No one needs to predict that generative artificial intelligence will be big—again—in 2024.
Because the output of GenAI models is directly determined by what goes in, there's a danger that onboarding inaccurate data could lead to significant strategic and tactical misfires, as model outputs are skewed by faulty data. In fact, fears surrounding this risk are a big part of executive concerns, with the possibility of"making factually wrong decisions"From a security perspective, it’s important to recognize that inputted information can also become algorithm training fodder.
A relatively straightforward initial step that all companies can take is establishing stringent policies for technology vetting and application. For instance, robust assessment protocols that involve legal teams, security experts and cross-business users will help ensure that safety measures are rigorously evaluated—especially surrounding data protection—and reduce the chances of encountering unforeseen issues.
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