Most claims stricken in AirPods Max condensation lawsuit


An attempted class action lawsuit alleging that sweat condensation is killing AirPods Max prematurely has seen most of its claims thrown out by a judge.

The AirPods Max have been the subject of complaints about condensation buildup, even if that hasn’t really translated into significant repairs. That hasn’t stopped one lawsuit from taking Apple on, though a judge has seemingly taken the bite out of the legal challenge.

Stemming from a 2025 lawsuit, the filing posted by Law360 from the U.S. District Court for the Eastern District of New York has Judge Orelia E. Merchant throw out most of the claims. All over whether AirPods Max has a condensation problem.

The 24-page filing recounts the lawsuit, which claims plaintiff Arthur Apicella noticed condensation in his AirPods Max after watching a movie. Indeed, he claims the AirPods Max “generated condensation” after about 15 minutes of use.

Similarly, Dustin Amundson bought AirPods Max and saw the condensation every time he used them.

The pair said that the condensation couldn’t allow them to enjoy “exhilarating high-fidelity audio,” with alleged switches in connection between devices, pauses, and reduced battery life.

Most claims denied

In the filing, Judge Merchant dismissed all of the claims brought by the New York-based Apicella with prejudice. Under New York’s implied warranty of merchantability, there needs to be a “minimal level of quality,” not perfection.

That means the defendant’s admission of being able to watch a movie with them worked against the lawsuit. Apple’s dismissal request for Apicella’s claims was granted with prejudice.

Though Apicella was dropped, the Washington state-based Amundson still had two claims available, including Washington law and the federal-level Magnuson-Moss Warranty Act.

Ultimately, Apple’s motion to dismiss the Amundson set of claims was denied in part. Some Washington common law fraud claims were dismissed with prejudice.

With the lawsuit set to continue, Apple has to file its opposition to any amended complaints by September 4, 2026.

A very small water problem

While the lawsuits allege that there’s a condensation problem, it’s not a device-specific problem. Indeed, back in 2023 when the complaints were prevalent, the issue was inherent to over-year headphones in general.

But there’s a difference between the reports and complaints existing and it being prevalent. Even in our own long-term review, we acknowledged it was a possibility, but after two years, didn’t experience it ourselves.

As for the 2023 expert analysis, there was no evidence of a widespread defect or problem that was seen by repair stores. Apple has no repair programs in effect, and a spot-check of Genius Bars on Tuesday morning don’t suggest that there is a high service rate on the devices.



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YouTube has an AI slop problem, and its crackdown is catching legitimate creators in the crossfire. Faceless channels, where no human host ever appears on screen, have existed for years and are not inherently AI-generated.

Many are run by solo creators who simply prefer to stay anonymous. The problem is that AI tools made it easy to flood the platform with low-effort faceless content at scale, and YouTube’s algorithm is now penalizing the format as a whole.

How bad is the AI slop problem on YouTube?

A Kapwing study found that roughly 21% of the first 500 videos recommended to a new YouTube account were classified as AI slop, while 33% fell into a broader brainrot category. The problem extends to children, too, as more than 40% of YouTube Shorts recommended to kids in a 15-minute session contained low-quality AI content.

YouTube’s response has been to tweak its algorithm to favor videos with real human faces on camera, which is hitting faceless creators even when their content is entirely human-made.

How is YouTube tackling its AI slop problem?

YouTube is now testing a new pop-up on mobile that asks viewers to rate whether a video feels like AI slop, on a scale from “not at all” to “extremely.” The idea sounds reasonable, but crowdsourcing AI detection has real problems. People are bad at spotting AI content, and they are getting worse at it as AI capabilities continue to improve.

There are also legitimate concerns that YouTube could use this viewer feedback as training data for its own AI models, potentially making future AI-generated content even harder to spot.

🚨 Did you just see what YouTube did?

YouTube isn’t banning AI slop.. They’re making you label it so they can train their next model to not look like slop.

Read that again…

You flag the bad AI content. YouTube collects it. Google feeds it into Veo 4… Then next year their… https://t.co/8UC2J3mjjv pic.twitter.com/mIrTChqC1b

— Tuki (@TukiFromKL) March 17, 2026

Meanwhile, faceless creators are scrambling to adapt. According to The Hollywood Reporter, some are hiring cheap on-camera hosts through platforms like Fiverr and Upwork. Others are doubling down on niche educational content, which has held up better than broad content farms.

The AI text-to-video space is still valued at enormous sums, with Higgsfield AI alone sitting at $1 billion, but on YouTube, the math for faceless creators is getting harder to work out every month.



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