Why history warns us against underestimating transformative technologies
Prof Suresh Chander
suresh.chander@gmail.com
Every major technological shift in history has followed a familiar pattern. In its early years, a new technology is judged not by what it could become, but by what it can immediately do. Leaders focus on efficiency, cost reduction, and productivity-while the deeper consequences remain invisible.
Artificial Intelligence today stands at precisely this moment.
Around the world, governments, corporations, and institutions speak of AI as a tool for automation, optimisation, and acceleration. These are important uses, but they reflect a limited imagination. History suggests that when technology is framed only as an improved tool, society misses its most profound implications.
When Revolutionary Technologies Look Modest
In the mid-20th century, computers were developed to solve scientific and military problems. They were expensive machines, housed in special rooms, operated by experts. No one imagined personal computers, smartphones, social media, or digital economies.
Computers were seen as faster calculators, not as agents of social and cultural transformation.
A similar story unfolded in control systems engineering. Early control theory dealt with simple feedback mechanisms-regulating machines and industrial processes. Over time, these ideas expanded into aviation, space systems, robotics, economics, and even biology.
One of the pioneers of the field, Hendrik W. Bode, later remarked that he no longer recognised the control systems of his own era. The discipline had evolved far beyond its original boundaries.
The lesson is clear:
Transformative technologies do not merely improve existing systems-they redefine the systems themselves.
AI Today: Powerful, Yet Narrowly Understood
AI today is widely celebrated for:
* Automating routine tasks
* Analysing vast datasets
* Improving decision speed
* Reducing human error
These achievements are real. But they also confine AI to a familiar role-that of an efficiency engine.
This mirrors the early years of computing, when innovation was measured by speed and accuracy rather than societal impact. We are asking how AI can do what humans already do-but faster.
What we are not asking often enough is:
* How will AI change the way knowledge is created?
* How will it reshape human judgement and responsibility?
* How will it alter institutions, governance, and leadership itself?
Leadership failure often begins with conceptual failure-when the future is interpreted using outdated frameworks.
Fear Dominates the Debate-But Fear Misses the Point
Public discourse on AI is dominated by anxiety:
* Job losses
* Surveillance
* Deepfakes and misinformation
* Loss of human control
These concerns are legitimate and must be addressed. But history shows that fear usually focuses on visible disruptions, while the most enduring changes unfold quietly.
The printing press did not merely disrupt scribes-it transformed religion, politics, and identity. The internet did not just speed up communication-it blurred the boundaries between public and private life.
AI’s deepest impact may not be dramatic or immediate. It may lie in areas that are less visible, but far more consequential.
Beyond Machines: AI and the Non-Physical World
Most policy discussions assume that AI will reshape the physical economy-factories, offices, logistics, defence systems. But its most profound influence may be on the non-physical foundations of society.
How Humans Think
AI externalises reasoning in the same way writing once externalised memory. Human intelligence may increasingly become collaborative-distributed across people and machines. Learning may shift from memorisation to interpretation and judgement.
How Knowledge Is Defined
When access to information becomes universal and instantaneous, traditional hierarchies of expertise are challenged. Authority shifts from possession of knowledge to the ability to contextualise, evaluate, and ethically apply it.
How Culture Is Created
AI-generated art, narratives, and ideas complicate notions of originality and authorship. Culture may become less about individual genius and more about collective meaning-making.
These changes are not technological; they are civilisational.
Why Leadership Consistently Gets the Future Wrong
There are structural reasons why societies underestimate transformative technologies:
* New tools are described using old language
* Regulations are built for yesterday’s realities
* Institutions resist change to preserve stability
* Leaders assume linear progress instead of disruptive shifts
India’s own experience offers a reminder. Digital identity, mobile payments, and large-scale public technology platforms were once seen as unrealistic. Today, they shape everyday life and global conversations.
AI may follow a similar trajectory-starting as an efficiency tool and evolving into a defining feature of governance, education, and social organisation.
The Leadership Challenge of Our Time
For global and Indian leaders alike, the challenge is not whether to adopt AI-it is how to think about it.
Treating AI merely as a productivity enhancer risks repeating historical mistakes. The real test of leadership lies in preparing societies for changes that cannot yet be fully described.
This requires:
* Intellectual humility
* Ethical foresight
* Investment in education and institutional redesign
* A willingness to rethink long-held assumptions
Conclusion: From Fear to Foresight
Future generations may look back at today’s debates on AI and find them surprisingly narrow-focused on speed, efficiency, and control, rather than transformation.
Just as early pioneers of computing could not imagine the digital societies of today, we may not recognise the AI systems of the future-not because they failed, but because they evolved beyond our present understanding.
The task of leadership, therefore, is not to predict the future perfectly, but to create conditions where society can adapt wisely.
AI is not just a technological challenge. It is a test of imagination, governance, and moral responsibility.
Those who approach it with fear alone will react too late. Those who approach it with foresight may help shape a future that remains recognisably human-even as intelligence itself takes new forms.
(The author is former Head of Computer Engineering Department in G B Pant University of Agriculture & Technology)
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