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AI vs Sewing Machines: Lessons From History

The resistance to new technologies is not unique to the 21st century. It has existed since humans first began inventing tools to enhance production and efficiency. 

From the printing press to the telephone, transformative technologies have consistently faced scepticism, fear, and opposition. This resistance rarely came from the technology itself, but from those who felt threatened by the shift it introduced. 

When the printing press emerged in the 15th century, opposition largely came from scribes and established authorities. Scribes feared job displacement, while institutions worried about losing control over information. Printed books reduced the cost of knowledge, weakened traditional gatekeepers, and allowed ideas to spread at unprecedented speed. What was perceived as a dangerous disruption was, in reality, the foundation for mass literacy, education, and intellectual progress. 

The telephone faced a different but equally revealing form of resistance in the late 19th and early 20th centuries. The concerns were social and psychological rather than economic alone (Rymarczuk, 2016). Privacy was a major fear. Early telephone systems relied on shared party lines, where multiple households used the same circuit. It was not uncommon for neighbours to overhear conversations. Operators could also manually connect calls and, in many cases, listen in. This lack of privacy made people uneasy. The telephone was often portrayed as intrusive, unsafe, or socially destabilising. Many questioned why anyone would need such a device when face-to-face communication already existed.

Despite these concerns, the telephone proved its value over time. It transformed personal relationships, business operations, and global communication. The modern internet, real-time messaging, and global connectivity all trace their roots back to this once-contested invention. What was initially viewed as unnecessary or dangerous became essential infrastructure.

There is a clear parallel with artificial intelligence today. Just as AI requires large datasets, complex systems, and massive data centres, early transformative technologies were also large, expensive, and difficult to scale. Printing presses were costly machines. Telephone networks required extensive physical infrastructure. These barriers limited early adoption and delayed mass acceptance. Over time, as costs decreased and usability improved, these technologies reached broader audiences and reshaped society.

History shows a repeating pattern. New technologies emerge, resistance follows, early limitations slow adoption, and eventual integration transforms daily life. AI sits squarely in this cycle. The fear surrounding it is not evidence of failure, but a familiar stage in the evolution of powerful tools.

In 1830, French tailor Barthélemy Thimonnier patented a sewing machine capable of stitching uniforms far faster than hand-sewing ever could. He opened what may have been the world’s first machine-based garment workshop in Paris, with around eighty machines producing clothing for the French army. Tailors saw this innovation and reacted not with curiosity, but with hostility. In January 1831, a mob of roughly two hundred Parisian tailors stormed the factory, destroyed dozens of machines, and burned the workshop, motivated by the belief that mechanised sewing threatened their livelihoods. Thimonnier fled for his life and, despite further efforts to refine his design, never recouped the financial rewards of his invention and died in poverty. His machines were so thoroughly rejected that the initial commercialisation of mechanised sewing in France stalled for years. This moment has been called the Tailor’s Riot and stands as a 19th-century version of a TikTok “shame” backlash against disruptive tech, where anger and fear translate into destructive action rather than adaptation.

This reaction aligns closely with what is now referred to as the Luddite fallacy. The original Luddites were skilled textile workers in early industrial England who destroyed machinery they believed would replace them. Contrary to modern caricatures, they were not anti-technology. They were protesting the deployment of technology without safeguards, fair wages, or alternative employment pathways. The fallacy lies in the assumption that new technology permanently destroys jobs. History shows that while specific roles disappear, new ones emerge, productivity increases, and overall economic capacity grows. The real problem is not technological progress but how societies manage transitions.

Artificial intelligence is following this same trajectory (Elbayadi, 2025). AI systems now perform tasks that once required years of training, from writing and analysis to design and customer support. The fear surrounding AI is not irrational. It reflects concerns about speed, scale, and power concentration. AI adoption is happening faster than previous technological shifts, and the benefits are often captured by a small number of organisations while displacement risks are borne by workers.

History has shown us a consistent pattern. Innovation arrives. Resistance follows. Early systems are imperfect, expensive, and unsettling. Over time, society adapts, workflows change, and new norms emerge. The question is never whether technology should exist, but whether institutions, policies, and cultures evolve quickly enough to ensure people benefit alongside productivity gains.

The sewing machine did not destroy tailoring. The printing press did not destroy knowledge. The telephone did not destroy human connection. Artificial intelligence will not destroy work. But like every major technological shift before it, it will redefine who benefits first and who must adapt fastest. However, this does not mean corporations should blindly adopt an AI-first strategy just for capital gain. People first, tools second. Tools are powerful, but people are the ones who give them purpose and direction

In the final part of this blog series, we will explore When People Mattered: Lessons from Socialist Tech Adoption. We will examine how technology has been deployed in socialist versus capitalist contexts, and how different systems either prioritise human well-being or leave people behind. This discussion will reveal not just the risks of ignoring the workforce but the opportunities to design technology in ways that serve society as a whole.

References:

Rymarczuk, R. (2016). Same old story: On non‑use and resistance to the telephone and social media. Technology in Society, 45, 40–47. https://doi.org/10.1016/j.techsoc.2016.02.003

Elbayadi (2025) discusses how resistance to the printing press in the 15th century mirrors modern fears about AI adoption.

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