True resistance to harmful corporate AI depends upon the collective wisdom and experience of multiple generations—not only the young—because strategic, enduring change requires intergenerational insight, institutional knowledge, and collaboration.
Recent coverage spotlights younger Americans rebelling against generative AI, with media often depicting youth as the primary force challenging Big Tech, while older generations are absent. However, the main issue isn’t AI itself, but how corporations deploy it to extract value at the expense of human augmentation. In various sectors, AI replaces experienced workers, automates judgment, and centralizes power and wealth. Effective resistance requires not only youthful energy but also strategic wisdom and institutional knowledge gained from decades of navigating technological and corporate change.
What the Data Actually Shows
The Pew Research Center data reveal that older adults are more likely than youths to say they are more concerned than excited about AI in daily life. In the United States, the gap between young and old is “really small,” with almost half of young adults concerned about AI. This framing is Silicon Valley ageism in reverse. Instead of assuming that only young people can build AI, it is assumed that only young people can effectively challenge its corporate misuse. Both positions fundamentally misunderstand how effective resistance to value extraction and worker displacement works.
The Pattern Recognition Advantage
Decades of observing technological shifts—from mainframes to large language models—taught me this: resisting corporate technology abuse takes more than passion. It requires pattern recognition, strategic thinking, and an understanding of how corporations use technology for extraction, not augmentation.
Consider what experienced professionals bring.
Historical Context: Those who lived through past tech bubbles, like the dot-com and blockchain eras, recognize how hyped technologies get oversold, mature, and integrate. We’ve seen this before and know which plot points matter.
Institutional Knowledge: Effective resistance requires understanding regulatory systems, legislative processes, and how corporate behavior changes. Smashing iPhones makes dramatic photos but doesn’t shift policy.
Risk Calibration: Experience distinguishes existential threats from manageable problems, battles worth fighting from distractions that consume energy without results.
Strategic Patience: Effective technology resistance combines urgency with strategic planning. Sustainable change requires building coalitions, developing alternative frameworks, and creating accountability mechanisms—work that takes years, not rallies.
The Missing Collaboration Story
The “youth rebellion” narrative hides a key element: intergenerational collaboration. This combines youthful energy and strategic wisdom. Pew data suggests this is underway, even if the media disregard it. When older and younger Americans share AI concerns and form coalitions, or when advocacy bridges recent graduates and veteran policy experts, effective resistance results.
The Real Frontlines
The prevailing narrative portrays young people as being “on the frontlines” due to their firsthand experiences with tools like ChatGPT in education or social contexts. However, the true frontlines of AI impact are found in critical sectors where deployment decisions carry significant consequences. In healthcare, AI diagnostic tools influence patient outcomes, especially for older adults and people with disabilities. In employment, AI-driven hiring systems can systematically disadvantage experienced workers. In finance, AI shapes access to credit and housing. In government, AI informs decisions on resource allocation. In the legal system, algorithms affect bail and sentencing practices. These domains represent the areas where AI’s effects are most profound and deserve focused resistance.
‘We should build coalitions across age groups to create sustainable change that influences policy and corporate practices.’
The core challenge is not AI as a technology but its corporate use for value extraction over augmentation—replacing workers, automating judgment, and centralizing benefits while distributing costs and harms. When Amazon’s AI hiring tool systematically rejects experienced candidates, when healthcare algorithms deny necessary treatment to older patients, when performance monitoring systems squeeze productivity from workers without improving conditions—these aren’t AI problems. They’re corporate deployment problems. This is why effective resistance requires more than smashing phones or opting out of apps. These frontlines demand technical expertise to audit algorithms, legal knowledge to craft regulation, policy experience to navigate legislation, institutional relationships ensuring accountability, and strategic thinking to identify leverage points that challenge corporate extraction models.
Beyond the Rebellion Narrative
Groups organizing against AI’s harms deserve support. These efforts matter.
But framing this primarily as a younger thing does everyone a disservice: Framing resistance as exclusive to youth marginalizes equally concerned older adults and misrepresents shared generational concerns. It prioritizes attention-grabbing actions over the sustained institutional work essential for effective governance and reinforces ageist technology biases. This framing misses the collaborative power of combining youthful innovation with experienced wisdom for stronger movements.
The Path Forward
Effective AI resistance needs a “wisdom worker” model—using technology to amplify judgment and experience, not replace them. Movements should value intergenerational collaboration, prioritize strategic thinking over reaction, combine urgency with discipline, and include diverse perspectives, recognizing that AI harms affect people differently.
Focus on systemic change, not individual opt-outs. Personal choices don’t address how corporations use AI for extraction: replacing workers, automating judgment, and concentrating wealth and harm.
Conclusion: Resistance Requires Wisdom
The youth resistance narrative equates age with tech expertise, overlooking the role of experience and strategic know-how. While youth activism matters, effective resistance relies upon intergenerational collaboration that pairs energy with wisdom and urgency with patience. The Pew data show broad generational concern about AI. Rather than isolating youth activism, we should build coalitions across age groups to create sustainable change that influences policy and corporate practices.
The AI resistance needs more than rebellion. It needs wisdom—understanding corporate power, recognizing extraction, and developing models where AI augments people rather than replacing them for profit. Wisdom comes from combining diverse knowledge, not from assuming that one generation has all the answers.
James Lomastro, PhD, has more than 40 years’ experience as a senior administrator in healthcare, human services, behavioral health, and home- and community-based services. For 20 years, he was a surveyor at the Commission on Accreditation of Rehabilitation Facilities throughout the United States and Canada. Lomastro chairs the Veterans Services Work Group at Dignity Alliance Massachusetts. The author’s career began with the DEC PDP-1145 interactive computer, then evolved to teaching distributed data processing, to installing information systems, and later to integrating information technologies into operations and strategic directions.
Photo credit: Shutterstock/PeopleImages
