> ## Documentation Index > Fetch the complete documentation index at: https://meta.niceshare.site/llms.txt > Use this file to discover all available pages before exploring further. # Hick's Law > Hick's Law links reaction time to the number of alternatives via a logarithmic rule. Learn the 1952 origin, UX uses, and limits. **Category**: Laws
**Type**: Cognitive / psychophysical regularity (choice reaction time)
**Origin**: William E. Hick, *Quarterly Journal of Experimental Psychology*, **1952**
**Also known as**: Hick–Hyman law (related formulation) **Quick Answer** — **Hick’s Law** says that, in simple choice tasks, **reaction time grows with the logarithm of the number of equally likely alternatives**—not linearly with raw option count. It helps explain menu design, emergency controls, and any interface where scanning and deciding compete with acting. It is a tendency across conditions, not a single universal constant for every real-world decision. ## What is Hick's Law? **Hick’s Law** describes a robust pattern in **choice reaction time**: when stimuli are equally probable and the task is cleanly defined, **mean reaction time increases roughly in proportion to the logarithm of the number of alternatives**—often written with a base-2 log form because information is measured in bits. The relationship connects cognitive psychology to [Weber–Fechner scaling](/laws/weber-fechner-law) intuitions (perception compresses stimulus ratios) and complements [Yerkes–Dodson](/laws/yerkes-dodson-law) concerns about arousal and performance. It differs from [choice overload](/effects/choice-overload) in emphasis: Hick focuses on **timed discrimination among labeled options**, while overload often includes preference formation and regret. > More forks on the road do not add equal seconds—complexity compounds gently at first, then demands structure. ### Hick's Law in 3 Depths * **Beginner**: Expect visibly slower taps when a screen adds a few equally plausible buttons; shrinking counts helps more than “bigger font.” * **Practitioner**: Chunk options into **progressive steps** or defaults so each step keeps *n* small; measure task time, not opinion polls about “simplicity.” * **Advanced**: Recognize domain limits—semantic search, expertise, and unequal priors break the tidy equal-probability setup. ## Origin **William Edmund Hick** published “On the Rate of Gain of Information” in **1952** in the *Quarterly Journal of Experimental Psychology*, reporting choice-reaction experiments (including setups with **10** response alternatives arranged around a subject). The paper helped crystallize the idea that humans process choice information at a roughly steady **bits-per-second** rate in those paradigms. **Ray Hyman** reported related linear relations between reaction time and transmitted information in **1953**, which is why the pairing is often called **Hick–Hyman** in textbooks. ## Key Points Use Hick to budget attention in timed tasks, not to excuse bad information architecture. Doubling alternatives does not double time in these models—yet zero shortcuts still vanish if *n* explodes. The cleanest fits assume alternatives are equiprobable and clearly labeled; skewed priors change optimal strategies. Observed latency includes perception, memory retrieval, and movement—Hick isolates a slice, not the whole product experience. Good IA moves decisions from one giant menu to several small, meaningful choices. ## Applications Translate the law into measurable design moves. Reduce parallel top-level actions; use **progressive disclosure** and strong defaults so each step’s option count stays small. In high-stress consoles, match control layout to **muscle memory** and limit simultaneous decisions—Hick adds latency where seconds matter. Multiple-choice length affects speed and error; fair comparisons hold item difficulty constant when changing option counts. Approval chains multiply alternatives—**clarify decision rights** so individuals face fewer simultaneous competing moves. ## Case Study Hick’s empirical anchor is his **1952** paper’s controlled laboratory setting: participants responded to one of **10** alternative stimuli in a choice reaction paradigm, enabling quantitative fits between **number of alternatives** and **reaction time distributions**. That work is why modern HCI references cite Hick when arguing that shaving a menu from many peer options to fewer **meaningful** branches can reduce mean selection latency—an effect you can approximate in usability tests with median task-time and error-rate metrics, even though office software rarely matches equiprobable lab conditions perfectly. ## Boundaries and Failure Modes **Boundary 1: Experts compress menus**\ Practice and chunking change effective *n*; experts are not bound by novices’ curves. **Boundary 2: Preference is not discrimination**\ Choosing what you *want* involves taste and tradeoffs beyond simple reaction tasks. **Common misuse**: Shrinking options by **hiding** critical functions—latency drops while failures rise. ## Common Misconceptions Keep the law’s laboratory roots visible. **Reality**: Search, filters, and recommendations change the task; Hick targets simultaneous equally likely choices. **Reality**: Input modality, target size (see Fitts-style constraints), and fatigue shift measured times. **Reality**: Rushed selections raise errors—pair time with accuracy and safety margins. ## Related Concepts Connect these when tuning decisions under time pressure. Arousal and performance follow an inverted-U—stress interacts with Hick-style latency. Perception often scales logarithmically—cousin intuition for compressed stimulus scales. Beyond reaction time—preference, satisfaction, and regret when assortments grow. ## One-Line Takeaway Cut *effective* alternatives per step—defaults, grouping, and search—before polishing pixels.