Humans have a formidable trait of learning from nature as we build, design and innovate. Our ‘natural intelligence’ and ability to mimic and draw inspiration from biological and abiological nature has skilled us to design shelter, vehicles, functional and structural materials, optics, and myriad innovations.
Artificial intelligence (AI) has originated from our ability to mimic natural intelligence — those of higher-order organisms, including us humans, and lower-order organisms — but modern AI pursuits have forgotten these roots.
The celebrated systems theorist John von Neumann’s concept of self-replicating automata (1958), Norbert Wiener’s concept of self-regulating mechanisms in his path-breaking modern use of the term cybernetics (1948), the renowned psychologist Frank Rosenblatt’s work on perceptron algorithm for image recognition (1960), Warren McCulloh’s and Walter Pitt’s pioneering study on artificial neural networks (1943), and Joshua Lederberg’s post-Nobel prize work on dendritic algorithm ‘Dendral’ that set the stage for exobiology (search for life in the universe) and search for exotic organic compounds on Mars (1965) — all tried to mathematicise, compute, and mechanise biophysical and biochemical phenomena.
But after these successful initial trans-disciplinary pursuits, AI became increasingly siloed in computer sciences, information technology, and engineering domains.
Today, AI is considered an emerging technology of great importance across laboratories, business board rooms and parliaments. It is largely estimated to troubleshoot numerous end-of-the-road processes and make them appear mundane. Its conjoined usage with the term robotics often gives the impression that these two will serve humans.
Regardless of the intent of designing robots to serve humans, intelligence is a far more profound construct to serve the species.
AI attempts to simulate natural intelligence as we know it. But how much do we comprehend natural intelligence?
The answer is, very little.
The fact that we do not know how to use AI for understanding the simplest of life forms testifies to the fact that we are definitely far from able to simulate higher-order life forms and their intelligence.
In the 21st century, AI research will progress in a multipolar world, with each country approaching it with its innate civilisational understanding and philosophy. The diversity of approaches to AI is bound to accelerate the growth of the field.
In this, India will have to develop its innate two-pronged strategy for AI: a focus on ‘tactical’ AI, which is of immediate socio-economic consequence, and secondly, on ‘strategic’ AI, which will yield a multitude of returns over longer scales of time.
India’s current focus is largely on ‘tactical AI’ which has immediate applications in industry and governance and that is easy to adapt, assimilate and accommodate with the globally common AI.
However, it is the strategic AI and its scientific and technological niches upon which India ought to deliberate intensively. Strategic AI might not be of immediate commercial consequence, but it will give India primacy in the field.
India must make strategic AI a trans-disciplinary pursuit and not keep it limited to information technology, computation, and machine learning.
If science and technology policy-makers are to lay a strong AI plinth for India, they need to consolidate and co-nurture discrete disciplines, such as classical Indian philosophy (astika and nastika schools of thought), neurosciences, cellular biology, molecular biology, language processing, systems sciences, control theory, evolutionary biology, origin of life, astrobiology, fluidic robotics, and operations research.
Natural sciences and indigenous philosophies are the bedrock of AI. The trans-disciplinarity is particularly important now, with the world on the verge of the Fourth Industrial Revolution — as strategic AI has begun to diversify in a major way into new pursuits for artificial consciousness, artificial cognition, artificial sentience and artificial sapience.
India’s philosophical riches and unique outlook on the natural sciences will go a long way in enriching global comprehension, not only of natural and Artificial Intelligence, but also our search for extra-terrestrial intelligence. If AI is to grow in tune with human needs and safety, humans will have to put in diverse efforts to learn more about nature and natural intelligence.
Chaitanya Giri is Fellow, Space and Ocean Studies Programme, Gateway House.
This article was originally published by Swarajya.