Science is an Analogue Process

We hear so much these days about science, with data and models and how supercomputers crunch these things to tell us the future and it all seemed so wonderful and so simple to believe. And yet they keep getting it wrong. Why could this be? What is the problem? It could simply be that all the above are digital processes and yet, at its heart, science isn't digital.

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This is an era increasingly defined by digital precision and binary systems where the data drives decisions more than any judgement by human beings. So it might seem counterintuitive to consider science as an analogue process. That word "analogue" often evokes images of retro dials, vinyl records, and continuous waveforms which is a stark contrast to the binary on-off logic of digital systems. However, at its most fundamental level, science is inherently analogue. It is a continuous, dynamic process, reflective of the intricate, often unpredictable nature of the real world it seeks to understand. Recognising science as an analogue process not only enriches our appreciation of scientific inquiry but also underscores the complexity and nuance required to grasp the realities of the natural world.

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Let me start with the simple assertion that science is not a static collection of facts; rather, it is a continuous and never-ending process of ongoing inquiry and discovery. Scientific knowledge evolves through the accumulation of evidence, the testing of hypotheses, and the refinement of theories. This process is rarely linear or straightforward (digital). Instead, it is characterised by a spectrum of possibilities, where outcomes are not simply right or wrong, but fall within a range of probabilities. This analogue nature of science is akin to how physical quantities like temperature, pressure, or time are measured along a continuum, rather than in discrete steps.

Let’s consider the process of scientific measurement itself. Whether it is the length of a coastline, the concentration of a chemical in a solution, or the speed of light, measurement in science is rarely exact. It is always subject to a degree of uncertainty, often represented by a range of values or error margins. This uncertainty is not a flaw but a fundamental aspect of the analogue nature of scientific inquiry and key to the power of the Scientific Method. Scientists understand that measurements are approximations, influenced by the limitations of instruments, the conditions under which experiments are conducted, and the inherent variability of the natural world.

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As an example, the measurement of a coastline can vary dramatically depending on the scale at which it is measured. A satellite view might show a smooth outline, while a closer inspection reveals intricate curves and details that increase the measured length. This phenomenon, known as the "coastline paradox," illustrates the inherent complexity and analogue nature of scientific measurements. No single measurement can capture the full reality, highlighting the importance of considering the continuum of possibilities rather than seeking an absolute answer.

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Furthermore, scientific theories themselves are constantly subjected to revision and refinement as new evidence emerges. Theories are never settled “Final Truths” but rather the best explanations available at the time and always subject to change as our understanding deepens. This iterative process of theory development is another example of the analogue nature of science, where knowledge is continuously expanded and refined, rather than simply accumulated in discrete, binary increments.

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Let me now expand upon the role of analogue thinking in scientific progress. At the heart of scientific inquiry lies a form of thinking that is inherently analogue. Unlike digital thinking, which favours the binary distinctions of true/false or yes/no, analogue thinking accommodates subtleties. It allows for ambiguity, nuance, and the possibility that multiple explanations might coexist or even overlap. This kind of thinking is essential in many areas of science where simple, binary answers are insufficient to capture the complexity of the phenomena being studied.

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In fields of research such as quantum mechanics, for example, particles do not exist in well-defined states like on or off, but rather in superpositions, where they can simultaneously exist in multiple states. Similarly, in evolutionary biology, the distinctions between species are often blurred. Evolution does not proceed in discrete jumps from one species to another but through a continuous process of change and adaptation over time. This is why the concept of a "species" is sometimes difficult to define precisely - there is no clear dividing line, only a spectrum of variation.

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The practice of analogue thinking encourages scientists to consider a range of possibilities, to entertain multiple hypotheses, and to remain open to revision and reinterpretation. This mindset is crucial for scientific progress. For instance, the theory of evolution, first proposed by Charles Darwin in the 19th century, has been revised and expanded many times as new evidence has emerged from genetics, palaeontology, and developmental biology. Each new piece of evidence adds to the continuum of knowledge, refining our understanding of how life on Earth has evolved. This iterative process of refinement and revision reflects the analogue nature of science, where knowledge is not simply accumulated in binary increments but is continuously expanded and deepened.

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While science is fundamentally an analogue process, the digital revolution has profoundly impacted how some scientific research is conducted. Digital tools have greatly enhanced our ability to collect, process, and analyse data, enabling scientists to model complex systems and simulate scenarios with unprecedented precision. High-powered computers can now process vast amounts of information, identifying the patterns sought and relationships that would be impossible to discern manually.

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However, it is crucial to recognise that even in these digital environments, the underlying processes being studied - such as climate systems, biological networks, or human cognition - remain inherently analogue. The natural world does not operate in binary code. It exists as a continuous, dynamic system where variables can change incrementally rather than in discrete steps. Thus, digital tools must often be calibrated to account for the analogue nature of the phenomena they measure.

Consider, for example, digital sensors that convert continuous physical quantities into digital data. A thermometer measuring temperature or a microphone capturing sound waves both start with an analogue signal - a continuous variation in temperature or pressure. These signals are then sampled and quantified, turning them into digital data that can be processed by digital computers. However, this conversion process introduces a degree of approximation, as the continuous signal is reduced to a series of discrete points. The accuracy of this digital representation depends on the resolution of the sampling process, highlighting the ongoing interplay between analogue and digital approaches in science.

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Furthermore, in fields such as climate science, digital models are used to simulate extremely complex, dynamic systems. These models are based on mathematical equations that describe the chaotic analogue processes of the natural world, such as fluid dynamics, thermodynamics, and chemical reactions. The output of these models is typically a range of possible outcomes, reflecting the uncertainty inherent in the analogue processes they simulate. Thus, even as we rely on digital tools to advance our understanding, the analogue nature of the systems being studied remains a central consideration.

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Perhaps the most compelling evidence of science as an analogue process lies in the human element it is built around. Scientists themselves are not machines that operate in binary modes; they are complex beings whose thought processes, emotions, and intuitions are deeply analogue. Human cognition, perception, and creativity are characterised by continuous thought processes, subjective experiences, and intuitive leaps, all of which play a crucial role in scientific discovery.

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Possibly because of the human element the process of scientific discovery is often non-linear and unpredictable, marked by trial and error, serendipity, re-evaluation and reinterpretation. For instance, the discovery of penicillin by Alexander Fleming was a fortunate accident, a serendipitous moment that could easily have been overlooked in a strictly binary, digital approach to science. This example highlights the importance of maintaining an open, analogue mindset that is receptive to unexpected results and willing to explore new avenues of inquiry.

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Moreover, scientific debates and peer reviews, essential components of the scientific process, are also analogue in nature. They involve the weighing of evidence, the consideration of alternative interpretations, and the application of judgement - none of which can be reduced to simple yes-or-no answers. Peer review, for instance, is not about determining whether a study is absolutely correct or incorrect but about evaluating the robustness of its methods, the validity of its conclusions, and the significance of its contributions. This analogue dimension of human cognition is what allows science to adapt, evolve, and ultimately progress.

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The international aspects of scientific collaboration in places like CERN, further exemplifies the analogue nature of the process. Researchers from different disciplines and cultures often bring diverse perspectives, methods, and assumptions to a problem, leading to a rich, nuanced understanding that could never be achieved through a single, binary approach. This interdisciplinary collaboration reflects the analogue process of science, where the integration of different viewpoints and the synthesis of diverse data lead to a more comprehensive understanding of complex phenomena.

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As we move further into the digital age with the addition of AI, it is crucial to recognise and embrace the analogue nature of science. While digital tools have become indispensable in modern research, they should not overshadow the fundamental principles of scientific inquiry, which are rooted in the continuous, analogue processes of observation, experimentation, and interpretation.

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This digital revolution has brought many benefits, but it has also led some commentators to oversimplify complex phenomena, to reduce them to binary terms or to over-rely on models and simulations that, while powerful, are still limited by their digital nature. This can lead to a false sense of certainty and an underappreciation of the uncertainties and complexities that are inherent in the analogue world.

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Only by embracing the analogue nature of science, can we maintain a more balanced and nuanced approach to scientific inquiry. We can recognise the limitations of digital models and simulations and continue to value the role of human judgement, creativity, and intuition in the scientific process. In doing so, we ensure that science remains a dynamic, evolving field that is capable of adapting to new evidence and new ways of thinking.

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In addition, understanding science as an analogue process has important implications for how scientific knowledge is communicated to the public. In an age where digital media often favours oversimplification and binary narratives, there is a risk that the complexity and nuance of scientific inquiry may be lost. Communicating science effectively requires acknowledging its analogue nature, presenting findings with the appropriate context, uncertainties, and degrees of confidence.

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Science communicators have the challenge of conveying that scientific conclusions are not absolute truths but rather the best explanations available and will be subject to change as new evidence emerges. This involves educating the public about the iterative nature of science, where hypotheses are continually tested and refined, and where uncertainty is not a weakness but a fundamental aspect of the process. By embracing the analogue nature of science in communication, we can foster a more informed and engaged public, capable of understanding and appreciating the complexities of the scientific process.

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In this world, which is being increasingly dominated by digital technology, it is easy to overlook that the true nature of science is analogue. Yet, despite the dazzle of digital, at its heart science remains fundamentally a continuous, dynamic process that mirrors the complexity of the universe it seeks to understand. The continuum of discovery, the iterative refinement of theories, and the analogue thinking required to navigate the nuances of scientific inquiry all highlight the profound limitations of a purely digital approach to understanding the world.

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As we continue to develop and rely on digital tools to advance scientific research, it is crucial to remember that the essence of science lies in its analogue nature, which in turn, seeks to reflect the analogue nature of the universe we are trying to understand. The real world is not digital; it is a rich tapestry of continuous variables, probabilities, and uncertainties. Only by embracing the analogue nature of science, can we foster a deeper appreciation for the complexity of the natural world and the ongoing process of discovery that drives scientific progress. Science, in its pursuit of understanding, remains a fundamentally analogue process, one that reflects the endless shades of grey that characterise our universe.

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