Co-designing with AI: Design Approaches to Creativity Support with Imbedded Artificial Intelligence

随着功能性人工智能变得越来越容易获得，人们越来越认识到，设计方法，特别是在人机交互中，需要适应将计算智能因素纳入设计结果。Holmquist(2017)认为新兴的人工智能实用实现是“一种新的设计材料”，并定义了使用这种材料设计的一些挑战，包括“为不可预测性而设计”、“为进化而设计”和“为共享控制而设计”。然而，人工智能的挑战也代表着机遇。通过改变“为..而设计”对于“使用..进行设计”，人工智能的这些特殊挑战可能被重新定义为方法优势(例如，在项目的构思阶段的不可预测性，导致问题和创造性的反应)。这些因素背后是人工智能的自主性和“主动智能”(Holmquist，2017)。正是在这里，“材料”的隐喻遇到了身体的限制，人工智能明显缺乏定义材料的一致和可预测的物理属性。相比之下，Manovich(2013)将“由软件实时构建”的数字体验描述为瞬时的“软件表演”。将计算机系统视为表演者(演员遵循剧本，代表系统设计者做出决定和假设，并对观众的行动做出反应)与人工智能的高度自主性有特别的共鸣。在这种赋予人工智能权利的观点中，在设计过程中将其视为参与者而不是非物质似乎更合适。尽管实用的人工智能系统具有新兴的性质，但已经有一个既定的研究机构来检验这一方法。例如，Boden(1994)的创造性程序化代理概念，Lubart(2005)的人格化计算创造性合作者类别(特别是“计算机作为同事”的角色)以及Gabriel等人(2016)记录的许多创造力支持系统。此外，AIY工具包(Google，2018)的引入提供了一种实用的、适应性强的、有用的体现在设计过程中的人工智能表示方法。

As functional AI becomes more accessible, there is a growing recognition that design methods,particularly within Human Computer Interaction, need to adapt to factor computationalintelligence into design outcomes. Holmquist (2017) considers emerging practicableimplementations of AI as "a new design material" and defines some challenges to designing withthis material, which include "Designing for unpredictability", "Designing for evolution", and"Designing for shared control".Yet the challenges of AI can also represent opportunities. By shifting 'designing for..' to'designing with..', these particular challenges of AI could potentially be reframed asmethodological advantages (e.g. unpredictability within the ideation stage of a project leading tounique and creative responses). Underlying these factors is the autonomy and "proactiveintelligence" of AI (Holmquist, 2017). It is here that the 'material' metaphor encounters somelimitations, with AI conspicuously lacks the consistent and predictable physical properties thatdefine materials.In contrast Manovich (2013) describes digital experiences being "constructed by software in realtime" as momentary "software performances". Considering the computer system as a performer(an actor following a script, making decisions and assumptions on behalf of the system designerand in response to audience actions) has particular resonance with the heightened autonomy ofAI. In this enfranchising view of AI it seems more appropriate to treat it as participant rather than amaterial during the design process.Despite the emerging nature of practical AI systems, there is already an established body ofresearch examining this approach. For example Boden's (1994) concept of programmatic agentsfor creativity, Lubart's (2005) personified categories of computational creative collaborators (inparticular the role of "computer as colleague") and many of the creativity support systemsdocumented by Gabriel et al (2016).Furthermore, the introduction of AIY Kits (Google, 2018) provide a practical, adaptable, andusefully embodied method of representing AI in the design process.