SILICON VALLEY — A groundbreaking new report reveals that despite decades of scientific research and incredible advances in deep analytics, corporate hiring algorithms are consistently flagging women as 'too complex' for senior leadership positions. The AI, developed to navigate increasingly volatile markets and identify optimal talent, reportedly struggles to process non-linear career paths and the 'unquantifiable' benefits of diverse perspectives.

“Our models are built for efficiency and predictable outcomes,” stated Dr. Brenda Systems, lead AI ethicist for GlobalCorp, a fictional company that definitely exists. “When presented with candidates who might, for example, take a parental leave or prioritize team cohesion over aggressive individual metrics, the system categorizes them as 'high-risk' or 'anomalous data points.' It’s simply optimizing for what it understands: a straight line to the top, preferably without children or outside interests.”

The report, published by the Institute for Obvious Observations, found that while companies express 'no shortage of good intentions' regarding diversity, their AI systems are inadvertently perpetuating existing biases. “It’s not malice, it’s just… math,” explained Systems, adjusting her glasses. “The algorithms learn from historical data, and historically, leadership has looked a certain way. We’re working on a patch, but it’s proving difficult to teach a machine to value things it can’t put on a spreadsheet.”

Industry experts suggest that until the AI can be re-educated, companies may need to resort to archaic methods like 'human judgment' or 'blind resume reviews' to ensure a more balanced leadership pipeline. Meanwhile, the algorithms continue to recommend male candidates with identical CVs, citing their 'unwavering commitment to the status quo.'