Paper Overview
- Research area: AI
- Authors: Suraj Biswas, Saurav Gupta, Pritam Mukherjee
- Published: 2026-05-28
- arXiv: 2605.27580
- Within-person variability is the core phenomenon the paper tries to explain: identical inputs do not produce identical outputs for the same person.
- Latent state is introduced as the locus of this variability, capturing biology, physiology, and neuropsychology through a time-indexed weighting vector.
- Causality: the state–decision–outcome link is causal, not merely statistical correlation, which justifies targeting the state through intervention.
- Temporal dynamics: the weighting vector changes within a single day, so interventions must be time-sensitive.
- Attentional bottleneck: consciously reportable outcomes are a narrow subset of the state, meaning self-reports alone under-describe the underlying state.
- Implication for AI: human-facing AI systems can be designed to influence the state at the moment of decision formation, enabling controllable rather than merely predictive behaviour modelling.
- arXiv link: https://arxiv.org/abs/2605.27580
- *Automatically collected on 2026-05-29*
Summary
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. The authors 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.
A state is defined 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 varies dynamically on within-day (intra-day) timescales. The conscious, reportable channel of outcomes is a narrow attentional bottleneck whose content itself depends on the state. Taken together, the paper claims that the outcome of a given event is controllable conditional on the trajectory of the state at the moment of intervention.