This article examines the multifaceted nature of biases in generative artificial intelligence systems, with particular emphasis on the significant yet often overlooked influence of developer-implemented guardrails. While biases inherited from training datasets have received substantial scholarly attention, this analysis argues...

“If you don’t measure it, you can’t improve it.” This maxim also applies to cybersecurity: without clear KPIs and constant monitoring, companies are blindly navigating a sea of ​​ever-changing threats. But which metrics really matter? And how can we use...