Meta Harvests Employee Keystroke Data to Train AI Models

Skynet Chance (+0.04%): The willingness to harvest employee data without clear boundaries demonstrates weakening privacy norms and oversight in AI development, which correlates with reduced safety constraints. This erosion of ethical guardrails in the pursuit of training data suggests companies may increasingly prioritize capability advancement over alignment and control considerations.

Skynet Date (+0 days): While concerning from a privacy perspective, employee keystroke data does not represent a qualitative breakthrough in AI capabilities or control mechanisms. The practice affects data sourcing methods but doesn't materially accelerate or decelerate the timeline toward potential loss of control scenarios.

AGI Progress (+0.01%): Access to diverse human interaction data (keystrokes and mouse movements) provides marginal additional training signal for AI models to better understand human work patterns. However, this represents incremental data augmentation rather than a fundamental breakthrough in capabilities or understanding required for AGI.

AGI Date (+0 days): The trend of exploiting previously untapped internal data sources (employee activity, corporate communications) provides modest acceleration by expanding the available training data pool. This could slightly speed up model improvements, though the impact on AGI timeline is minimal compared to algorithmic or architectural breakthroughs.