Why We're Different in the Morning and Evening express
Every morning you pick up the same mug, but the coffee tastes either bitter or just right. It's not about the coffee, and not about your character. Inside us, an invisible panel with dozens of sliders is constantly shifting: fatigue, hunger, anxiety, hormone levels. At different times of day, they sit at different positions, and the same signal from the outside world produces a completely different outcome.
The authors of the study call this panel a state — a snapshot of how the body, brain, and biology process the next event. It's not a personality trait but rather the weather inside: clouds roll in and out, changing the lighting of the same landscape. A decision is not predetermined by past experience: it is born here and now, when an external push meets the momentary settings of all the body's systems.
The most interesting part: consciousness is just a narrow slit through which we see our own state. We notice only what falls into the focus of attention, and the focus itself also depends on the slider positions. That's why we can influence a choice not through lengthy persuasion but with a brief intervention at the right moment, like adjusting the settings before taking a photo.
The researchers tested this idea on data from hundreds of thousands of people and derived seven testable predictions. If we learn to catch the moment when the sliders are in a favorable position, we can help people make decisions in medicine, education, or even in an ordinary phone app. Morning coffee will taste good again, but now we'll know it's not about the coffee, but about ourselves.
Original abstract
as written by the authors arXiv:2605.27580
A central puzzle for the behavioural sciences and for human-facing artificial intelligence is the persistence of within-person variability. The same individual, presented with the same observable input, produces different outcomes on different occasions, and different individuals produce divergent outcomes that no observable covariate fully predicts. We argue that this variability belongs in the dynamic latent state of the person, and that human outcomes are controllable in a precise and operational sense through interventions that target the state and its weighting at the moment a decision is being formed. We define a state as the time-indexed weighting vector over the dimensions that govern how an individual's biology, physiology, and neuropsychology process the next event into a decision and an outcome. The relationship between state, decision, and outcome is causal rather than correlational. The weighting vector is dynamic at sub-daily timescales. The conscious channel through which outcomes are reportable is a narrow attentional bottleneck whose contents are themselves state-dependent. Taken together, these claims imply that the outcome of a given event is controllable, conditionally, on the state-trajectory at the time of intervention. We motivate the framework with six strands of established evidence (causal inference, predictive processing, allostasis, attentional bottleneck, chronobiology, computational psychiatry) and a 24-month observational base from a deployed behavioural platform spanning more than 200,000 consented users across four occupational personas (research period 2023 to 2026). We derive seven testable predictions, list six operational requirements for state-aware systems, and discuss implications for digital health, education, AI personalisation, and personal agency.
Over the course of a day, our internal 'sliders'—cortisol levels, body temperature, gene activity — change with an amplitude comparable to the difference between different people.