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- Summary:
- Opacity in AI used to be an academic problem - now it's everyone's problem. In this piece, I define the issues at stake, and how they tie into the ongoing discussion on AI ethics.
Neil Raden, active industry analyst, consultant and widely published author and speaker and also the founder of Hired Brains Research says, Opacity in AI is a formal, academic description of what is more commonly referred to as, "What the heck is the algorithm doing?" It's a problem that is at the root of many ethical issues with AI.
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| Man solving complex problem finds surreal keyhole to success Photo: © frankie's - Shutterstock.com |
It appears as a robust classification and ranking mechanisms, such as search engines, credit card fraud detection, market segmentation, spam filters, all used in insurance or loan qualification advertising or credit. These mechanisms of classification are calculated on computational algorithms, most often machine learning algorithms...
What's in a machine learning algorithm? Two parallel processes are driven by two different algorithms: or two distinct algorithms: learners and classifiers. Inputs (features) are processed by the classifiers, producing results referred to as a category.
Source: Diginomica
