从指标到意义：是时候重新思考人机协同设计中的评估了
From Metrics to Meaning: Time to Rethink Evaluation in Human-AI Collaborative Design
AI总结：
针对传统人机协同设计评估仅关注行为与设计质量指标的不足，该研究通过大规模实地与实验室实验验证MAP--Elites系统可提升用户参与度与设计质量，提出需从情感、行为、认知多维度整体评估人机系统。
摘要：
随着AI系统越来越多地影响创意设计场景下的决策，理解人类如何与这些工具交互已成为交互智能系统研究的关键挑战。本文提出一项挑战，即重新思考如何评估人机协同系统，倡导采用更细致、多维度的评估方法。研究呈现了迄今规模最大的人机协同创作系统实地研究之一（样本量n=808）的发现，研究对象为The Genetic Car Designer（遗传汽车设计师）系统，同时辅以一项受控实验室研究（样本量n=12）。该系统基于交互式进化算法，参与者的任务是设计简单的二维汽车造型。参与者分别接触由智能系统MAP--Elites生成的设计建议图库，以及随机对照组的设计图库。结果表明，接触MAP--Elites生成的图库能显著提升认知和行为参与度，进而带来更高质量的设计成果。对更广泛的研究领域而言至关重要的是，分析显示传统评估方法往往仅关注行为和设计质量指标，无法全面覆盖用户参与的全部维度。通过将人机设计过程视为设计师不断变化的情感、行为与认知状态，我们提出应整体评估人机系统，并将智能系统视为用户体验的核心组成部分，而非仅仅是后端工具。
英文摘要：
As AI systems increasingly shape decision making in creative design contexts, understanding how humans engage with these tools has become a critical challenge for interactive intelligent systems research. This paper contributes a challenge to rethink how to evaluate human--AI collaborative systems, advocating for a more nuanced and multidimensional approach. Findings from one of the largest field studies to date (n = 808) of a human--AI co-creative system, The Genetic Car Designer, complemented by a controlled lab study (n = 12) are presented. The system is based on an interactive evolutionary algorithm where participants were tasked with designing a simple two dimensional representation of a car. Participants were exposed to galleries of design suggestions generated by an intelligent system, MAP--Elites, and a random control. Results indicate that exposure to galleries generated by MAP--Elites significantly enhanced both cognitive and behavioural engagement, leading to higher-quality design outcomes. Crucially for the wider community, the analysis reveals that conventional evaluation methods, which often focus on solely behavioural and design quality metrics, fail to capture the full spectrum of user engagement. By considering the human--AI design process as a changing emotional, behavioural and cognitive state of the designer, we propose evaluating human--AI systems holistically and considering intelligent systems as a core part of the user experience -- not simply a back end tool.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
