Horizon CDT Year 1

地平线 CDT 第 1 年

• 批准号: 2887466
• 金额: --
• 依托单位: University of Nottingham
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2887466
• 关键词: Horizon; CDT; Year

Rider Spoke is a project that invites you to cycle alone through the city with a smartphone attached to your handlebars. Guided by the voice of a narrator, you are asked questions about your life and then search for a place to record your answer to each one. As you cycle, you choose whether to answer another question or listen to the answers left by other cyclists.Conceived by Blast Theory in 2007 as a response to the emergence of user-generated content, the project facilitates contributions from its audiences that are open, intimate and reflective. After taking part, audiences commonly report a feeling of recognition in the recordings they listen to, and a renewed sense of belonging to the city and its people.The project has toured to 30 cities around the world with about twenty-five thousand audience recordings being made in that time. As such, it offers a unique opportunity to study how sharing personal stories can contribute to social cohesion and explore the potential that machine learning and large language models might play in this context.What new insights about the stories shared within Rider Spoke can these technologies produce? And how might these technologies be used by artists and designers of mixed reality experiences to support social cohesion?I will combine linguistic and machine learning approaches to study the stories and data saved in Rider Spoke recordings. And - informed by insights from this study - I will design a series of novel public prototypes that test potential roles for AI in supporting social cohesion on new platforms, and in new contexts.This author is supported by the Horizon Centre for Doctoral Training at the University of Nottingham (UKRI Grant No. EP/S023305/1).

Rider Spoke是一个项目，邀请你在车把上安装智能手机，独自骑自行车穿过城市。在旁白的引导下，你被问到关于你生活的问题，然后寻找一个地方记录你对每个问题的回答。当你骑车时，你可以选择是回答另一个问题还是听其他骑车者的回答。作为对用户生成内容的回应，Blast Theory于2007年构思了该项目，该项目促进了观众的贡献，这些贡献是开放的、亲密的和反思的。在参与之后，听众们普遍表示，他们听到的录音中有一种认同感，对这座城市和这里的人有了一种新的归属感。该项目已在全球30个城市巡回演出，期间录制了约2.5万份听众录音。因此，它提供了一个独特的机会来研究分享个人故事如何有助于社会凝聚力，并探索机器学习和大型语言模型在这种情况下可能发挥的潜力。这些技术可以产生哪些关于Rider Spoke中分享的故事的新见解？这些技术如何被混合现实体验的艺术家和设计师用来支持社会凝聚力？我将结合语言和机器学习方法来研究保存在Rider Spoke录音中的故事和数据。根据这项研究的见解，我将设计一系列新颖的公共原型，以测试人工智能在支持新平台和新环境下的社会凝聚力方面的潜在作用。本文作者是由诺丁汉大学博士培养地平线中心(UKRI资助号：EP / S023305/1)。