Publication: Humanoid futures without lock-in: a design-driven framework for morphology, infrastructure, and policy
Program
KU-Authors
KU Authors
Co-Authors
Editor & Affiliation
Compiler & Affiliation
Translator
Other Contributor
Date
Language
eng
Type
Embargo Status
No
Journal Title
Journal ISSN
Volume Title
Alternative Title
Abstract
While humanoid robots are increasingly framed as the “natural” solution for human-scale environments (from factories to public spaces) this immediate “fit” carries the risk of a long-term “morphological lock-in.” This article argues that prioritizing human resemblance in robotics is not merely a technical choice but a socio-technical commitment that may prematurely foreclose alternative, and potentially more efficient, robotic forms. By synthesizing scholarship on path dependence with recent signals from the 2024–2025 industrial deployment wave, we identify three stabilizing mechanisms such as infrastructural compatibility, social familiarity, and narrowing engineering horizons. To counteract this tendency, we propose a three-level transition framework: (1) Design Research that decouples “fitness for task” from “human likeness” to generate morphological diversity
(2) Experimental Infrastructures that serve as incubation environments for non-humanoid forms
and (3) Anticipatory Governance that shifts standards from prescribing form to evaluating performance outcomes. This study contributes a design-driven roadmap to ensure that the future of robotics is not limited to a single archetype but remains open to a pluralism of bodies optimized for diverse functions. Copyright © 2026. Published by Elsevier Ltd.
(2) Experimental Infrastructures that serve as incubation environments for non-humanoid forms
and (3) Anticipatory Governance that shifts standards from prescribing form to evaluating performance outcomes. This study contributes a design-driven roadmap to ensure that the future of robotics is not limited to a single archetype but remains open to a pluralism of bodies optimized for diverse functions. Copyright © 2026. Published by Elsevier Ltd.
Source
Publisher
Elsevier
Subject
Robotics, Human likeness, Path dependence, Design frameworks, Governance
Citation
Has Part
Source
Social Sciences and Humanities Open
Book Series Title
Edition
DOI
10.1016/j.ssaho.2026.102680
item.page.datauri
Link
Rights
N/A
Copyrights Note
Creative Commons license
Except where otherwised noted, this item's license is described as N/A
