By Wilfred Ndifon
Human societies face tremendous challenges, including disease epidemics and the life-altering impacts of climate change. To find better ways to address these issues, people should apply principles learned from nature.
For millions of years, nature has repeatedly offered solutions to important problems, such as immune systems to help fight diseases or cognitive systems to help organisms make sense of themselves and their surroundings. Nature developed these solutions through the processes of genetic mutation/recombination and natural selection. Societies can solve problems by re-purposing nature’s solutions to similar problems and by applying evolutionary principles.
First, the solutions that already exist in nature need to be understood in order to be re-purposed. Significant progress in this area is already being made. For example, scientists recently found that soils are replete with chemical compounds that have antibiotic activity, which could be used to address the important problem of antimicrobial resistance. Natural biomolecules are being re-purposed for medical applications such as repairing damaged human tissues. Microbial organisms are being harnessed to recycle carbon and to produce various substances for agricultural and other purposes, with the potential to improve global food security and mitigate the impacts of climate change. Despite this progress, societies can accomplish a lot more by understanding the organizing principles of nature’s solutions to particular problems. For example, understanding the principles by which immune systems fight diseases will enable the development of improved vaccines, and uncovering the principles of human cognition will make it possible to build machines that think like humans and even solve problems intractable for humans alone. Fundamental scientific research is required to elucidate these and other principles of nature.
Second, applying evolutionary principles can facilitate the search for problem-solving ideas. Based on the writings of the philosopher David Hume, ideas can be classified into two general types: 1) simple ideas, derived directly from sense perceptions, and 2) complex ideas, including problem-solving ideas, which are formed by modifying/combining (“mutating/recombining”) simple ideas (“genes”) in accordance with logic and/or intuition. For example, the idea that something is hot is simple because it derives from humans’ perception of heat. On the other hand, the idea of a vaccine is complex because it results from combining simple ideas, such as the idea derived from Edward Jenner’s perception that contracting cowpox disease reduces a person’s chances of subsequently contracting smallpox. Societies assign values (“fitnesses”) to ideas, whereupon ideas and their progenitors are encouraged (“positively selected”), actively discouraged (“negatively selected”), or ignored. This relationship between ideas and values produces outcomes in a similar way to evolutionary processes, with particular combinations of ideas that align with socially determined values rising to the top.
Schematic illustration formed by assigning values to different combinations of simple ideas. Peaks in the landscape correspond to problem-solving combinations of ideas.
In particular, activities that enhance the mutation/recombination of ideas, such as working across disciplines, could make the search process for a problem-solving idea more successful. All else being equal, an individual with expertise in many disciplines and a wider variety of ideas at his or her disposal is more likely to find problem-solving ideas than someone with expertise in only a single discipline. Similarly, teams comprising individuals with expertise in multiple disciplines are better placed to solve problems compared to single-discipline teams. What is important, however, is not only the scope of the ideas represented, but also the relatedness of those ideas and their relevance to the problem under consideration. Little benefit is derived from combining ideas unrelated to each other or to the problem at hand.
As the relatedness of the ideas increases, the likelihood that valuable surprises and innovations will arise from combining them also increases—to a limit. Beyond that limit, further increases in the relatedness of the ideas become counter-productive, as it becomes more difficult to identify the connections that can actually solve the problem. I apply these thought processes in my own work, such as when solving the problem of the original antigenic sin and explaining why certain useful components of the human immune system suddenly disappear in the eighth decade of life.
In addition, ideas should be valued as objectively as possible, and individuals should be rewarded based on their ideas’ values. When ideas and their progenitors are valued based on nepotism and related corruptive practices, this invariably leads to worse search outcomes. To understand why, imagine an experiment conducted to find molecules that bind a particular ligand by simulating the evolution of an initial population of poor ligand-binders. In the first step of the experiment, individual molecules are replicated by an error-prone process, producing new, mutated copies. In the second step, a subset of the molecules is selected for further replication, each with probability proportional to its measured affinity. These steps are repeated many times.
Over time, the population of molecules would traverse an evolutionary landscape produced by the mapping between different molecules and their measured affinities. If the measurement of affinities is accurate, then successive steps of the experiment would produce better solutions to the ligand-binding problem. On the other hand, if it is inaccurate, then improved solutions might never be found. Similarly, the valuation of ideas must be accurate (i.e. objective) to enable progress toward better solutions to problems. Still, while more valuable ideas should be preferred when trying to solve problems, ideas that are neither better nor worse than existing ones should not always be discarded because they might eventually lead to valuable innovations.
Societies can improve their search for solutions to problems in two main ways: by improving the understanding and application of nature’s organizing principles, particularly through the study of science, engineering and mathematics, and by enhancing opportunities for the mutation/recombination of relevant ideas and ensuring that ideas and their progenitors are objectively valued. These evolutionary principles can enable the establishment of cultural forms best able to produce solutions to any problem. Societies should facilitate their adoption, beginning with incentivizing adherence to social norms that foster a vibrant culture of ideas, wherein new ideas are actively sought through contemplation, multidisciplinary study, and collaborations, and ideas are routinely subjected to appropriate intensities of positive and negative selection.
Wilfred Ndifon leads a team that conducts research in theoretical and experimental biology, with a focus on the human immune system. He is based at the African Institute for Mathematical Sciences. This article is based on a talk he gave in July 2016 at the Quartz Africa Innovators Summit.
[Photo courtesy of US Army Africa]