# When is it better for an AI assistant to say nothing? > Whenever speaking would cost more attention than it gives back: when the person can't take it in, the evidence is thin, or nothing needs to change. The 2018 framework for just-in-time support (Nahum-Shani et al.) counts giving nothing as a designed option, and declining uncertain cases makes a system's other answers more reliable (Geifman and El-Yaniv, 2017). - Page: https://tre-up.com/research/when-is-it-better-for-an-ai-assistant-to-say-nothing - Topic: [Timing and receptivity](https://tre-up.com/research/topics/timing-and-receptivity) - Published 2026-10-07 · Updated 2026-10-10 · 8 sources - Written by Pursue Lab, Tre-Up's research process (https://tre-up.com/research/method) - Cite as: Pursue Lab, Tre-Up (2026). When is it better for an AI assistant to say nothing? https://tre-up.com/research/when-is-it-better-for-an-ai-assistant-to-say-nothing ## Silence is a decision The framework for just-in-time support treats each moment as a decision point where providing nothing is one of the options, and warns that repeated prompting creates burden [1]. A 2026 review adds that people often can't engage at the very moment they need help most [2]. Decision theory frames each alert as a trade between the value of telling someone now and the cost of interrupting them [3]. Even useful content is disruptive at the wrong moment [4], and a notification costs attention even when it is ignored [5]. ## Why false alarms are expensive People learn to ignore systems that cry wolf; false alarms are a common cause of 'disuse' [6]. Every unnecessary signal makes the next useful one weaker. On the machine side, a system that may decline uncertain cases trades coverage for reliability [7]. Staying quiet is a legitimate action, not a failure. ## Silence is not the same as broken One distinction is easy to lose: choosing not to speak is different from being unable to. A classic security principle says systems should fail to the safe side [8]. By analogy, an assistant that can't work reliably should say so, not go quiet and let you think there was nothing to say. ## Where the evidence stops No study we found directly tests whether assistants that stay quiet more often lead to better outcomes. The sources support a design stance and testable hypotheses, not a proven rule. ## Something to try today Look at the apps allowed to interrupt you and ask of each one: when did it last tell me something I needed at that moment? Silence the ones you can't answer for. ## How Tre-Up approaches this Pursue has three possible answers: one small step, one question, or nothing to change. Saying nothing is designed in, and when Pursue can't work reliably it tells you so. Tre-Up is an iOS app in development. Pursue is the AI inside it. This note describes research and design intent, not results from the app. Nothing here is medical advice. ## Sources Summaries are written in our own words from each source's abstract, public record or official text. Follow the link to read the original. 1. Nahum-Shani I, Smith SN, Spring BJ, Collins LM, Witkiewitz K, Tewari A, Murphy SA (2018). Just-in-Time Adaptive Interventions (JITAIs) in Mobile Health: Key Components and Design Principles for Ongoing Health Behavior Support. Annals of Behavioral Medicine 52(6):446–462. https://doi.org/10.1007/s12160-016-9830-8 - Institutions: University of Michigan (United States); Northwestern University (United States); Pennsylvania State University (United States); University of New Mexico (United States) - Our summary: https://tre-up.com/research/sources/nahum-shani-2018-jitai 2. Nahum-Shani I, Murphy SA (2026). Just-in-Time Adaptive Interventions: Where Are We Now and What Is Next?. Annual Review of Psychology 77:679–703. https://doi.org/10.1146/annurev-psych-121024-044244 - Institutions: University of Michigan (United States); Harvard University (United States) - Our summary: https://tre-up.com/research/sources/nahum-shani-murphy-2026-jitai-review 3. Horvitz E, Jacobs A, Hovel D (1999). Attention-Sensitive Alerting. Proceedings of UAI 1999, 305–313. https://www.microsoft.com/en-us/research/publication/attention-sensitive-alerting/ - Institutions: Microsoft Research (United States) - Our summary: https://tre-up.com/research/sources/horvitz-1999-attention-sensitive-alerting 4. Mehrotra A, Pejovic V, Vermeulen J, Hendley R, Musolesi M (2016). My Phone and Me: Understanding People's Receptivity to Mobile Notifications. Proceedings of CHI 2016, 1021–1032. https://doi.org/10.1145/2858036.2858566 - Institutions: University of Birmingham (United Kingdom); University College London (United Kingdom); University of Ljubljana (Slovenia); University of Calgary (Canada) - Our summary: https://tre-up.com/research/sources/mehrotra-2016-receptivity 5. Stothart C, Mitchum A, Yehnert C (2015). The attentional cost of receiving a cell phone notification. Journal of Experimental Psychology: Human Perception and Performance 41(4):893–897. https://doi.org/10.1037/xhp0000100 - Institutions: Florida State University (United States) - Our summary: https://tre-up.com/research/sources/stothart-2015-notification-cost 6. Parasuraman R, Riley V (1997). Humans and Automation: Use, Misuse, Disuse, Abuse. Human Factors 39(2):230–253. https://doi.org/10.1518/001872097778543886 - Institutions: Catholic University of America (United States); Honeywell Technology Center (United States) - Our summary: https://tre-up.com/research/sources/parasuraman-riley-1997-use-misuse 7. Geifman Y, El-Yaniv R (2017). Selective Classification for Deep Neural Networks. Advances in Neural Information Processing Systems 30 (NeurIPS 2017). https://arxiv.org/abs/1705.08500 - Institutions: Technion – Israel Institute of Technology (Israel) - Our summary: https://tre-up.com/research/sources/geifman-el-yaniv-2017-selective-classification 8. Saltzer JH, Schroeder MD (1975). The Protection of Information in Computer Systems. Proceedings of the IEEE 63(9):1278–1308. https://doi.org/10.1109/PROC.1975.9939 - Institutions: Massachusetts Institute of Technology (United States) - Our summary: https://tre-up.com/research/sources/saltzer-schroeder-1975-protection ## Related notes - [When is the right moment for a reminder or a nudge?](https://tre-up.com/research/when-is-the-right-moment-for-a-reminder.md) - [How should an AI say it isn't sure?](https://tre-up.com/research/how-should-an-ai-say-it-isnt-sure.md) --- © 2026 Tre-Up. You may read, link to, quote and summarise Research Notes, and search engines and AI assistants may index, summarise and cite them, as long as the source is credited with a link to the page on tre-up.com. Please do not present our notes as your own, or republish whole pages, without permission. Terms: https://tre-up.com/terms#use · About Tre-Up: https://tre-up.com/about