Personal AI doesn't need to control your life to change it; it just needs to provide clear feedback on your behavior. Viewing AI as feedback loops rather than mere butlers redefines the 'agent' conversation.
This paper introduces algometrics, a framework for time series whose evolution depends on the predictive algorithms forecasting them. It distinguishes historical risk from deployment risk, proving that deployment risk is not identifiable from passive historical data alone and that historical model rankings can invert under crowding.
The Dual Loop Law explains how self-healing systems can paradoxically harm system stability. This happens due to feedback loops that escalate problems rather than resolving them.