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Human sensorimotor control exhibits remarkable speed and accuracy, and thetradeoff between them is encapsulated in Fitts' Law for reaching and pointing.While Fitts related this to Shannon's channel capacity theorem, despitewidespread study of Fitts' Law, a theory that connects implementation ofsensorimotor control at the system and hardware level has not emerged. Here wedescribe a theory that connects hardware (neurons and muscles with inherentsevere speed-accuracy tradeoffs) with system level control to explain Fitts'Law for reaching and related laws. The results supporting the theory show thatdiversity between hardware components is exploited to achieve both fast andaccurate control performance despite slow or inaccurate hardware. Such"diversity-enabled sweet spots" (DESSs) are ubiquitous in biology andtechnology, and explain why large heterogeneities exist in biological andtechnical components and how both engineers and natural selection routinelyevolve fast and accurate systems using imperfect hardware.

Fitts' Law for speed-accuracy trade-off describes a diversity-enabled sweet spot in sensorimotor control