AI beyond steps and scores: The next wave of quantified self
We hosted a dynamic panel exploring how design, science, and technology are converging to shape the future of data tracking and the quantified self. No longer just about step counts and calorie monitoring, today’s tools are unlocking real-time insights into our physiology, behaviors, and environments. But with this shift comes new challenges: how do we ensure the data is trustworthy, actionable, and designed to truly improve lives?
To unpack these questions, we brought together leaders working across the spectrum of health innovation: Rooz Ghaffari of Epicore, Tim Roberts of Therabody, and Tucker Fort of Smart Design. With backgrounds spanning biomedical engineering, sports science, and human-centered design, the panelists shared their experiences building technologies that go beyond passive tracking to actively support behavior change and wellbeing.
Keep reading for more in-depth takeaways from this insightful discussion!
01 The evolution of measurement
Over the past decade, the quantified self movement has evolved from counting steps and calories to unlocking deep physiological and biochemical insights. Advances in miniaturization and sensor technology have enabled real-time tracking of biomarkers like hydration, stress, and fatigue, once only possible in clinical labs.
02 Closing the loop for action
The biggest shift on the horizon is not just “track → recommend,” but “track → act.” Data that simply informs is no longer enough. The future lies in creating feedback loops that nudge or intervene at just the right moment with as little effort from the user as possible. Whether it’s haptic alerts prompting hydration or smart devices adjusting room temperature mid-sleep, the goal is to make health interventions ambient, contextual, and nearly invisible.
03 Designing for trust and ease
As devices become more intelligent and interventions more automatic, trust becomes paramount. Users need to feel confident that the technology will act in their best interest, especially when it’s acting on their behalf. As one panelist put it, “The less a user has to do, the more likely they are to benefit and stick with it.” That means taking the guesswork out and offering not just raw data, but clear, actionable guidance.
04 Personalized paths, not prescriptions
Automation should never override our ability to listen to our own bodies. Instead of simply recommending “do some exercises,” AI might identify a need—like strengthening a specific muscle group—and then suggest a few targeted activities to address it. This approach reinforces personal agency. It allows people to factor in how they feel in the moment, while still benefiting from expert-backed insight. This not only supports behavior change, but keeps people actively engaged in decisions about their health.
05 Consumer wellness vs. Clinical health
The boundaries between healthcare and consumer wellness are becoming increasingly blurry and clinging to a binary mindset ultimately limits progress. Unlocking the full potential of the quantified self means navigating regulatory complexity, redefining value models, and designing for behavior change that’s both clinically sound and emotionally resonant. The future of health tech lies in this convergence zone where science, design, and human context meet.
As the panel made clear, the future of the quantified self isn’t just about collecting more data. It’s about making that data meaningful, actionable, and seamlessly integrated into people’s lives. Whether through real-time feedback loops, trust-building design, or science-based credibility, true impact lies in closing the gap between insight and intervention for everyday usability.