The compression of political change from years to days represents more than quantitative acceleration—it’s a qualitative transformation in how societies evolve. Understanding what this temporal compression means for democratic adaptation requires examining what naturally occurs over three years that algorithms now accomplish in one week.
Over three years, political attitudes typically shift through gradual accumulation of experiences, conversations, news consumption, and social influence. People encounter diverse perspectives, reflect on changing circumstances, discuss politics with friends and family, and slowly update their views. This gradualism allows for course corrections and social adaptation.
The research found that algorithmic manipulation among over 1,000 X users during the 2024 presidential election compressed this three-year process into seven days. Users experienced attitude shifts matching those that would normally develop through thousands of interactions and extensive reflection, except these shifts occurred through mere exposure to slightly altered social media feeds.
This compression bypasses the reflection and social processing that normally accompanies political change. When attitudes evolve gradually, people can notice shifts, discuss them with others, and potentially moderate extreme movements. When algorithms compress change into days, these adaptive mechanisms cannot operate—people find their views have shifted without the normal opportunities for conscious evaluation.
The implications extend to institutional adaptation. Democratic institutions evolved to handle gradually-shifting public opinions that give policymakers time to respond. Institutions designed for three-year timescales may prove dysfunctional when algorithmic acceleration compresses equivalent changes into weeks. This mismatch between institutional timescales and algorithmically-driven change could produce governance crises even in otherwise healthy democracies.