Feature 15 April 2026

Age against the machine

From technophobic boomers to ‘brainrot’ Gen Zs, the dominant conversations on AI pit generations against each other, masking how extractive technologies entrench control and deepen inequality – but we can only shift the narrative by rejecting inevitability and reclaiming collective power

Cartoon scene of yellow alien helmets with tentacles scattered on a snowy landscape, surrounded by small, armoured humanoid figures walking and interacting. Some helmets appear to have fallen, spilling sand or soil.

Tania Duarte, FRSA

Founder of We and AI

reading time: Eight minutes

Communities Digital Diversity and inclusion Education Technology

Summary

Debates around artificial intelligence often frame generational differences in misleading ways, portraying older people as technophobic and younger people as overly dependent on technology argues Tania Duarte, FRSA. Drawing on research from her organisation, We and AI, she suggests these narratives obscure the real issue.

^{Illustrations by Renaud Vigourt}^.

As the pandemic took hold at the beginning of 2020, I had just left a role encouraging business and digital leaders to embrace disruptive technologies such as artificial intelligence (AI). I had started worrying about the impact of rapid adoption of new technologies on future generations; in particular, how algorithmic bias was starting to roll back some of the gains made in gender and racial equity. I set up the non-profit organisation We and AI to address this trend by enabling greater awareness of the potential impacts of AI, aiming to support a greater diversity of people to get meaningfully involved in decision-making.

Six years later, generative AI awareness has skyrocketed, but my concerns over algorithmically enhanced discrimination have simply been subsumed into a deluge of wider AI harms. Rather than a greater public voice and power exercised in how AI is deployed, tech companies and their leaders have increased their own power and stranglehold over democracy itself.

Polarising algorithms – designed to fuel and amplify divides – pit populations, groups and cultures against each other, often making it seem as though the only shared objective is not to be ‘left behind’ as we hurtle towards a seemingly inevitable AI-powered future.

At We and AI, we have spent time in conversation with teenagers and older adults to understand their perspectives on the impact of AI and the information environment to which they are exposed. What we have learned through these discussions contradicts many of the dominant generational narratives that have emerged in the current discourse on generational gaps and AI.

Enjoying this article? Share it on WhatsApp

Generational narratives

Narrative 1: Gen X and Boomers are slowing us down

“Gen X and remaining Baby Boomers in the workplace need to take the lead from younger generations to be productive members of the workforce. After all, experience of many waves of technological implementation is less important than the ability to prompt.”

We found that what is often characterised as a lack of aptitude or skills are actually missed opportunities to explore what lies behind reticence, what is lost when processes are automated and what lessons can be learned from previous transformations.

Narrative 2: We need to protect The Silent Generation by upskilling them

“The answer to older people being ‘left behind’ is to protect them from being such clueless technophobes and vulnerable incompetents.”

We worked with researcher Dr Eleonora Lima from King’s College London to instead explore how we could unlock the benefit of older generations’ experience of new technologies over the years. In many cases, this generation is not as clueless as depicted. They don’t need a lot of know-ledge and experience to be able to question technology, or reflect about it on a societal level. Furthermore, if the goal is, indeed, to ‘protect’ them, then time may be better spent focusing on stopping platforms from gaining money by exploiting people in the first place.

Narrative 3: Gen Z and Alpha have ‘brainrot’

“Young people are cheaters, trying to outwit their teachers, with diminished cognitive skills caused by generative AI slop on social media.”

We saw a much more nuanced picture in a community research project we conducted last year, in which 15–18-year-olds interviewed each other about their relationships with AI chatbots. These young people were very aware of the wider impacts of AI, and expressed fears about job and career replacement, increasing devolvement of control to AI, the hope for scientific breakthroughs, concerns over the impact of chatbot interactions on the ability to develop social skills, fears over privacy, and general loss of agency.

Narrative 4: Millennials (literally) love AI

“Millennials love AI, whether they are building it, evangelising for it or literally falling in love with it.”

As one component of community research, we identified 11 groups of harms evidenced by individual users of AI chatbots. These are in addition to any societal, rights-based or environmental harms caused by the widespread use of generative AI. They include hazards operating at a personal level such as privacy risks, exploitation, language standardisation, psychological harm, over dependency and impacts on real life relationships.

What became clear is that all generations are involved in parasocial and unhealthy relationships with AI, and the real issue is the unnecessary anthropomorphising of products and language which encourages these harms.

A banner with the text "Become a Fellow Today" and a description about events, webinars, research, RSA Journal delivery, alongside a colorful grid of diverse professional headshots.

Changing the frame

These narratives are not only reductive and divisive, but they are imbued with the idea that technological innovation is the principal motor of economic or political change – this makes finding solutions to living better seem impossible. They are the stories of how we must seek to adapt to AI, and overcome the obstacles caused by our lack of readiness and individual capacity. This removes our agency to question what it really is we are trying to keep up with, and who is really benefiting.

The truth is that we are the test subjects for tech companies as they try to find use cases for generative AI; scrambling to lock us in, consolidate control, and find a business model for energy inefficient technologies that are haemorrhaging money, not making it.

Even when we talk about the pitfalls and anxieties caused by many different technological hazards across generations, we are still being distracted. The sheer number of issues means that we are all tied up fighting one battle after another, addressing individual AI harms that are really just symptoms of underlying societal problems. While we try to regulate, apply legislation and draw on an already strained civil society to pick up the pieces, navigate or campaign, the frontline continually expands and seems impossible to cover.

It would be a challenge even if we weren’t set against each other, through narratives of generational and other identity gaps, blaming each other rather than looking at the biggest gap: the gap between those with extreme wealth and power and those without. This gap has increased so rapidly partly due to the increasing reliance on technologies. Power inequities and imbalances that have always been there are growing, despite the techno-optimist refrain that, in some yet undetermined way, AI will solve poverty and herald universal basic income.

As of right now, that is not the case – AI is increasing poverty and exploitation, and those who have always been at the bottom of the socioeconomic scale are feeling it first.

Taking action

It may seem pointless to advocate for a public good in a system optimised for labour and resource extraction. It might seem easier to go along with the idea that AI will solve all problems eventually (if we allow Silicon Valley unlimited resources, land, data and power). But there are very few actual examples of quantified, evidenced public good. Acquiescence is not an option in the face of such lack of care, so what can we do?

A quirky cartoon creature stands holding a mobile, with long yellow cables connecting its head to a large, black and yellow sphere floating above. The background is a solid beige colour.

Refute narratives of AI inevitability

The first and most powerful step is to remember that, while the system is set up for the few, we are many. No future can be inevitable unless everyone goes along with it.

The fervent response to a framework published by We and AI outlining ways in which groups and individuals are pushing back against extractive technologies has shown there is a public appetite for more regenerative futures.

It would be a challenge even if we weren’t set against each other… blaming each other rather than looking at the biggest gap: the gap between those with extreme wealth and power and those without.

A yellow cartoon character with a round head is tangled in grey cables, struggling to untangle them, on a white background with a peach border.

We mapped out the following initiatives:

Resisting AI: Rejecting the ideologies of extraction, datafication and automation

Refusing AI: A targeted opposition to AI applications

Reclaiming AI: Giving communities control of technology design, development and use

Reimagining AI: Collectively reshaping tech narratives through an environmental, decolonial and ancestral lens

We are building a database of these initiatives to inspire collective action across divides in issue and identity. A place to find strategies and campaigns to design a future which does not just benefit or legitimise the privileged and powerful. Meanwhile, here are two substantive mandates:

Don’t be complicit

Denying the potential and need to challenge AI’s role as a system of increasing power asymmetries is complicity. An individualistic race to be the one who keeps their job by being the best AI acolyte will have few winners. It just contributes to work insecurity for everyone. In terms of generational divides, consider concepts related to the wisdom of elders, the impact of intersectionality, and the need to nurture younger generations rather than accept the damage done to them with untested technologies.

Insist on critical AI literacy

Current programmes of AI literacy are generally missing vital elements – ones that should enable the questioning not just of the output or choice of tools, but to ask if, how, when and under what circumstances AI is even the answer, and who for. We are documenting the emergence of ‘critical AI literacy’ in response, and the need for a ‘human’ as well as technical and functional element in education. Any course which starts at learning tools, rather than exploring the interdependent relationship between society and AI infrastructure, risks being simply a consumer onboarding programme.

The direction (and use) of AI is not inevitable. We don’t have to buy into narratives relating to the need to get everyone on board the AI hype train and, if we do, we risk laying down tracks over the space for considering better ways to live. Ways that free us from dependency on tech companies and their political agents, and allow us to flourish in a way that benefits the many, not the few.

Learn more about We and AI

Get involved

Jayanshi Rawat at We and AI contributed to this piece.

Tania Duarte, FRSA is the Founder of We and AI, a volunteer non-profit organisation focusing on critical AI literacy, which also runs the global Better Images of AI library. Tania works on the decoding of narratives related to AI hype, AI inevitability and the use of AI metaphors.

Knowledge grows when shared.

If you found this interesting, pass this article on to your friends and family.

Share on LinkedIn | Share on Whatsapp

← Previous article

Next article →