Essay by Mark Esposito and David De Cremer: “…These advances are not happening in isolation on engineers’ laptops; they are increasingly playing out in “decision theaters” – specialized environments (physical or virtual) designed for interactive, collaborative problem-solving. A decision theater is typically a space equipped with high-resolution displays, simulation engines, and data visualization tools where stakeholders can convene to explore complex scenarios. Originally pioneered at institutions like Arizona State University, the concept of a decision theater has gained traction as a way to bring together diverse expertise – economists, scientists, community leaders, government officials, and now AI systems – under one roof. By visualizing possible futures (say, the spread of a wildfire or the regional impact of an economic policy) in an engaging, shared format, these theaters make foresight a participatory exercise rather than an academic one. In the age of generative AI, decision theaters are evolving into hubs for human-AI collaboration. Picture a scenario where city officials are debating a climate adaptation policy. Inside a decision theater, an AI model might project several climate futures for the city (varying rainfall, extreme heat incidents, flood patterns) on large screens. Stakeholders can literally see the potential impacts on maps and graphs. They can then ask the AI to adjust assumptions – “What if we add more green infrastructure in this district?” – and within seconds, watch a new projection unfold. This real-time interaction allows for an iterative dialogue between human ideas and AI-generated outcomes. Participants can inject local knowledge or voice community values, and the AI will incorporate that input to revise the scenario. The true power of generative AI in a decision theater lies in this collaboration.
Such interactive environments enhance learning and consensus-building. When stakeholders jointly witness how certain choices lead to undesirable futures (for instance, a policy leading to water shortages in a simulation), it can galvanize agreement on preventative action. Moreover, the theater setup encourages asking “What if?” in a safe sandbox, including ethically fraught questions. Because the visualizations make outcomes concrete, they naturally prompt ethical deliberation: If one scenario shows economic growth but high social inequality, is that future acceptable? If not, how can we tweak inputs to produce a more equitable outcome? In this way, decision theaters embed ethical and social considerations into high-tech planning, ensuring that the focus isn’t just on what is likely or profitable but on what is desirable for communities. This participatory approach helps balance technological possibilities with human values and cultural sensitivities. It’s one thing for an AI to suggest an optimal solution on paper; it’s another to have community representatives in the room, engaging with that suggestion and shaping it to fit local norms and needs.
Equally important, decision theaters democratize foresight. They open up complex decision-making processes to diverse stakeholders, not just technical experts. City planners, elected officials, citizens’ groups, and subject matter specialists can all contribute in real time, aided by AI. This inclusive model guards against the risk of AI becoming an opaque oracle controlled by a few. Instead, the AI’s insights are put on display for all to scrutinize and question. By doing so, the process builds trust in the tools and the decisions that come out of them. When people see that an AI’s recommendation emerged from transparent, interactive exploration – rather than a mysterious black box – they may be more likely to trust and accept the outcome. As one policy observer noted, it’s essential to bring ideas from across sectors and disciplines into these AI-assisted discussions so that solutions “work for people, not just companies.” If designed well, decision theaters operationalize that principle…(More)”.
