Biomimicry, big data and artificial intelligence for a dynamic climate change management policy regime

Abstract

The adverse impacts of climate change are not always immediately discernible. Managing the impacts of this dynamic phenomenon demands an equally dynamic policy regime instead of the traditional and often static policy response mechanisms. The traditional policy responses are often a result of long consultative processes sometimes stretching over several years. Frequently, this generates obsolete policy responses. In this chapter, we propose the development of a dynamic policy and legislation formulation and implementation system that respond to dynamic disturbances such as climate change. The proposal draws from natural systems that have been constantly evolving over aeons. The proposed approach uses the systems lens of biomimicry positing that lessons from natural systems can be mimicked using models that rely on artificial intelligence (AI) to monitor changes through analysing and learning from Big Data and utilising rapid feedback loops to subsequently self-improve policy response mechanisms. Hypothetically under this approach, some key indicators for climate change and related hazards, exposure, risks and vulnerability can be tracked and material policy changes automatically made to appropriately to mitigate and/or adapt to climate change thus avoiding the pitfalls of the traditional protracted policy change routes.