**1. Introduction and background**

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. One would expect a global and intense focus on managing the adverse impacts of this phenomenon across and between all governments, the private sector and virtually all of humanity. However, this is not the case. 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. Nevertheless, the scope and sophistication of policies and practices seeking to manage the various aspects of climate change continues to advance. The management of climate change manifests through the dual policy

approach that employs either/or and often both the market-based and the regulatory mechanisms of climate change management.

Market-based mechanisms involve creating economic instruments to direct the flow of finance, technology and capacity-building support towards innovations and actions that mitigate greenhouse gas (GHG) emissions to retard global warming and ultimately climate change [1]. The mechanisms are rooted in economic principles that seek to heighten the frugality of managing climate change through activities that do not compromise the efficacy of the embedded mechanisms. Two popular mechanisms under the market approach are the Kyoto Protocol rooted in the Clean Development Mechanism (CDM) and the International Emissions Trading (IET) [1]. The regulatory mechanisms, also called the command-and-control policies, invariably require polluters to take specific actions to reduce emissions [2]. Typically, these actions comprise the installation of particular technologies seeking to meet specific environmental management performance standards, that is, GHG emission reduction. While academics, policymakers and bureaucrats often make a distinction between these mechanisms, practice shows an overlap between the two. In fact, and largely, the two are mutually inclusive.

Although there is link between interventions related to climate change and economic indicators, there are other important indicators such as biodiversity that are difficult and perhaps not necessary to reduce to absolute monetary terms. For example, about 40% of the global economy relies on biological products, and 35% of the total jobs are dependent on ecosystem services that support sectors such as agriculture, construction, forestry, textiles and tourism [3, 4]. This indicates the complexity of variables that need consideration in any effective and efficient strategy for managing climate change. Such management, its related policies and legislation need to balance the economic, social and environmental approaches. 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. Such a delivery system equally demands a rapid, flexible and dynamic policy formulation, implementation and revision system. An important input to this system is relevant, adequate and accurate (as much as possible) data to enable the development of appropriate policies. Policymaking based on such data is the essence of evidence-based policymaking. 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 traditional complaint around managing climate change, climate change adaptation in particular has been the paucity of relevant quantities of data for processing to derive trustworthy information. However, this condition has and continues to improve rapidly and definitely. A combination of rapid and incessant increases, and improvements in the sophistication, affordability, compactness and use of technology are enabling the prompt generation and analysis of copious data sets. These large sets of both structured and unstructured heterogeneous data are known as Big Data. In principle, the timely (often in real time) processing of this data accompanied by appropriate policy responses can make a difference between the ability to rapidly as well as suitably respond to the climate change hazards and costly policy reform delays.

A challenge in the policy arena is that outside absolute dictatorships, contemporary and 'acceptable' policy formulation, adoption and implementation processes follow a routinely lengthy bureaucratic and linear approach. These processes often exclude the views of one or other concerned group(s) through a typical

## *Biomimicry, Big Data and Artificial Intelligence for a Dynamic Climate Change Management… DOI: http://dx.doi.org/10.5772/intechopen.84406*

accentuating of internal bargaining among small, highly placed powerful groups [6]. Actors in the policy space bargain around their personal beliefs and preferences as well as those of interest groups they represent. These beliefs and preferences may initially vary widely but are narrowed by the give-and-take practices of the bargaining process. Consequently, the policy outcomes of the process rarely advance the absolute views of single individuals but instead are a mix of views from several individuals [6]. While this is the essence of democracy, the disadvantage is that the nature of bargaining processes usually delivers suboptimal policy outcomes and often belatedly. While the importance of democracy in policymaking is acceptable, the delivery of suboptimal and delayed policy responses is problematic in dealing with dynamic and deleterious effects of phenomena such as climate change, economic development and human health, among others. Ideally, the desired policy responses must be dynamic, and more importantly, they must deliver systemic changes for efficient policy implementation, monitoring and evaluation that may lead to either to policy entrenchment or revision.

Nature is replete with forms of order and seemingly systemic changes in large complex systems. In principle, the policy formulation, implementation and revision space can draw important lessons from the collective and individual units of biological systems such as cell colonies, schools of fish, ant colonies and bird flocks. A protuberant characteristic of collective behaviour in such natural systems is the appearance of global order in which individuals harmonise their states to an extent of giving a striking impression that the group behaves as one [7]. While it is posited that group formations in systems such as insect swarms are a mere epiphenomenon of the independent interaction of each individual with an external landmark and stimuli, what matters is that the resultant order remains impressive and individual actions culminate in a collective benefit. While group formations are impressive, nature also shows deeper and long-lasting systemic changes that confer adaptation of individuals and entire ecosystems to external conditions.

Looking at how nature both rapidly and gradually but systemically adjusts to a plethora of stimuli and eventually achieves a 'dynamic equilibrium', it is arguable that managing climate change, that is, adjusting both mitigation and adaptation strategies and regimes, can learn from biological systems. 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. Ideally, the proposed approach was appropriate and should seek to avoid the lengthy policy cycle stages but still deliver a systemic and responsive policy to manage climate change narrowly and sustainable development broadly. The suggested and futuristic policymaking approach is cognisant of the fact that there is limited clarity around the concept of global order in many biological systems. It is also aware of fears around artificial intelligence/machine-learning phenomena as well as the contests and power dynamics in the policymaking space. Nevertheless, we posit that lessons from how natural systems both as individual and most relevantly as a system have and still evolve to adapt to changing environmental conditions carry important learning points for the proposed policymaking approach. As stated earlier changes in natural systems are both immediate as in the case of a school of fish avoiding predators and slow, for example, how the ecosystems have adapted to ionising radiation from Chernobyl [8]. Even slower is that birds of flight have evolved to have hollow bones strengthened by struts to reduce dead weight, whereas flightless birds like ostrich have more solid bones. In the case of birds of flights, bones in places with higher stresses are more solid. This principle informs the building of the shells of modern aircraft to optimise weight and strength of designs. Eliminating unrequired

material means less dead weight, less fuel consumption and thus a lesser carbon footprint. Indeed Mother Nature can be a model, measure and mentor.
