Meta's mandate for employees to have their laptop activity tracked for AI training, followed by AI-driven layoffs, creates a new labor paradigm. Workers are compelled to provide the very data that makes their roles obsolete, turning the workforce into the raw material for their own automation.

An Indian company, Objectways, pays thousands of workers to wear headset cameras while performing manual tasks. This footage is sold as training data for humanoid robotics companies like Tesla's Optimus, effectively paying humans to accelerate their own obsolescence.

Previously, data privacy concerns were abstract for most, leading only to worse ads. Now, giving AI companies unfettered access to your professional data provides them with the exact material needed to train models that will automate your job.

A trend called "tokenmaxxing" is emerging in Silicon Valley, where companies like Meta use leaderboards to track employee AI token usage. This reflects a corporate bet that higher token consumption correlates with increased productivity, turning AI usage into a new, albeit gameable, performance metric for engineers.

AI's potential for rapid growth is creating a new moral calculus. Practices like tracking every employee keystroke for CRM automation, once controversial, are becoming standard. This trend suggests that as companies chase exponential gains, they will increasingly justify and normalize actions, from mass layoffs to invasive monitoring, that were previously considered unacceptable.

The most valuable data for training enterprise AI is not a company's internal documents, but a recording of the actual work processes people use to create them. The ideal training scenario is for an AI to act like an intern, learning directly from human colleagues, which is far more informative than static knowledge bases.

Meta is monitoring employee mouse movements and keystrokes to train AI agents. This practice mirrors 'Taylorism,' the historical method of measuring and optimizing factory workers' physical movements, with the modern parallel being knowledge workers training their own digital replacements.

Because Meta is using raw employee computer usage for AI training, its models may learn to replicate common human inefficiencies. This could lead to AI agents that browse social media or watch videos instead of working, mirroring the actual behavior of their human trainers.

Future AI models will learn complex, multi-step tasks by watching screen recordings. Companies should begin capturing video of their key internal workflows now. This data, which is currently discarded, will become a valuable proprietary asset for training AI agents to automate bespoke business processes.