Evolution of Decision Theater

A more active, nimble tool of engagement for researchers and communities

When ASU first opened the doors of the Decision Theater (DT), the idea was to provide data visualization at the highest and fastest performance level to help stakeholders not only examine options for pathways to solutions, but also nimbly adjust the variables. DT has since worked with partners as varied as the National Science Foundation, U.S. Department of Agriculture, the Helios Foundation, Conservation International and adidas on projects addressing megacity disaster assistance, land degradation, water and leadership training through game-based simulation. Now, Senior Global Futures Scientists are looking at the next evolution of DT and how it can use augmented intelligence in order to become an active participant instead of merely a data tool.

Patricia Solís is executive director of the Knowledge Exchange for Resilience, a campuswide effort to link multisector community needs with research innovations in building community resilience. The effort is funded by a generous grant from the Virginia G. Piper Trust, and engages a multidisciplinary team of community and academic fellows, design scholars, research professors, and full-time staff and graduate student assistants. Solís is an associate research professor of geography in the School of Geographical Sciences and Urban Planning.

Manfred Laubichler is the director of the School of Complex Adaptive Systems and the Global Biosocial Complexity Initiative. He is the Global Futures Professor and President’s Professor of theoretical biology and history of biology. His work focuses on evolutionary novelties from genomes to knowledge systems, the structure of evolutionary theory and the evolution of knowledge.

What is the purpose of Decision Theater?

Manfred Laubichler: I see Decision Theater as a core technology for global futures because it allows us to investigate and advance societal will, which is needed to accomplish necessary transformations. In a way, the Julie Ann Wrigley Global Futures Laboratory’s success crucially depends on activating societies to engage in the kind of transformations of those complex problems that we are part of and that we need to change. The issue of societies contributing to change is, of course, a tricky one, because societal change happens no matter what — and it generally doesn’t happen in a very clear cut and directed way. DT, as a technology, allows us to bring together our model-based scientific understanding of the problem and engage with societies or stakeholders in such a way that they learn how to think in terms of complex systems transformation. In turn, members of society can tell us what’s missing in the model so that we can refine the process. Through this act of co-creation we can become partners in achieving necessary transformations.

Patricia Solís: The biggest challenges that we’re going to face in our global futures are going to be extremely complex. We need to have all of society working together, especially the public university. Arizona State University in particular is designed to create research and public value. We need to engage the public in every step of the process, including what I call the “first mile,” which helps us to determine what questions matter the most. What are the questions that we need to engage around first? If we’re going to really focus in on where we can make a difference, we need to be engaged with community members, decision-makers and other stakeholders who are affected, at every step of the way. At the Knowledge Exchange for Resilience (KER), we’re trying to create the space for knowledge exchange to happen so that we can liberate the data that community members have that is not typically used in science. Those inputs will inform our models and help us innovate because now we know what situations our decision-makers are facing and what kinds of data they hold on to, which in turn helps us improve our models and perspectives. We’ve learned a lot about the way that communities work by partnering with them around specific projects regarding how decision-making works. We’ve joined with DT, as part of our work, to understand better how those decisions get made, how we can access the data and insights that communities have and that we have, and put those in play together to really come around to some solutions.

Laubichler: DT has the power to change the way science interacts with society. At one extreme, the purpose of science is to generate pure knowledge and scientists don’t care about its applications. At the other end of the spectrum, science really engages in terms of citizen science. The new version of DT will enable us to cover a large part of that continuum. What has worked in the past is that you bring some select people — whether it’s a client or some small group of stakeholders — into DT, where scientists and researchers help them arrive at a decision through models or data visualization. That’s one data point in that spectrum. But, as we liberate DT from its facility and bring it out into the community, it can really become an interesting research tool, where one can uncover — as Patricia was saying — what people care about. But researchers must go to the people, into pubs and other locations, and engage them. And you can do it with a simple laptop. We can use this version of the DT to break down the barrier between science and the public. It’s truly democratic to go out and engage people in the whole process of discovery and science. If we don’t do that, we will continue to lose credibility as scientists.

The KER website already is a place for people to go and find data, but with this future iteration of DT, you’re adding another access point through which society can receive information in a more visual way and potentially help drive or shape improved futures. How will that work?

Solís: Decisions that affect our global future are not just going to be the decisions of the highest-level decision-makers. We all make decisions every single day, about our lives, the communities we live in, and our workplaces, families, relationships and purchases. We’re all making decisions. Collectively, that has an impact on what global futures look like in this complex system. It’s important that we’re doing this in an engaged way — we can’t just sit back and “do science” without understanding and giving the opportunity for input and feedback. One of the most important assets that this new configuration of DT will give us is the ability not just to share data, but to share the models and algorithms around that data. I think we can accelerate our work tremendously. We come across the same kinds of problems in different situations. With the new configuration, we will be able to access a suite of tools that we’ve built together and reconfigure it for different questions that come up. Especially when we’re looking at the future, a lot of those tools need to be scenario-based and forward looking. They need to be predictive — not just descriptive of what is happening right now in the world, but helping us get to a vision of what it could be.

Laubichler: Building on what Patricia said, DT captures the Global Futures Laboratory’s five core spaces: Discovery, Learning, Solutions, Networks and Engagement. It’s a core facility for global futures given its transformative potential to imagine possible future scenarios in the context of complex systems. A major part of the new version, DT 3.0, will be to broaden its use. In the past, DT was focused on providing an infrastructure for decision-making, bringing in a relatively narrowly defined group of central decision-makers into the facility. Some researchers, specifically Patricia, are already using DT in a much more engaged way, where it isn’t just top clients who want to have a solution that they can then run with. It is much more engaged and open-ended. What the DT hasn’t comprehensively done, because it was facility-based, is be part of scientific culture and the scientific core. When you think about what the scientific core of the Global Futures Laboratory is, it is understanding and modeling big transformations of social, technological and environmental systems. But that kind of model structure has not been part of the DT expertise. It is a distributed expertise within the laboratory, which we have to bring more closely together with DT. To do so, DT 3.0 must become a focal lens of the laboratory where we combine and bring together our different expertise in modeling. That will allow the laboratory to become a clearinghouse for understanding how different, interconnected systems actually change and bring it to the relevant and affected parties. It’s not a one-way street.

It seems that we are now talking about Decision Theater as being an active participant of the process. How does that impact how you are approaching it as a user and as a facilitator of its use?

Solís: Decision Theater is one of the reasons that I loved the idea of coming to ASU in the first place. I was just fascinated by it. But I think tools like it are often thought of as “the last mile.” We’ve got all these models, and we need to reach out to those who use our work. But typically, it doesn’t result in the actual decisions being made. That’s why we have been focusing on the first mile and getting engagement throughout the whole process. The first mile means you get the question right from the beginning. It also means that we access datasets that other researchers would never have thought of using. Sometimes trying to deal with data that isn’t built for scientific purposes, and trying to translate it into meaningful indicators or models, is really messy. This kind of data is everywhere. It’s in organizations that provided support through the pandemic, or in housing information or transportation data. If you can access that data, as well as the insights of the stakeholders who curate and cultivate it, you have a whole new world of opportunities to be able to build robust, meaningful models. It’s easy to just go with what’s out there, such as U.S. Census data, to answer questions that the literature is asking of us. There’s a place for that. But if we’re really going to be influencing decision-making and trying to move this needle fast enough for a complex, global future, we need a different process. By zeroing in from the very first mile, we can better determine the questions and the data available to bring to the scientific process.

As you talk about asking the right question from the outset and understanding the datasets out there, how do you accomplish that in a global world? We are working on global futures, not regional futures. How does DT 3.0 better take into consideration cultural factors to help make holistic decisions for stakeholders?

Laubichler: From a strictly scientific point of view, global futures point us to something science, by and large, has ignored. We live in what’s called the Anthropocene. What that means is that we can no longer understand nature independent of our actions. The whole scientific epistemology is based on the distinction between the observer and the observed, so that based on having an objective data set about what we observe, we can create an understanding of that world independent from us as the observer. That no longer holds because in the Anthropocene, we live in a planetary system that is primarily affected by human action. What we need to develop as a new scientific methodology is a way of modeling the planetary system together with the effects of our actions. This is hard because it hasn’t been done. Now, the way to get into this is through what Patricia described as the first mile because this is a way to understand and appreciate that it is the diverse, local human activities that define the problem, and then scaling up to the global scale. DT serves as a way that helps us get into this necessary transformation of the science of global futures. To transform planetary systems, we must factor in — and be able to steer — societal inputs and societal consequences.

Solís: Exactly, as Manfred said about scaling up, our science and our models need to be designed in such a way that we can look at multiple scales. Every decision-maker has a jurisdiction, they have a space in which their actions take effect. For example, the boundaries of the state versus the boundaries of the county versus the boundaries of the watershed. The governing authorities in these jurisdictions all have different spheres of influence. We need to be able to navigate through all that complexity because different decision-makers have different influences. If we can get the question right, in the beginning, we understand who can make this decision and what they need to know to make good or evidence-based decisions. That helps us navigate scale across futures.

Solís: Exactly, as Manfred said about scaling up, our science and our models need to be designed in such a way that we can look at multiple scales. Every decision-maker has a jurisdiction, they have a space in which their actions take effect. For example, the boundaries of the state versus the boundaries of the county

What are some of the proof points to demonstrate that this new DT approach will work? What do you see as the potential long-term successes?

Solís: At KER, we’ve been working a lot on heat resilience, the one multiplier threat that we have here in the Phoenix metro area that I think we’re going to see reverberate across the globe. Arizona is at ground zero for changes that we’re going to see as temperatures rise. One of the things I think we could do for the world is to improve understanding and mitigate some of the impacts of heat effects across all our systems. One of the things that I see as proof of success would be if we could really develop different kinds of modeling around housing. Heat affects people where they live, where they sleep, where they reside. It affects the roads that we drive on and our city infrastructure. And heat affects our health. Right now, all those systems are really siloed. I have high hopes for Decision Theater that we can start to integrate across datasets so we could say when the temperatures rise, we expect these different impacts. This is how much it costs; this is how much the solutions will cost. This will be how much we can mitigate, and this is the price tag for all those changes, to optimize and mobilize action. It might seem simple, but we are not yet able to answer some fundamental questions in a way that affects decision-making. If we can come up with one or two key decisions that can really attenuate the effect of heat, then DT will have been hugely successful.

Laubichler: What Patricia just said is the blueprint for the science of global futures. We have to grow our understanding of large-scale dynamics. Let’s take temperature as an example. From a complex systems point of view, if this variable changes, what are its consequences? What are the policies, what are the decisions? What is the earth-systems science dimension and the known dynamics of heat and temperature change? What are the consequences for health? What are the consequences for livability in certain areas? What are the consequences for migration? What are the consequences for the whole built environment? So, we want to build an integrated systemic model that captures all this and helps target the intervention points in that system. This is a complex systems perspective geared toward identifying the levers in the system.

A core purpose of the Julie Ann Wrigley Global Futures Laboratory is to be anticipatory, to avoid challenges and problems. At this moment in time, we have deadly flooding in Pakistan and in Mississippi. Climate change is a likely culprit, but we’re also seeing complete destruction and breakdown of the infrastructure in these two disparate, populated areas. How can DT help prevent similar disasters in the future?

Solís: I think DT 3.0 needs to help us make up for lost time

Laubichler: Extreme events are part of the normal variation in the system, except that they are now much more frequent and much larger. We can directly attribute that kind of amplitude and frequency to the Anthropocene. For the areas that are currently afflicted, the question is, how do you rebuild? What decisions do you have to make, and what tools do you have to give those local communities, to take that unfortunate, traumatic experience and channel it into productive, anticipatory action for adaptation? In the future, we should be in a position to go to Mississippi and set up a DT event with local decision-makers and experts in the community, and say, “Let’s bring together all that you just experienced, and determine what we can anticipate the potential future scenarios will be and establish a strategy of rebuilding the infrastructure in a way that would allow you to deal with these events.” In my vision, DT comes in after the Federal Emergency Management Agency leaves. There is an immediate urgency to distribute water and those kinds of things, but generally once FEMA leaves, those communities are left to their own devices. And what they do is generally rebuild as they did before. That’s a pattern we must break because what we saw this summer is basically every single square inch of this planet experiencing a climate-induced crisis.

Solís: Indeed we do, Manfred. And what are the urgent solutions, the response solutions, the incremental solutions and also the multiplied solutions? Like heat has a multiplier effect, you can find some synergy in solutions, too, if you’re putting this in the right kind of modeling environment. You could find an optimal solution that solves more than one problem at one time.

The Global Futures Laboratory recognizes the next 10 years as a decisive decade for action. We’ve talked very conceptually about DT, but pragmatically, what does it take to get to DT 3.0?

Laubichler: We need to restructure the organization of DT, and we need to invest quite a lot of money into DT because it has been under resourced for a while. There is clearly an opportunity for the philanthropy community to invest in this solution-oriented technology. But the most important change is that we need to bring DT into the core of the science of global futures. We need the Global Futures’ Scientists and Scholars Network to look at their research interests and activities, and put them through the conceptual frame of DT 3.0. We must invite our scholars and researchers to really make use of DT 3.0 because that is the way that they can have real impact. We also need to structure the technical and modeling expertise to build this kind of integrative systems perspective that would allow us to see all the ripple effects of a potential change.

Solís: The only thing that I would add from the knowledge exchange perspective is I think we also have to perfect that vision of being open to the community, so that our community really sees our university and its experts as something they can access, something that they can be part of.