TY - GEN
T1 - Design from Zeroth Principles
AU - Suchow, Jordan W.
AU - Pacer, Michael D.
AU - Griffiths, Thomas L.
N1 - Publisher Copyright:
© 2016 Proceedings of the 38th Annual Meeting of the Cognitive Science Society, CogSci 2016. All rights reserved.
PY - 2016
Y1 - 2016
N2 - A successful design accounts for the structure of the problem it is aimed at solving. When it is a human-directed design, this includes the expectations of its users. How do we arrive at such a design? One approach starts from first principles (e.g., simplicity, unity, symmetry, balance) to evaluate the quality of proposed designs. Here, we introduce design from zeroth principles, a form of human-in-the-loop computation that synthesizes a design that conforms to its users' expectations. The technique begins by constructing a transmission chain seeded with a random design. Each user in the chain is exposed to the design and then recreates it, passing along their recreation to the next user, who does the same. Through this iterative process, the users' perceptual, inductive, and reconstructive biases directly transform the initial design into one that is better fit to human cognition. Such designs are easier to learn and harder to forget. We evaluated the approach in three domains - stimulus-response mappings, vanity phone numbers, and letter placement in typeset words - and show that it produces a good design in each.
AB - A successful design accounts for the structure of the problem it is aimed at solving. When it is a human-directed design, this includes the expectations of its users. How do we arrive at such a design? One approach starts from first principles (e.g., simplicity, unity, symmetry, balance) to evaluate the quality of proposed designs. Here, we introduce design from zeroth principles, a form of human-in-the-loop computation that synthesizes a design that conforms to its users' expectations. The technique begins by constructing a transmission chain seeded with a random design. Each user in the chain is exposed to the design and then recreates it, passing along their recreation to the next user, who does the same. Through this iterative process, the users' perceptual, inductive, and reconstructive biases directly transform the initial design into one that is better fit to human cognition. Such designs are easier to learn and harder to forget. We evaluated the approach in three domains - stimulus-response mappings, vanity phone numbers, and letter placement in typeset words - and show that it produces a good design in each.
KW - cognitive ergonomics
KW - design
KW - inductive bias
KW - transmission chain
KW - user interface
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M3 - Conference contribution
AN - SCOPUS:85136153481
T3 - Proceedings of the 38th Annual Meeting of the Cognitive Science Society, CogSci 2016
SP - 1505
EP - 1510
BT - Proceedings of the 38th Annual Meeting of the Cognitive Science Society, CogSci 2016
A2 - Papafragou, Anna
A2 - Grodner, Daniel
A2 - Mirman, Daniel
A2 - Trueswell, John C.
T2 - 38th Annual Meeting of the Cognitive Science Society: Recognizing and Representing Events, CogSci 2016
Y2 - 10 August 2016 through 13 August 2016
ER -