The implicit bias of present-day generative AI models make their rapid adoption in the financial sector hazardous, according to a report by a financial technology expert working for the Bank of England.
Kathleen Blake’s report, published Wednesday, splits AI model bias into two categories — bias based on underlying training data, and bias based on the results of model output. Although both reflect the human biases that developers and creators bring to AI models, the former category is impossible to counteract just by getting rid of data points that indicate, for example, femininity or non-whiteness.
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The implicit bias of present-day generative AI models make their rapid adoption in the financial sector hazardous, according to a report by a financial technology expert working for the Bank of England.Kathleen Blake’s report, published Wednesday, splits AI model bias into two categories — bias based on underlying training data, and bias based on the results of model output. Although both reflect the human biases that developers and creators bring to AI models, the former category is impossible to counteract just by getting rid of data points that indicate, for example, femininity or non-whiteness.To read this article in full, please click here Read More Computerworld
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