A digital twin is a psychologically realistic simulation of a human population or society — a working model populated by many AI agents whose beliefs, values, and behaviors are calibrated to mirror those of real people. Rather than abstracting a society into a few aggregate variables, a digital twin instantiates it as a dense field of individual agents, each carrying its own attitudes, identities, and decision rules, so that collective dynamics emerge from the bottom up the way they do in life. The purpose is foresight: by running interventions inside the model first, researchers and decision-makers can test how a policy, message, or shock is likely to ripple through a real population before committing to it in the world, where mistakes are costly and irreversible. These twins are built through 📝Multi-Agent AI (MAAI), in which large numbers of AI-agent simulations interact under realistic social and cultural conditions. 📝CulturePulse constructs digital twins of this kind through its 📝ARES platform — including a roughly fifteen-million-agent twin of the Israeli–Palestinian conflict developed for the United Nations to evaluate paths toward de-escalation. This social sense should be distinguished from the engineering sense of the term, where a digital twin is a virtual replica of a machine, building, or factory; the twins discussed here are digital twins of societies and audiences, not of physical equipment.
For me this is the whole point of the work: if we can model a population faithfully enough, we can stop guessing about human behavior at scale and start testing our interventions before they touch real lives. That is where simulation stops being a toy and becomes a moral instrument.