The ’80s throwback and the invisible cost of AI-generated nostalgia

AI is giving us the power to manufacture a past. What we do with that power will say far more about our future.

3 min readSep 12, 2026 07:13 AM IST First published on: Sep 12, 2026 at 07:00 AM IST

Social media is filled with images of bouffant hair, aviator glasses, grainy photographs, vintage cars and the warm imperfections of analogue film. Except much of this past, set in the 1980s, never happened. It was being generated in the present.

Politicians joined in, too, and what began as an amusing exercise in nostalgia soon acquired a distinctly political edge. Congress Kerala posted an invented Gujarat street scene; BJP Telangana answered with a fabricated bar scene labelled “Lusiana, Italy”, an apparent reference to Sonia Gandhi’s birthplace. The internet trend had completed a remarkably quick journey: From entertainment to self-presentation to political attack.

For much of the modern era, controlling the image required infrastructure. There were photographers, advertising agencies TV crews, campaign budgets. Generative AI radically compresses that machinery.

I study sustainability in fashion, an industry that understands better than most how images manufacture desire. A campaign photograph can make a garment signify rebellion, luxury, or responsibility. The physical object matters, but so does the story wrapped around it. Generative AI puts this logic on steroids. We are moving to an economy in which convincing realities can be manufactured on demand. That is entertaining when everyone understands the game. The difficulty begins when this capacity enters domains where authenticity matters.

Here sustainability offers a useful lens. Sustainability is often reduced to carbon emissions, recycling, or renewable energy. At its core, however, it asks a more fundamental question: What happens when the consequences of what we produce are separated from the act of producing it?

Fashion learnt this painfully. For decades, cheap clothing appeared almost frictionless to consumers because much of its true cost — waste, water, emissions and precarious labour — remained somewhere else in the value chain. The sustainability movement forced businesses to examine what was hidden behind the finished product. We need a similar instinct for AI. The synthetic image that appears instantaneously on our phone is not consequence-free simply because it is intangible. There are questions of energy, data, consent, intellectual property and labour and, increasingly, trust.

For decades, photographs carried a peculiar authority. They could be manipulated, staged or selectively framed, of course, but their basic cultural proposition was that a camera had encountered something in the world. Generative AI breaks that assumption. The consequence is not simply that we may believe things that are false, but that we begin doubting things that are true. The social cost is the gradual erosion of our confidence in visual evidence itself.

The answer is not to reject generative AI, but to develop norms as fast as we are developing capabilities. And we need to acquire a new reflex. For the last generation, digital literacy meant learning not to believe everything we read online. For the next , it will mean learning not to believe all we see.

There is something fitting about the fact that this lesson has arrived dressed in the clothes of the 1980s. Fashion knows that styles return, but never to precisely the world they left behind. AI is giving us the power to manufacture a past. What we do with that power will say far more about our future.

The writer is professor of practice, Sustainability at Masters’ Union, India.