The Resolution of Revolutions

This essay was submitted by Sukanya Chakraborty for the 2019 NxG Science Communicator Competition.

“If I had an hour to solve a problem and my life depended on it, I would use the first fifty-five minutes determining the proper questions to ask.”

– Albert Einstein

We humans, arguably the pinnacle of evolution in today’s world, have been driven by an insatiable thirst to ask questions since time immemorial. How far are we from the Sun? How did life evolve? What happens when subatomic particles collide? Why do we age? The questions never cease. We have the potential to ask, explore, investigate and ponder the relentless mysteries before us. We may not always arrive at the answers, yet, this very power and desire is what sets us apart from all other life on Earth. What have we chosen to do with this gift? Evidently, we use it to address challenges faced by society, strive to cure diseases, save the earth, and build unfathomable automated machines. What is remarkable in this pursuit, is the transition of scientific exploration from simple descriptions to complex hypotheses and sophisticated experimentation.

When Ancient Egyptians started probing into the preserved remains of their deceased rulers, little did they know that their naive curiosity was laying the foundation stones of the practice of organized medicine. The Babylonians, who started inscribing the observed celestial patterns on clay, giving birth to modern astronomy, were just as oblivious. In fact, it might have been Aristotle’s inductive-deductive reasoning methods which steered early thinkers to adopt rational and factual approaches, breaking free of the restraints of teleological empiricism. Galileo pioneered the advent of the alleged “thought” experiments, with his discovery that objects of different weights when dropped from the same height, fall to the ground at the same time. This ingenious school of thinking has led to some groundbreaking theories prevailing till date, including Einstein’s theory of Special Relativity. Amidst the dilemma of which school to adopt as a justified scientific method – empiricism or rationalism, many regard the resolution to this conundrum to have come from Isaac Newton’s profound contributions. His seminal work on motion and gravitation all incorporated a structured approach of observations, hypotheses, experiments and deductions.

The paradigm adopted in addressing challenges developed through the course of many years, and the efforts of many great thinkers were influential in shaping modern scientific methodology. Needless to mention, the singular event that might have revolutionized research findings would have been the incorporation of statistical tools in substantiating collected data. Be it in supporting theories of Mendelian Inheritance or Darwinian Evolutionary theory, modelling energy states of thermodynamic systems, or merely, framing theoretical probability distributions, there is probably no field that has not been permeated by statistical approaches. Data quantification has left an indelible mark on the progress of scientific investigation.

Another radical journey in experimentation has been the advent of instrumentation. When the average Paleolithic man started fashioning tools out of metal and stone, they inadvertently paved the way to modern day innovations. The steam engine has now given way to high powered electricity generators, Turing Machines, and quantum computers.  It is now possible to process, and store instructions fed into a computer through a 30 mm chip containing integrated circuits, and perform seemingly impossible calculations in a few seconds. In essence, it appears that human thinking still has the same zeal, but what has changed is the ability to compile and execute ideas in shorter and more realistic time frames.

The study of neural networks exemplifies the above aspects of science: hypotheses, statistics and experimentation. The brain is an incredibly complex interwoven web of interactions, rewiring its circuitry with everyday experiences. The integration of action potentials and plasticity of the innumerable synaptic connections, led researchers on a quest to find how intelligence emerges from neuronal interactions. Through several decades, the discipline of modelling neural networks was born, replete with hypothetical answers to profound questions, such as the generation of dynamic patterns in memory formation or imagination, indiscernible from the conscious mind. Beginning with the simple studies of reflex arcs, the realization was reached that neurons are incredible computational devices. This naturally attracted the attention of scientists from other disciplines. The sincere endeavors continue to aim to emulate the process of self-assembly of synapses in artificial models, and thus recreate the networks of our mind.

Where do we go from here? All that the brain of man has achieved till now, and will probably continue to achieve in the future, is mesmerizing. Yet, it would not be justified to simply marvel at the progress without introspection. We can make intelligent machines “learn” now, incorporate experience into computers to understand the world in terms of a hierarchy of concepts. In all likelihood, humans may no longer remain indispensable to practice science. Exalted to the status of Machiavellian gods, would we forget our roots?

The advancements in research methods, should therefore, be keenly monitored as well. Although this progress has made it possible to achieve many aims with admirable ease, it would probably do us all good, if we paced our efforts without losing sight of ethical grounds. The emphasis on interdisciplinary research to address the dynamic palette of scientific challenges facing current society has received significant impetus. This collaborative science has emerged as possibly one of our greatest strengths in the 21^st century. The astonishing feats of science and ways to conduct this science, is indeed an arduous journey. We have been standing on the shoulders of giants and will also, through the revolutions of our age, leave footprints on the sands of time.

 In the words of Robert Lanza, the propounder of the Biocentrism theory, “Sometime in the future, science will be able to create realities that we can’t even begin to imagine”. It is now unequivocally safe to say that this fervour and passion herald the break of a new dawn and hold the promise of achieving a brighter tomorrow.

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References:

1. Hintikka J. (2004) Concepts of Scientific Method from Aristotle to Newton. In: Analyses of Aristotle. Jaakko Hintikka Selected Papers, vol 6. Springer, Dordrecht

2. Souder, L. What Are We to Think about Thought Experiments?. Argumentation 17, 203–217 (2003). https://doi.org/10.1023/A:1024071710337

3. Eagleman, David. The Brain : The Story of You. Penguin Random House LLC, New York. Pantheon Books, October 2015.

4. Kandel, E. R., Schwartz, J. H., & Jessell, T. M. (2000). Principles of neural science. New York: McGraw-Hill, Health Professions Division.

5. R. Lippmann, “An introduction to computing with neural nets,” in IEEE ASSP Magazine, vol. 4, no. 2, pp. 4-22, Apr 1987. doi: 10.1109/MASSP.1987.1165576