Audits attempt to straighten out the "wild, wild west" of algorithms


AI algorithms employed in everything from hiring to lending to criminal justice have a persistent and often invisible problem with bias. The big picture: One solution could be audits that aim to determine whether an algorithm is working as intended, whether it's disproportionately affecting different groups of people and, if there are problems, how they can be fixed. How it works: Algorithmic audits -- usually conducted by outside companies -- involve examining an algorithm's code and the data used to train it, and assessing its potential impact on populations through interviews with stakeholders and those who might be affected by it. Between the lines: Financial audits exist in part to open up the black box of a company's internal operations to outside investors, and ensure that a company remains in compliance with financial laws and regulations. Details: Algorithmic audits can help companies screen their AI products for flaws that may not be apparent at first glance.

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