The story of human progress is punctuated by revolutions, not
just in technology, but in how we think, organize, and trust. From the steam
engines of the 1840s to the generative models of the 2020s, each wave has
promised liberation and delivered disruption. Today, as AI surges toward
ubiquity, we must ask: what have we learned from past revolutions, and what
must we safeguard before the bubble bursts.
Four Revolutions That Changed Everything
There are four revolutions that resulted in significant change
where we can learn from the affects to help the AI revolution progress
unhindered.
|
Era
|
Catalyst
|
Impact
|
Risk
|
|
Industrial
Revolution (c. 1760 – 1840s)
|
Steam power,
mechanization
|
Mass
production, urbanization, labour displacement
|
Exploitation,
unrest (e.g. Plug Plot Riots, 1842)
|
|
Digital
Revolution (1950s – 1990s)
|
Mainframes,
UK computing pioneers, PCs
|
Automation,
global communication, software economies
|
Surveillance,
fragmentation, digital exclusion
|
|
Cloud
Revolution (2000s – 2020s)
|
Virtualization,
SaaS, mobile-first
|
Scalable
infrastructure, remote work, data centralization
|
Vendor
lock-in, opaque governance, cyber risk
|
|
AI Revolution
(2020s –)
|
Foundation
models, generative AI
|
Cognitive
automation, new interfaces, synthetic creativity
|
Hallucinations,
bias, job loss, trust collapse
|
During the industrial revolution there was a deep industrial
economic depression. The Plug Plot Riots were a wave of industrial action and
disturbances across Lancashire, Cheshire, and Yorkshire, triggered by severe
wage reductions (often 20-25% in the cotton and coal industries). Many workers
aligned with the Chartist movement advocating for political reform, responded
by "plugging" mill boilers, removing drain plugs to flood engines and
halt production which forced factories to close. The
Plug Plot Riots of 1842 led to some improvements for workers, notably the
prevention of further wage cuts and the eventual passage of the Factory Act
1844, which introduced limited reforms. It introduced a reduction in working
hours for women and children, some safety regulations in factories and a modest
step toward better labour conditions.
The second revolution of computing was not just technical.
It redefined abstraction, logic, and control. From the UK’s early computing
pioneers to the rise of PCs, it laid the groundwork for cloud and AI. Yet it
also introduced new vulnerabilities: fragmented standards, digital inequality,
and the erosion of analogue memory.
Cloud as the Bridge: Infrastructure to Intelligence
Cloud computing connected digital and AI with its abstracted
hardware, centralized data, and the capabilities to scale with ease. But as
Satya Nadella emphasizes in his annual letter and Microsoft’s 2025 report,
innovation without strategic purpose is fragile. Microsoft’s Secure Future
Initiative and Quality Excellence Initiative reflect a shift: AI must be built
on trust, not just talent.
Brad Smith’s AI Diffusion Report warns that AI is spreading
faster than any prior technology but unevenly. The Global South, non-English
languages, and underrepresented communities’ risk being left behind.
Data: The Fuel, the Flaw, the Future
AI’s power is unprecedented and has the power to improve or
destroy depending on the algorithm development but also on the state of data.
Poor quality, biased, or ungoverned data leads to hallucinations,
misinformation, and systemic risk. As the BBC’s article on AI hallucinations
shows, even the most advanced models can confidently fabricate facts,
undermining journalism, science, and public trust. From the simplest things I
have seen AI fabricate data, which is written so well, to the untrained eye it
could be believed. Once the data is triangulated the output can be trusted. However,
the data sources quality, the prompts and data that is behind paywalls will
influence the outcome.
This is not a glitch it is a consequence of probabilistic
systems trained on imperfect inputs. Without rigorous data governance,
provenance tracking, and human oversight, AI becomes a mirror of our worst
assumptions.
When the Bubble Bursts: Coping with the AI Comedown
Every revolution has its reckoning. The Plug Plot Riots of
1842, the dot-com crash, and the decline of post-industrial towns all reveal
the cost of overhyped promises and underprepared systems. When the AI bubble
bursts whether through regulation, disillusionment, or economic correction, organizations
with strong data foundations, ethical frameworks, and human-centred design will
endure.
Those who chased novelty without governance will falter.
Satya Nadella’s mantra is “thinking in decades, executing in
quarters” is more than a business strategy. It’s a survival imperative. The AI
era demands long-term vision grounded in short-term accountability. That means:
- Investing in data quality and lineage as core
infrastructure
- Embedding responsible AI principles into every product and
process
- Preparing workers for augmentation, not just automation
- Designing for resilience, not just scale
Conclusion: From Revolution to Renaissance
The Industrial Revolution reshaped labour. The digital
revolution redefined logic. The cloud revolution scaled infrastructure. AI is
now rewriting cognition. but without trust, transparency, and governance, even
the most powerful tools will falter. As the socio-technical divide deepens and
ecological systems strain, the cost of inaction grows, and we risk accelerating
collapse socially and ecologically.
The disruption from AI is only just beginning. As Business
Insider quoted, “Elon Musk said AI will make desk jobs feel like when
workers used to make calculations by hand before the computer age.” This
echoes the upheaval of 1842, when industrialisation redefined labour.
If we want AI to be a renaissance, not a reckoning, we must
treat data as infrastructure, governance as strategy, and human ethics as
non-negotiable. The future isn’t just what we build; it’s what we’re willing to
steward.
We must draw a line: to protect data, embed meaningful
guardrails, and confront the human cost of displacement. That means planning
not only for the jobs we lose, but for the ones we must invent. It also means
addressing the widening continental divide in AI development and its cascading
impact on the environment and global economy.
References
'It's going to be really bad': Fears over AI bubble bursting
grow in Silicon Valley
https://www.bbc.co.uk/news/articles/cz69qy760weo
Satya Nadella annual letter: Thinking in decades, executing
in quarters
https://www.microsoft.com/investor/reports/ar25/index.htmlhttps://www.linkedin.com/pulse/my-annual-letter-thinking-decades-executing-quarters-satya-nadella-7orpc?utm_source=share&utm_medium=member_android&utm_campaign=share_via
Brad Smith https://aka.ms/AIDiffusionReport
Elon Musk says the AI 'supersonic tsunami' will eliminate
desk jobs 'at a very rapid pace'
https://www.businessinsider.com/elon-musk-ai-supersonic-tsunami-job-displacement-future-joe-rogan-2025-11
Transparency: Written with the help of Copilot.
