{"id":24796,"date":"2025-06-29T15:20:09","date_gmt":"2025-06-29T15:20:09","guid":{"rendered":"https:\/\/www.europesays.com\/us\/24796\/"},"modified":"2025-06-29T15:20:09","modified_gmt":"2025-06-29T15:20:09","slug":"the-unbearable-obviousness-of-ai-fitness-summaries","status":"publish","type":"post","link":"https:\/\/www.europesays.com\/us\/24796\/","title":{"rendered":"The unbearable obviousness of AI fitness summaries"},"content":{"rendered":"<p class=\"duet--article--dangerously-set-cms-markup duet--article--standard-paragraph _1ymtmqpi _17nnmdy1 _17nnmdy0 _1xwtict1\">After nearly a decade of wearables testing, I\u2019ve amassed a truly terrifying amount of health and fitness data. And while I enjoy poring over my daily data, there\u2019s one part I\u2019ve come to loathe: AI summaries. <\/p>\n<p class=\"duet--article--dangerously-set-cms-markup duet--article--standard-paragraph _1ymtmqpi _17nnmdy1 _17nnmdy0 _1xwtict1\">Over the last two years, a deluge of AI-generated summaries has been sprinkled into every fitness, wellness, and wearable app. Strava introduced <a href=\"https:\/\/www.theverge.com\/2024\/5\/16\/24158290\/strava-ai-dark-mode-night-heat-maps-family-subscription\" rel=\"nofollow noopener\" target=\"_blank\">a feature called Athlete Intelligence<\/a>, pitched as AI taking your raw workout data and relaying it to you in \u201cplain English.\u201d Whoop has <a href=\"https:\/\/www.theverge.com\/2023\/9\/26\/23888984\/whoop-coach-chatgpt-ai-fitness\" rel=\"nofollow noopener\" target=\"_blank\">Whoop Coach<\/a>, an AI chatbot that gives you a \u201cDaily Outlook\u201d report summarizing the weather, your recent activity and recovery metrics, and workout suggestions. Oura added <a href=\"https:\/\/www.theverge.com\/news\/639576\/oura-advisor-ai-chatbot-wearables\" rel=\"nofollow noopener\" target=\"_blank\">Oura Advisor<\/a>, another chatbot that summarizes data and pulls out long-term trends. Even <a href=\"https:\/\/www.theverge.com\/24279552\/eight-sleep-pod-4-ultra-review-tracking\" rel=\"nofollow noopener\" target=\"_blank\">my bed<\/a> greets me with summaries every morning of how its AI helped keep me asleep every night. <\/p>\n<p class=\"duet--article--dangerously-set-cms-markup duet--article--standard-paragraph _1ymtmqpi _17nnmdy1 _17nnmdy0 _1xwtict1\">Each platform\u2019s AI has its nuances, but the typical morning summary goes a bit like this:<\/p>\n<p class=\"duet--article--dangerously-set-cms-markup duet--article--standard-paragraph _1ymtmqpi _17nnmdy1 _17nnmdy0 _1xwtict1\">Good morning! You slept 7 hours last night with a resting heart rate of 60 bpm. That\u2019s in line with your weekly average, but your slightly elevated heart rate suggests you may not be fully recovered. If you feel tired, try going to bed earlier tonight. Health is all about balance! <\/p>\n<p class=\"duet--article--dangerously-set-cms-markup duet--article--standard-paragraph _1ymtmqpi _17nnmdy1 _17nnmdy0 _1xwtict1\">That might seem helpful, but those summaries are usually placed next to a chart with the same data. It\u2019s worse for workouts. Here\u2019s one that Strava\u2019s Athlete Intelligence generated for a recent run:<\/p>\n<p class=\"duet--article--dangerously-set-cms-markup duet--article--standard-paragraph _1ymtmqpi _17nnmdy1 _17nnmdy0 _1xwtict1\">Intense run with high heart rate zones, pushing into anaerobic territory and logging a relative effort well above your typical range. <\/p>\n<p class=\"duet--article--dangerously-set-cms-markup duet--article--standard-paragraph _1ymtmqpi _17nnmdy1 _17nnmdy0 _1xwtict1\">Thanks? I can ask Athlete Intelligence to \u201csay more,\u201d but it regurgitates my effort, heart rate zone, and pace metrics I can see in graphs in the workout summary. If you didn\u2019t know anything about my athletic history or the circumstances surrounding this run, this summary might read as insightful. Here\u2019s what the summary left out: <\/p>\n<ul class=\"duet--article--unordered-list _1ymtmqpi _11h7yix0 _1xwtict1\">\n<li class=\"_11h7yix1\">It was dangerous to triple my mileage in only my second run of the year, given the high humidity, 85-degree-plus weather, and my spotty workout history over the past two months compared to the six months before it. Strava has access to weather data and every workout I\u2019ve done in the past five years. <\/li>\n<li class=\"_11h7yix1\">I had to cut this run short because I fell and shredded my hand and knees. This is information Strava has access to, as I uploaded a gnarly picture in addition to text notes. After adding said notes, the updated summary only reflected that I cut the run short. My injury changed nothing about its insights, even though it\u2019s the most important thing that happened during this run. <\/li>\n<\/ul>\n<p><a class=\"kqz8fh1\" href=\"https:\/\/platform.theverge.com\/wp-content\/uploads\/sites\/2\/2025\/06\/IMG_1046.png?quality=90&amp;strip=all&amp;crop=0,0,100,100\" data-pswp-height=\"2796\" data-pswp-width=\"1290\" target=\"_blank\" rel=\"noreferrer nofollow noopener\"><img alt=\"Screenshot of a Strava run\u2019s Elevation graph where it restates the elevation data shown directly above and below it in a graph.\" data-chromatic=\"ignore\" loading=\"lazy\" decoding=\"async\" data-nimg=\"fill\" class=\"x271pn0\" style=\"position:absolute;height:100%;width:100%;left:0;top:0;right:0;bottom:0;color:transparent;background-size:cover;background-position:50% 50%;background-repeat:no-repeat;background-image:url(&quot;data:image\/svg+xml;charset=utf-8,%3Csvg xmlns='http:\/\/www.w3.org\/2000\/svg' %3E%3Cfilter id='b' color-interpolation-filters='sRGB'%3E%3CfeGaussianBlur stdDeviation='20'\/%3E%3CfeColorMatrix values='1 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 100 -1' result='s'\/%3E%3CfeFlood x='0' y='0' width='100%25' height='100%25'\/%3E%3CfeComposite operator='out' in='s'\/%3E%3CfeComposite in2='SourceGraphic'\/%3E%3CfeGaussianBlur stdDeviation='20'\/%3E%3C\/filter%3E%3Cimage width='100%25' height='100%25' x='0' y='0' preserveAspectRatio='none' style='filter: url(%23b);' href='data:image\/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAQAAAC1HAwCAAAAC0lEQVR42mN8+R8AAtcB6oaHtZcAAAAASUVORK5CYII='\/%3E%3C\/svg%3E&quot;)\"   src=\"https:\/\/www.europesays.com\/us\/wp-content\/uploads\/2025\/06\/IMG_1046.png\"\/><\/a><\/p>\n<p>I don\u2019t know guys, without Athlete Intelligence, would I have known my elevation gain was a modest 88ft? Screenshot: Strava<\/p>\n<p class=\"duet--article--dangerously-set-cms-markup duet--article--standard-paragraph _1ymtmqpi _17nnmdy1 _17nnmdy0 _1xwtict1\">A more helpful insight might\u2019ve been: \u201cYou ran during record-breaking heat for your region. While you maintained a consistent and steady pace, you have a bad habit of ramping up mileage too quickly after prolonged breaks, leading to several self-reported injuries in the past five years. A safer alternative would be lower mileage runs over two weeks to acclimate to rising temperatures. Since you\u2019re injured, stick to low-intensity walks until your wounds have healed.\u201d<\/p>\n<p class=\"duet--article--dangerously-set-cms-markup duet--article--standard-paragraph _1ymtmqpi _17nnmdy1 _17nnmdy0 _1xwtict1\">Runna, a popular running app that also features AI insights, generated a slightly more useful summary. It said my next run should be \u201ceasy,\u201d one that\u2019s perfectly timed for me to recharge. I\u2019m sorry, but 48 hours isn\u2019t enough time for my knees to safely heal without risk of re-opening my wounds.<\/p>\n<p class=\"duet--article--dangerously-set-cms-markup duet--article--standard-paragraph _1ymtmqpi _17nnmdy1 _17nnmdy0 _1xwtict1\">The in-app chatbots aren\u2019t much better. Yesterday morning, I asked Whoop Coach if I should run today because I injured myself on my last run. It told me: \u201cWhoop is unable to reply to the message you sent. Please try sending a different message.\u201d I tried reframing my prompt, saying, \u201cI\u2019m injured and have a limp. Generate a low-intensity workout alternative while I recover.\u201d I was prompted to contact Whoop Membership Services to continue the conversation.<\/p>\n<p class=\"duet--article--dangerously-set-cms-markup duet--article--standard-paragraph _1ymtmqpi _17nnmdy1 _17nnmdy0 _1xwtict1\">Oura Advisor was more helpful, noting in my daily summary: \u201cWith your Readiness dipping and recent stressors like heat, an injury, and higher glucose, your body may feel more fatigued than usual today.\u201d It suggested I prioritize rest. When asked, \u201cWhat types of movement are okay when you have an injured knee and a slight limp?\u201d it responded with common-sense answers like a short and easy walk if there\u2019s no pain, light stretching, and a reminder to completely rest if I feel any sharp discomfort. This is closer to an ideal response, but I had to guide it to the type of answer I wanted. The insights are so general-purpose that they benefit self-quantification newbies \u2014 and even then, only if they\u2019re allergic to googling.<\/p>\n<p class=\"duet--article--dangerously-set-cms-markup duet--article--standard-paragraph _1ymtmqpi _17nnmdy1 _17nnmdy0 _1xwtict1\">My botched run is exactly the type of scenario where tech CEOs say AI insights could be most useful. In theory, I agree! It would be nice to have a competent, built-in chatbot that I could ask more nuanced questions. <\/p>\n<p><strong class=\"_1etxtj1e\">1\/3<\/strong>I tried this exact query twice and got the same result. Screenshot: Whoop<\/p>\n<p class=\"duet--article--dangerously-set-cms-markup duet--article--standard-paragraph _1ymtmqpi _17nnmdy1 _17nnmdy0 _1xwtict1\">For example, I\u2019ve had an irregular sleep schedule this month. I asked Oura Advisor if my sleep and readiness trends showed signs of an elevated risk of injury. I also asked if I had abnormally high levels of sleep debt this month. In both cases, it said no \u2014 it said I was improving.<\/p>\n<p class=\"duet--article--dangerously-set-cms-markup duet--article--standard-paragraph _1ymtmqpi _17nnmdy1 _17nnmdy0 _1xwtict1\">What resulted was an hour-long debate with a chatbot that left me questioning my own lived experience. When I tried asking it to delve into a particularly stressful week earlier this month, it told me its insights were \u201climited to [my] most recent week and current trends.\u201d That sort of defeats the point of having six years\u2019 worth of Oura data. <\/p>\n<p class=\"duet--article--dangerously-set-cms-markup duet--article--standard-paragraph _1ymtmqpi _17nnmdy1 _17nnmdy0 _1xwtict1\">After months of perusing Reddit and other community forums, I know I\u2019m not the only person who finds these AI features to be laughable. And yet, Holly Shelton, Oura\u2019s chief product officer, tells me that the response to Oura Advisor has been \u201coverwhelmingly positive,\u201d with 60 percent of users using it multiple times a week and 20 percent using it daily. \u201cBeyond frequency,\u201d Shelton says, \u201cIt\u2019s delivering real impact: 60 percent say Advisor has helped them better understand metrics or health concepts they previously found confusing.\u201d <\/p>\n<p class=\"duet--article--dangerously-set-cms-markup duet--article--standard-paragraph _1ymtmqpi _17nnmdy1 _17nnmdy0 _1xwtict1\">Meanwhile, Strava spokesperson Brian Bell tells me Athlete Intelligence was intended to help beginner athletes and that \u201cthe response to the feature remains strong\u201d with about \u201c80 percent of those opting in to give feedback finding the feature \u2018very helpful\u2019 to \u2018helpful.\u2019\u201d <\/p>\n<p class=\"duet--article--dangerously-set-cms-markup duet--article--standard-paragraph _1ymtmqpi _17nnmdy1 _17nnmdy0 _1xwtict1\">A Whoop spokesperson wasn\u2019t able to respond by publication.<\/p>\n<p class=\"duet--article--dangerously-set-cms-markup qnnwq2 _1xwtict9\">These milquetoast summaries? They\u2019re probably the best compromise between speed, cost, usefulness, data privacy, and legal liability<\/p>\n<p class=\"duet--article--dangerously-set-cms-markup duet--article--standard-paragraph _1ymtmqpi _17nnmdy1 _17nnmdy0 _1xwtict1\">I understand my frustrations stem from the inherent limitations of LLMs and the <a href=\"https:\/\/www.theverge.com\/2024\/11\/22\/24303124\/strava-fitness-data-wearables\" rel=\"nofollow noopener\" target=\"_blank\">messiness of private health data<\/a>. Strava might be a de facto fitness data hub, but it lacks all the health data points necessary to create holistic, useful, and personalized insights. It\u2019d take Oura Advisor a long time to crunch a year\u2019s worth of sleep data for trends. That latency is guaranteed to offer a bad user experience. Not to mention, they\u2019d likely have to up their subscription from $5.99 a month to add that type of computing power. I\u2019m not sure, but Whoop Coach may have declined my injury-related queries to protect itself from liability if something bad happened to me from following its suggestions. These milquetoast summaries are probably the best compromise between speed, cost, usefulness, data privacy, and legal liability. But if that\u2019s the case, then let\u2019s be honest. Current AI features are repackaged data, much like book reports written by a fourth-grader relying on a Wikipedia summary instead of reading the book. It\u2019s a feature tacked on with duct tape and a dream because AI is the zeitgeist. Perhaps one day, these AI insights will create a useful and personalized experience with actionable insights. That day is not today, and it\u2019s not worth paying extra for.<\/p>\n<p><a class=\"duet--article--comments-link b1p9679\" href=\"http:\/\/www.theverge.com\/fitness-trackers\/694140\/ai-summaries-fitness-apps-strava-oura-whoop-wearables#comments\" rel=\"nofollow noopener\" target=\"_blank\"><\/a><\/p>\n","protected":false},"excerpt":{"rendered":"After nearly a decade of wearables testing, I\u2019ve amassed a truly terrifying amount of health and fitness data.&hellip;\n","protected":false},"author":3,"featured_media":24797,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[38],"tags":[529,1198,705,11852,210,11853,242,67,132,68,3075],"class_list":{"0":"post-24796","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-fitness","8":"tag-analysis","9":"tag-fitness","10":"tag-gadgets","11":"tag-hands-on","12":"tag-health","13":"tag-reviews","14":"tag-tech","15":"tag-united-states","16":"tag-unitedstates","17":"tag-us","18":"tag-wearable"},"share_on_mastodon":{"url":"https:\/\/pubeurope.com\/@us\/114767332995316062","error":""},"_links":{"self":[{"href":"https:\/\/www.europesays.com\/us\/wp-json\/wp\/v2\/posts\/24796","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.europesays.com\/us\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.europesays.com\/us\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/us\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/us\/wp-json\/wp\/v2\/comments?post=24796"}],"version-history":[{"count":0,"href":"https:\/\/www.europesays.com\/us\/wp-json\/wp\/v2\/posts\/24796\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.europesays.com\/us\/wp-json\/wp\/v2\/media\/24797"}],"wp:attachment":[{"href":"https:\/\/www.europesays.com\/us\/wp-json\/wp\/v2\/media?parent=24796"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.europesays.com\/us\/wp-json\/wp\/v2\/categories?post=24796"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.europesays.com\/us\/wp-json\/wp\/v2\/tags?post=24796"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}