From industrial revolution to artificial intelligence

The history of technology is fundamentally a history of human adaptation. From the wheel, the printing press, the steam engine, and electricity to the telephone, the computer, and the internet -- every major technological transition has done more than merely simplify human life, it has transformed how we work, our economies, our social dynamics, and our vision of the future. Each epoch was marked by fear, uncertainty, and resistance. Yet, ultimately, humanity successfully adapted and integrated each innovation into daily existence.

Today, we stand at a similar threshold with Artificial Intelligence (AI). The critical question is: will AI seamlessly integrate into human lives like previous innovations, or is its speed and capability so unprecedented that traditional paradigms of adaptation will prove insufficient?

To address this question, we must first abandon the simplistic binary of viewing technology as inherently good or bad.

Technology is not inherently dangerous -- application determines value. What a technology is capable of doing and how humans choose to deploy it are two distinct matters. As technological capability expands, its potential applications broaden proportionally. The exact same technological foundation can be harnessed for human welfare or deployed for catastrophic destruction.

Nuclear technology offers the most compelling illustration of this duality. Nuclear energy contributes significantly to electricity generation, medical advancements, scientific research, and industrial applications. In 2024, nuclear power generated approximately 9.0 per cent of global electricity [1]. Simultaneously, nuclear technology led to weapons capable of threatening the very existence of human civilisation.

Thus, technology inherently contains dual possibilities-unprecedented welfare and devastating disruption. Which trajectory materialises depends overwhelmingly on human decisions, institutional capacity, legal frameworks, ethics, and political structures.

For this reason, asking whether AI is "good or bad" is an unproductive exercise. Instead, the discourse must centre on how AI is deployed, who controls it, and what governance mechanisms oversee its application.

The Industrial Revolution was once feared. Today, we view the Industrial Revolution as the bedrock of modern economics and industrial society. However, during the 18th and 19th centuries, the rapid expansion of machinery caused profound social anxiety. The fear that machines would strip away human livelihoods was entirely rational. As production paradigms shifted, traditional skills and occupations became obsolete, even as entirely new forms of employment emerged.

This reveals a critical principle: technology rarely eliminates tasks in a vacuum to leave permanent displacement. Rather, it transforms the fundamental nature of work. Certain specific jobs disappear, others are redefined, and entirely novel professions are created.

A similar trajectory is evident with AI. Research by the International Labour Organisation (ILO) indicates that the primary impact of Generative AI is more likely to augment and alter specific job tasks rather than cause complete job destruction [2]. A 2025 ILO analysis highlighted that while nearly one in four workers globally belongs to an occupation exposed to Generative AI, the majority of jobs are far more likely to undergo transformation rather than total extinction [3].

Therefore, claims that "AI will eliminate all jobs" are heavily exaggerated, just as assertions that "AI will leave employment completely unchanged" are unrealistic.

Social Anxiety is Natural and Necessary: Public anxiety surrounding emerging technologies should not be dismissed as irrational. When livelihoods, income security, social status, or hard-earned skills are threatened by technological shifts, concern is a natural response.

Similar apprehensions arose with the introduction of personal computers. The expansion of the internet disrupted established business models. Smartphones fundamentally restructured communication, journalism, entertainment, and commerce.

Social resistance to technological disruption is not an anomaly, it functions as a social-feedback mechanism. Society scrutinises new technology, seeks to define its boundaries, identifies potential vulnerabilities, and formulates regulatory standards to manage integration safely.

This constructive- feedback loop is already underway for AI.

Adaptation Extends Beyond the Individual: Adapting to technology involves far more than individuals learning new software. Genuine adaptation unfolds across multiple systemic levels:

1. Individuals acquire new skills and technical competencies.

2. Organisations re-engineer workflow processes and operational models.

3. Educational systems shift focus toward modern, future-relevant skills.

4. Legal and regulatory frameworks evolve to mitigate emerging technological risks.

5. Societal ethics adapt to build a consensus on acceptable versus unacceptable practices.

All five dimensions are essential for AI integration. Telling individuals simply to "learn AI" will not resolve systemic challenges. Reskilling and upskilling programmes are mandatory -- organisations must re-evaluate human-in-the-loop decision-making and education systems must move away from rote memorisation toward problem-solving, critical analysis, creativity, and comprehensive AI literacy.

AI Differs from Previous Technological Revolutions: However, a crucial distinction must be recognised.

While AI can be compared to the Industrial Revolution, the two experiences are structurally distinct. Industrial machinery primarily amplified human physical power. Computers expanded computational speed and information-processing capacity. Modern AI, by contrast, penetrates cognitive domains-engaging in language comprehension, visual processing, software coding, complex analysis, and decision support.

In short, AI is entering cognitive-work domains where previous technological tools had limited reach.

Another defining factor is speed. AI capabilities can proliferate across global societies far faster than previous physical technologies. This creates a critical gap between the velocity of technological advancement and the pace of human institutional adaptation.

This dynamic gap constitutes the central challenge.

Risk Does Not Equal Inevitable Catastrophe: Discussions around AI often fragment into two extreme perspectives: one predicting guaranteed existential doom for humanity, and another dismissing all concerns as baseless paranoia.

Both positions are fundamentally flawed.

The reality lies in the middle. AI presents tangible and pressing risks-misinformation, algorithmic bias, privacy violations, cybersecurity threats, automated decision errors, workforce disruption, and over-reliance on automated systems.

Consequently, AI governance is no longer solely the domain of technologists. The National Institute of Standards and Technology (NIST) AI Risk Management Framework emphasises four continuous functions: Govern, Map, Measure, and Manage [4]. AI risk management is not a one-time setup; it requires continuous lifecycle monitoring, evaluation, and mitigation.

This reflects a fundamental paradigm shift: we are not merely attempting to build safe code, but establishing social -and institutional-governance frameworks that ensure responsible AI deployment.

How Humanity Will Partner with AI:

The most realistic outcome is that humans will utilise AI while simultaneously transforming themselves.

A physician might leverage AI to analyse complex medical diagnostics, an engineer might use AI for advanced simulation and design, an educator might employ AI to personalise learning pathways, a journalist might rely on AI for deep research and data analysis, and a software developer might utilise AI for code generation and debugging.

The paradigm need not be "Human versus Machine." The real paradigm is "Human plus Machine."

ILO research consistently reinforces that Generative AI's primary trajectory will be augmentation rather than direct substitution.

Naturally, benefits will not be distributed equally. Certain sectors will face acute pressure, specific skills will depreciate, and demand for new capabilities will surge. Ensuring a just transition alongside technological acceleration is therefore imperative.

The Ultimate Determinant: Human Institutions: Ultimately, the future of AI will not be determined solely by technological power, but by how rapidly and intelligently human institutions adapt.

If educational frameworks remain outdated, workforce-development infrastructure remains constrained, and regulatory policies lag years behind innovation, AI will generate severe socioeconomic friction.

Conversely, if individuals proactively upskill, organisations establish collaborative human-machine workflows, governments implement agile regulation, and AI developers prioritise risk management as a core system component, AI can serve as a catalyst for unprecedented productivity and human progress.

This aligns directly with the philosophy of the NIST AI Risk Management Framework: maximising potential benefits while systematically mitigating harmful impacts.

From Fear to Preparedness: The history of technology provides a clear lesson: humanity initially fears new technologies, tests their limits, discovers their boundaries, establishes governing norms, and eventually integrates them into daily life.

AI will follow a similar arc, though with far greater responsibility resting on our shoulders.

Anxiety regarding AI is natural and necessary. Concern drives caution, and caution yields robust policy and security frameworks. However, if anxiety degrades into anti-technology panic, humanity will forgo extraordinary benefits. Conversely, if blind techno-optimism ignores real risks, catastrophe becomes possible.

The most pragmatic stance toward AI is neither panic nor blind acceptance-it is proactive adaptation and responsible deployment.

Technological progress will move forward-halting it is unfeasible. The defining factor is how intelligently society adapts to guide that progress.

During the Industrial Revolution, people feared machines. At the advent of computing, workers feared total joblessness. With the internet, traditional commerce faced existential uncertainty. In every instance, society evolved.

With AI, the central narrative will not be machines replacing human relevances, but humanity redefining its place in an AI-augmented world.

The future of technology does not belong solely to machines. Ultimately, it remains firmly in human hands.

The writer is former managing director of BTCL