Majority of US teens have lost trust in Big Tech

Survey, framing, and what “trust” measures

• Several commenters question the survey’s design: collapsing nuanced answers into “trust most/always” vs “hardly/some of the time” is seen as misleading.
• Others note the sponsor (an advocacy org) has an agenda around tech regulation, so the results may be framed to support lobbying.
• Some argue “trust” is multidimensional: you might trust Amazon to deliver a toaster, but not to handle your data or shape politics.

Can corporations “care”?

• Many reject the survey’s premise that companies might “care about well‑being and safety.”
• They argue companies aren’t sentient; only executives and workers act, usually under profit-driven incentives.
• This leads to skepticism that any large firm would sacrifice profit to protect users, absent strong regulation.

Institutional trust, cynicism, and social cohesion

• One camp sees the erosion of trust in Big Tech and legacy media as healthy: blind faith in powerful institutions enabled past abuses.
• Another camp warns that “trust nothing” leads to chaos, polarization, and susceptibility to grifters and influencers filling the vacuum.
• There’s debate over whether today is uniquely bad or just another historical swing in a long pattern of mistrust and authoritarian drift.

Teens’ behavior vs stated distrust

• Several point out the gap between survey answers and “revealed preference”: most teens still own iPhones and use major social platforms.
• Explanations include network effects (you go where your friends are), social pressure, and lack of real alternatives, not genuine trust.
• Some note it can be coherent to dislike and distrust a platform yet still depend on it for social life, school, or work.

Media, algorithms, and misinformation

• Commenters lament the collapse of well-funded independent journalism and its replacement by ad‑driven social feeds and partisan outlets.
• Algorithmic feeds and headline‑only consumption are called “poison for the mind,” optimizing for outrage, not truth.
• Others counter that legacy media lied about major issues too; the problem is now a fragmented “fantasyland” where any narrative can thrive.

Big Tech’s business models and incentives

• Several stress that many “tech companies” are really ad/attention companies; calling them “tech” obscures their manipulation incentives.
• Profit motive is seen as consistently overriding user safety or democratic health (data exploitation, engagement‑at‑all‑costs, AI trained on everything).
• Historical optimism about firms like Google (and earlier examples like Bell Labs or GE) is contrasted with their later “enshittification.”

Responsibility and paths forward

• Some argue programmers and users share blame by continuing to work for and rely on these firms instead of building or supporting alternatives.
• Others reply that people often lack realistic options: modern life increasingly requires smartphones, big platforms, and digital IDs.
• There’s broad agreement that trust must be earned and maintained, and that without structural economic and regulatory changes, distrust alone won’t fix Big Tech’s harms.