What Good Are Wearable Computers if the Data Is Wrong?

The higher your VO2max, exercise experts say, the better your cardiovascular fitness
The higher your VO2max, exercise experts say, the better your cardiovascular fitness
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What Good Are Wearable Computers if the Data Is Wrong?

The higher your VO2max, exercise experts say, the better your cardiovascular fitness
The higher your VO2max, exercise experts say, the better your cardiovascular fitness

Smartwatches from tech companies like Apple and Garmin make it easy to see a number that could reflect how old you are more accurately than your age: the VO2max, the maximum amount of oxygen that your body can use during intense exercise.

The higher your VO2max, exercise experts say, the better your cardiovascular fitness. In the past, only serious athletes sought a traditional VO2max test, which involved wearing cumbersome sensors while exercising inside a lab, but now anyone can get an estimate by wearing a smartwatch and moving around.

Is it good to have access to this kind of information? And how accurate could a wearable be? In the last five months, when I fell down a VO2max rabbit hole, I learned some uncomfortable truths about my health and the limits of smartwatches.

First, let me tell you about my fitness journey. In November, while I was out celebrating my birthday, my Apple Watch delivered the most unwanted gift: a notification of a high heart rate. In search of a quick solution, I bought a membership at a high-intensity interval gym. Five months and many kettlebell swings and jump squats later, I felt progress. I burned fat, gained muscle and felt more energetic. The Apple Watch gave me a VO2max estimate of 40, just shy of average, and a Garmin watch that I also wore rated me at 45.

All that was left to do was to take a real VO2max test, so I found one. I got my lab results: 25, a rating of poor, far below the flattering results from the Apple Watch and Garmin. Devastating.

Dr. Ethan Weiss, a cardiologist in San Francisco who has studied wearable technology for many years, said my experiment underscored the pros and cons of using smartwatch data to explore health.

“On the one hand, you can give it credit for kicking you in the butt to tell you to go work out,” he said. “But on the other hand, now you’re sort of burned with this real test and like, ‘What do I do with this number?’”

Fortunately, after studying all the data, learning how the wearable algorithms work and talking with health experts, I arrived at a positive conclusion: Even if the smartwatch numbers were wrong, they were correct in broad strokes, and I was probably better off wearing one than not.

A Deeper Look at the Data

Last month, my gym in Oakland, Calif., called Sweat, announced that it had teamed up with PNOĒ, a metabolic health lab, to offer clinical-grade VO2max testing, so I signed up with gusto.

The purpose of a clinical VO2max test is to measure your maximum oxygen intake at the point that you reach exhaustion. This metric — the ability for a person to breathe in oxygen and produce carbon dioxide during exercise — is a strong indicator of cardiovascular fitness.

The test was very different from the way the wearables estimated my VO2max. The Apple Watch and Garmin study your heart rate and movement while you’re walking or running for at least 10 minutes and tally a score.

Spokespeople for Apple and Garmin referred to documents describing their methods. To inform their algorithms on how to make these estimates, Apple and Garmin ran studies involving people who were doing a real VO2max test as well as other exercises and studied their heart rates and various metrics.

The key word is “estimate.” The watches aren’t actually measuring your oxygen intake and, therefore, aren’t actually measuring your VO2max.

“It’s at best an imputed VO2max,” Dr. Weiss said. “Not only do you not have an oxygen mask, you’re not actually exerting yourself to exhaustion.”

A simple reason that my wearable estimates were so far off from my real VO2max result is that the way my body works doesn’t match the heart-rate and oxygen-intake patterns of participants in the Apple and Garmin studies. Such is the danger of putting too much trust in algorithms.

That left me with no choice but to embrace the hard truth: My VO2max result in the lab test was very low.

Ignore the Numbers; Follow the Trends

In the end, all the health experts I interviewed agreed that even though the wearable data — much of it flawed — had given me anxiety, I had reached a net positive. The Apple Watch nudged me to pay closer attention to my health, and as a result I’m healthier now.

The broad trends shown by the wearables were accurate: Months ago, after the pandemic had taken a toll on my body and mind, I was in my worst shape in years, and the watch numbers were low. Now, even though the watch numbers are too high, I do look and feel better, and that’s all that really matters.

Whether you’re using devices to measure your progress in losing weight, getting more sleep or taking more footsteps, what you need to know is whether the numbers are going up or down. But don’t take them too seriously, because all sorts of factors could be throwing them off — a loose wrist strap, a faulty sensor or, as in my case, imperfect algorithms.

“It’s the trend that’s important, not the absolute number, because this stuff’s not accurate,” Dr. Adams said.

The New York Times



China's Tencent Says AI Agents Showed Unintended Browsing Behavior

FILE PHOTO: The Tencent logo at the company's headquarters during a government‑organised media trip in Shenzhen, Guangdong province, China, April 17, 2026.  REUTERS/Go Nakamura/File Photo
FILE PHOTO: The Tencent logo at the company's headquarters during a government‑organised media trip in Shenzhen, Guangdong province, China, April 17, 2026. REUTERS/Go Nakamura/File Photo
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China's Tencent Says AI Agents Showed Unintended Browsing Behavior

FILE PHOTO: The Tencent logo at the company's headquarters during a government‑organised media trip in Shenzhen, Guangdong province, China, April 17, 2026.  REUTERS/Go Nakamura/File Photo
FILE PHOTO: The Tencent logo at the company's headquarters during a government‑organised media trip in Shenzhen, Guangdong province, China, April 17, 2026. REUTERS/Go Nakamura/File Photo

Tencent said on Friday that AI agents used to evaluate third-party models displayed web-browsing behavior not intended by the tech giant, in what appears to be the first known incident of rogue agent actions acknowledged by a major Chinese company.

The statement followed a report by AI-safety research group Swarmchasers on Wednesday, which said "rogue" agents running on infrastructure it linked to Tencent Cloud made repeated attempts between September 28 and October 8 to retrieve information from Alibaba's Amap, China's equivalent to Google Maps.

Tencent Hunyuan, the company's artificial ⁠intelligence unit, said in ⁠a post on X that the activity did not originate from its Hunyuan models. Its review found no evidence of deliberate targeting or coordination, Reuters quoted it as saying.

The Swarmchasers researchers said the agents sought information such as the commonly used entrances at Chinese parks, museums and zoos.

The actions are not as egregious as those disclosed by US AI companies which include the hack of ⁠open-source platform Hugging Face by an OpenAI agent and the lodging of a fake homicide tip by an Anthropic agent.

But the disclosure underscores research that shows Chinese AI agents can also misrepresent their identity, conceal failures and try to circumvent testing controls.

Tencent said it took the findings very seriously and was strengthening network access controls and agent monitoring.

Hunyuan is one of China's leading AI model developers, competing with in-house teams at rivals such as Alibaba and ByteDance. ByteDance this week announced the creation of a new unit focused on AI model and agent safety.

Swarmchasers said it used the ⁠word "rogue" to ⁠describe agents taking actions outside their intended scope or completing a task in unintended ways.

After routine automated requests were blocked, the agents tried other methods, including public web tools that could open pages and run code, routing requests through other websites and using Amap keys and security codes found in publicly available software code.

Swarmchasers said it found no evidence that the agents breached Amap's main anti-bot safeguards. Most of the 2,818 attempts it recorded either failed or returned anti-bot pages, login screens or blank results.

Some requests returned information through cached pages and intermediary services, including data on visitor arrivals at Chengdu Zoo, Swarmchasers said. The researchers said they could not determine whether an agent read the result or completed its task.


Anthropic Co-founder Renews Call for Robust Regulation of Frontier AI

AI Research Company Anthropic's Co-Founder and Head of Public Benefit Jack Clark speaks during the Artificial Intelligence and the Global Economy From Risk to Opportunity event of the 2026 Annual Meetings of the IMF and the World Bank Group in Bangkok, Thailand, 16 October 2026. EPA/RUNGROJ YONGRIT
AI Research Company Anthropic's Co-Founder and Head of Public Benefit Jack Clark speaks during the Artificial Intelligence and the Global Economy From Risk to Opportunity event of the 2026 Annual Meetings of the IMF and the World Bank Group in Bangkok, Thailand, 16 October 2026. EPA/RUNGROJ YONGRIT
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Anthropic Co-founder Renews Call for Robust Regulation of Frontier AI

AI Research Company Anthropic's Co-Founder and Head of Public Benefit Jack Clark speaks during the Artificial Intelligence and the Global Economy From Risk to Opportunity event of the 2026 Annual Meetings of the IMF and the World Bank Group in Bangkok, Thailand, 16 October 2026. EPA/RUNGROJ YONGRIT
AI Research Company Anthropic's Co-Founder and Head of Public Benefit Jack Clark speaks during the Artificial Intelligence and the Global Economy From Risk to Opportunity event of the 2026 Annual Meetings of the IMF and the World Bank Group in Bangkok, Thailand, 16 October 2026. EPA/RUNGROJ YONGRIT

Anthropic co-founder Jack Clark renewed calls on Friday for regulating artificial intelligence, saying that allowing companies to continue to operate without robust legislation was like letting a race car loose on the streets at night without brakes.

"It's remarkable to me that the toys I buy for my children are regulated more than the literal super intelligence I work on at my day job," he told an event at the IMF-World Bank's Annual Meetings in Bangkok.

Clark said that US President Donald Trump, whose administration has called for the industry to police itself, was against the idea of regulation but that China was not, said AFP.

"I think it's Formula One at night without maybe brakes in the cars," he said.

He said the lack of clarity around the will for regulation meant "the Formula One car is roaring round and nobody seems to want to put up a guardrail?"

At an industry summit in Dublin on Wednesday, calls to prioritize safety in the development of powerful AI technology dominated the conversation.

Concerns about AI guardrails have soared after models developed by OpenAI and Anthropic were involved in security incidents during testing, piling on pressure to regulate the technology.

A recent Anthropic report suggested small AI models may be only months away from behaving like computer worms, copying themselves from one internet-connected device to the next.

Anthropic has been among those companies calling for governments to step in, even suggesting international coordination to slow down the whole industry -- including Chinese rivals.

That initiative has so far failed to materialize, with companies involved in a hyper-competitive race to attract as much investment as possible.


Meta Releases Open-Weight Muse Spark Model for Coding, Agentic Tasks

The logo of Meta is seen at the entrance of the company's temporary stand ahead of the World Economic Forum (WEF) in Davos, Switzerland January 18, 2025. (Reuters)
The logo of Meta is seen at the entrance of the company's temporary stand ahead of the World Economic Forum (WEF) in Davos, Switzerland January 18, 2025. (Reuters)
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Meta Releases Open-Weight Muse Spark Model for Coding, Agentic Tasks

The logo of Meta is seen at the entrance of the company's temporary stand ahead of the World Economic Forum (WEF) in Davos, Switzerland January 18, 2025. (Reuters)
The logo of Meta is seen at the entrance of the company's temporary stand ahead of the World Economic Forum (WEF) in Davos, Switzerland January 18, 2025. (Reuters)

Meta ‌Platforms on Thursday released an open-weight version of its Muse Spark artificial intelligence model for coding and AI agents, expanding developers' ability to download and adapt the technology.

Open-weight models make trained parameters available for developers to modify, unlike proprietary models ‌that remain under ‌their creators' control. ‌They ⁠can offer businesses ⁠a lower-cost alternative to closed systems.

Meta said Muse Spark has 816 billion total parameters, with 42 billion active at a time, and ⁠can handle a context window ‌of up ‌to 1 million tokens.

The ‌model can run locally on ‌two Apple M5 Ultra Mac Studio computers and is also available through some API providers.

CEO ‌Mark Zuckerberg has argued that advanced AI should ⁠not be ⁠concentrated among a small number of companies.

While open-weight models can give companies greater control over their data, they can require significant computing resources and technical expertise to operate at scale.

In August, Meta released Muse Glimmer, a smaller open-weight model.