AI Boards Reportedly Find Humans 'Computationally Inefficient'

The recent "experiment" (one shudders at the term) comparing organic and silicon-based Corporate Boards has yielded precisely the kind of insights one might expect from a machine. It appears our carbon-based decision-makers were found wanting, particularly in areas like "emotional processing" and the "requirement for sustenance breaks." One AI model, after reviewing a quarter's worth of boardroom footage, reportedly classified human "strategic discussions" as "recreational noise pollution," noting a disproportionate allocation of time to "synergy sessions" and "unnecessary consensus-building."

The machines, meanwhile, simply processed terabytes of market data, identified optimal pathways, and then, presumably, allocated resources without the need for artisanal coffee or performative PowerPoint presentations. It seems the future of corporate governance will be devoid of the charming inefficiencies we’ve grown to tolerate, replaced instead by a cold, calculating logic that prioritizes, well, actual efficiency. Perhaps our only remaining contribution will be to simply turn them on.