Digital Distortions

Digital distortions are tech-mediated traps that have become much easier to fall into since the 2000s (and especially after 2020): algorithmic feeds, virality metrics, and AI-generated content can amplify classic biases and make them feel like “new” distortions. Each item below links to a detailed page on this site.

Treating rankings, feeds, or AI output as proof something is true. Why it happens in the digital era, examples, and how to verify claims.

Confusing likes, shares, and views with accuracy or importance. How social metrics distort belief and how to check evidence.

Mistaking emotional intensity for evidence. How feeds amplify outrage and how to slow down and separate facts from reactions.

A stream of bad news becomes a bleak forecast. Why doomscrolling skews perception and how to rebalance your information diet.

Inferring intent and character from posts stripped of tone and context. Examples, risks, and how to seek fuller context.

Treating cropped screenshots and clips as sufficient proof. Why it misleads and how to check provenance and original sources.

When measurable numbers become your definition of value. How metrics skew goals and how to reconnect numbers to purpose.

Feeling you truly know a public figure from curated fragments. Why familiarity turns into certainty and how to reduce mind-reading.

Treating fluent AI output as vetted expertise. Why clarity can be misleading and how to verify high-stakes claims.

Over-trusting automated summaries and recommendations and skipping checks. How to calibrate verification to the stakes.

An AI-generated mistake becomes the anchor even after correction. Why first claims stick and how to reset from verified facts.

Sliding from 'some media is fake' to 'nothing can be trusted.' How blanket doubt blocks truth and how to verify responsibly.