Update, August 2026: We’ve since finished evaluating providers and settled the design, so parts of this post are now out of date. It originally named ANU as an example provider — we build on Outshift by Cisco. It also described the feature as opt-in; it will be on by default with a setting to turn it off. And the consciousness-correlation idea below is one we’ve decided not to pursue — see the note in that section. The original text is otherwise unchanged.
Most mood tracking apps follow a predictable formula: you log how you feel, the app finds patterns, and it reflects those patterns back to you. It’s useful, but it has a ceiling. Algorithms trained on your past behavior tend to reinforce what you already know about yourself. They’re mirrors, not windows.
At FeelTrack, we’re exploring something different: integrating quantum random number generators (QRNGs) into the mood awareness experience. Not to replace pattern recognition, but to introduce something that algorithms fundamentally cannot produce — genuine unpredictability.
The Problem with Predictable Wellness
Conventional mood tracking creates a feedback loop. You report feeling anxious on Monday mornings. The app learns this. It starts prompting you about anxiety on Monday mornings. Over time, the tracking tool subtly reinforces the very pattern it’s observing.
This is a well-documented limitation in self-tracking psychology. When the system always meets you where you expect to be, it becomes harder to discover where else you might go.
True randomness breaks this loop.
What Quantum Randomness Adds
A quantum random number generator produces outcomes that are not determined by any prior state — not by your history, not by an algorithm, not by any hidden variable. Each number emerges from the quantum behavior of photons, irreducibly fresh.
Here’s how we envision integrating this into FeelTrack:
Randomized Reflection Prompts
Instead of always asking “How do you feel?” at predictable intervals with predictable framing, QRNG-driven prompts would introduce genuinely novel angles:
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Questions timed to quantum-random intervals, breaking habitual check-in patterns
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Prompt topics selected from unexpected categories — a question about a childhood memory when you expected one about work stress
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Random pairing of unrelated emotional dimensions, surfacing connections you hadn’t considered
The goal isn’t chaos. It’s productive surprise — the kind of gentle disruption that shakes loose insights stuck behind habitual self-narratives.
Quantum-Seeded Mood Exploration
Imagine a daily mood exploration exercise where the starting point isn’t determined by your history, but by a quantum random seed. The exercise might lead you to reflect on gratitude one day and vulnerability the next, with no algorithmic reason for the sequence. Over time, this builds a richer, less biased emotional vocabulary.
Consciousness Correlation Experiments
We are no longer pursuing this. Our design generates each quantum value after your rating is already recorded, which means your emotional state is fixed before any photon is measured. That arrangement cannot test whether consciousness influences a quantum system — whatever it measures, it isn’t that. Rather than keep a hypothesis our own architecture rules out, we dropped it. What we’re studying instead is described in Your Mind Will Find Meaning in Pure Noise. The original text follows, for the record.
Drawing inspiration from Entangled.org and decades of QRNG-consciousness research at institutions like Princeton and IONS, FeelTrack could offer opt-in experiments that correlate your emotional state with quantum random outputs.
The question: when you report feeling particularly centered, calm, or emotionally intense, do your dedicated quantum random bits show any statistical deviation from expected randomness?
We’re not claiming they will. We’re saying the question is worth asking at scale, with rigorous methodology, and that a mood-tracking platform with hundreds of thousands of daily emotional data points is uniquely positioned to ask it.
How We’d Implement It
The technical approach is straightforward:
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QRNG API integration — We evaluated the available providers and build on Outshift by Cisco’s QRNG API, which serves certified quantum random numbers over REST. No quantum hardware needed on our end.
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Random prompt engine — A new prompt selection layer that uses QRNG output to determine timing, framing, and content of mood check-ins, blended with the existing pattern-aware system.
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Correlation dashboard — A view showing your own emotional data alongside your quantum values, with the statistics stated honestly — including when they show nothing.
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Privacy-first design — All quantum data would be anonymized and aggregated. Individual QRNG streams would never be shared or used for identification.
The Bigger Picture
This isn’t about proving that consciousness affects quantum systems. It’s about something more practical: using true randomness to make self-awareness less predictable and more generative.
The wellness technology space is saturated with apps that learn your patterns and feed them back to you. That’s valuable, but it’s only half the picture. The other half is discovering what you don’t know about yourself — and that requires something no algorithm can provide: genuine novelty.
Quantum randomness is the only source of novelty that is provably not determined by anything that came before. In a mood tracking context, that’s not a gimmick. It’s a feature that addresses a real limitation of pattern-based approaches.
What’s Next
Provider evaluation is finished and the operational groundwork is deployed — including the unglamorous part, the alerting that tells us before our API key quietly expires. What’s still to come is the visible half: attaching quantum values to individual emotion responses, and asking what people make of them.
When that ships, it will be on by default, with a switch in your settings to turn it off. You don’t need to sign up for anything. The quantum values never alter your ratings — they’re recorded alongside them, and every trend, insight and streak you see stays computed from exactly what you reported.
If you’d rather not take part, one click turns it off and nothing else about your check-ins changes.
We’ll share our findings as the research progresses — including the null results, if that’s what we get.
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