual Sit Down with Reid Blackman. As I’ve written in my “On AI Ethics,” series, machine learning models that aim to mirror and predict real-life as closely as possible are not without their challenges. Household name brands like Amazon, Apple, Facebook, Google have been accused of algorithmic bias that have negatively affected society at large. 

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