In this activity, society members interacted with a decision-making system that determined access to a special opportunity, while its rules were intentionally hidden during play. Working in teams, students submitted profiles as inputs, received selection outcomes, and applied systems thinking to infer how the system operated based solely on repeated feedback rather than explicit explanations.

Over successive rounds, society members tested hypotheses, adjusted strategies, and observed how complex systems prioritise structure, signals, clarity, and consistency. The activity also surfaced the role of noise or chance, where small elements of randomness influenced outcomes, highlighting how luck and imperfect information can affect real-world decision-making systems. Together, this illustrated key characteristics of black-box systems, including opacity, emergent behaviour, and the gap between individual intent and system-level outcomes.

At the conclusion of the activity, the system’s actual rules, weightings, and sources of noise were revealed. This final reveal allowed students to compare their inferred models with the real system, reinforcing how systems thinking helps in understanding, questioning, and critically evaluating complex and opaque decision-making processes in contexts such as technology, algorithms, and institutional selection systems.