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The urgency of global societal challenges is clear and I strongly believe that Artificial Life, with its combination of tools, approaches and philosophy has immense potential to engage with real world problems. However, we must develop this potential from ideas into experiments and practice in collaborations with other disciplines and those working on the ground. This will require us to think both critically and creatively about our possible roles and our assumptions.
In order to illustrate some of the challenges and potential responses to working under “real world” constraints, I will describe my work with the UK government as part of the CECAN (Centre for Evaluation of Complexity Across the Nexus) Project, which aims to design and deliver innovative complexity-appropriate tools for policy evaluation in complex adaptive systems. In particular I will discuss participatory systems mapping work and co-production approaches in work with DEFRA, the department for Environment, Food and Rural Affairs and with BEIS the department for Business, Energy and Industrial Strategy. This method allows system stakeholders to collaboratively develop simple causal models of a complex system, consisting of a system’s key components, from any domain, and the causal interconnections between them. Models can encapsulate a broad range of important influences without quantitative information. It is particularly useful in systems in which there are many interacting factors, including policy interventions, and when system information is distributed amongst diverse actors. It is a powerful tool for bringing together system knowledge in a visually compelling and understandable way, rendering complexity more tractable and increasing ownership. It sets policy within a fuller context, allowing exploration of potential unexpected indirect effects and interactions of policy or policies on and within the system in which they are embedded. Network analysis of maps, combined with stakeholders’ information, can identify system vulnerabilities or bottlenecks; highly structurally-influential factors on which issues important to stakeholders depend and which may be variable or difficult to influence. Or, conversely, levers, which may be effectively used for change. Most importantly, this method can be used within the constraints of policy contexts and provide actionable insights whilst simultaneously highlighting the reality of policy domains as large, dynamic complex systems in which policies interact with extant human systems involving the interactions of social, economic, technical and ecological components.
In the second part of my talk, I will give an overview of the proposed contributions that ALIFE can make, as well as highlight the areas in which perhaps we need to think more carefully. These are ideas that have been collectively generated over the course of the ALIFE and Society conference sessions and societal impact section of the Journal of Artificial Life since 2016. I will use this as an opportunity to invite an ongoing discussion throughout the conference on how we as a community could proceed. I would like to go further in inviting us to address the question of what, if anything, ALIFE offers that other communities do not (complexity or systems sciences or the resilience community for example). And how do we take this forward to generate new thoughts and ideas, as well as to consider the provisos, the challenges, and the guiding principles for working which could allow us to make a genuine difference to real world societal challenges.