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.
Highlights
Introduction and backgroundDespite the near universally acknowledged, observed and predicted adverse impacts of climate change, a quandary in this space is the slow and inadequate policy and practice set of responses in climate change mitigation and climate change adaptation practices
This is because managing climate change is a complex and continuous process whose effectiveness is determined by the actions of diverse groups of individuals, communities, governments, local and international agencies all with a wide variety and, very often, conflicting agendas
We focus on two developments here, Big Data and artificial intelligence, and use these to propose a biomimicry-based policy cycle model for managing the challenges presented by the climate change phenomenon
Summary
Despite the near universally acknowledged, observed and predicted adverse impacts of climate change, a quandary in this space is the slow and inadequate policy and practice set of responses in climate change mitigation and climate change adaptation practices. What is important in the irrespective approaches is the timely provision of relevant data and information about potential hazards and potential benefits of climate change, globally and in specific locations This is critical to deliver appropriate, adequate and well-timed responses. The basis of evidence-based policymaking in the public policy space is the quest to anchor social reform programmes on pertinent and practical knowledge provided by scientific research [5] This approach elevates the importance of collecting and analysing the appropriate and adequate amount of data, both qualitatively and quantitatively. A timeous and appropriate adjustment of relevant policy levers is critical for managing climate change To this end, this chapter proposes a dynamic policy based on a learning, self-improving and self-adjusting policymaking approach that draws lessons from biological systems and it components—the essence of biomimicry. Mother Nature can be a model, measure and mentor
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