In this preview of our latest Singularity research paper & tech release, you’ll learn why addressing algorithmic bias is vital to evaluate from a business and societal lens.
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Bias in AI is nothing new. Any AI system operates on bias to be able to differentiate between different parts of the dataset; there is no such thing as a bias-free algorithm.
But in the design of the algorithm, including in its training or dataset, there may also be entry points for unintended bias, and even intended biases can have negative downstream consequences unforeseen by the designers.
While it may not seem urgent on the surface, bias in AI is a critical issue for business leaders to consider and take measures to address. Besides the ethical ramifications of ensuring algorithms aren’t making unfair decisions or giving unfounded preference to certain groups of people, it won’t be long until there are financial and reputational consequences around bias in AI.
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