Against a backdrop of widespread interest in how publics can participate in
the design of AI, I argue for a research agenda focused on AI incidents -
examples of AI going wrong and sparking controversy - and how they are
constructed in online environments. I take up the example of an AI incident
from September 2020, when a Twitter user created a 'horrible experiment' to
demonstrate the racist bias of Twitter's algorithm for cropping images. This
resulted in Twitter not only abandoning its use of that algorithm, but also
disavowing its decision to use any algorithm for the task. I argue that AI
incidents like this are a significant means for participating in AI systems
that require further research. That research agenda, I argue, should focus on
how incidents are constructed through networked online behaviours that I refer
to as 'networked trouble', where formats for participation enable individuals
and algorithms to interact in ways that others - including technology companies
- come to know and come to care about. At stake, I argue, is an important
mechanism for participating in the design and deployment of AI.

研究人工智能事故及其在在线环境中的构建机制，并探讨人工智能设计与部署中的参与方式。

AI 事件和 ' 联网麻烦 ': 一个研究议程的案例

AI incidents and 'networked trouble': The case for a research agenda

We exemplify how Large Language Models are used in both teaching and
learning. We also discuss the AI incidents that have already occurred in the
education domain, and we argue for the urgent need to introduce AI policies in
universities and for the ongoing strategies to regulate AI. Regarding policy
for AI, our view is that each institution should have a policy for AI in
teaching and learning. This is important from at least twofolds: (i) to raise
awareness on the numerous educational tools that can both positively and
negatively affect education; (ii) to minimise the risk of AI incidents in
education.

我们示范了大型语言模型在教学和学习中的应用，并讨论了已经在教育领域发生的人工智能事件，我们主张迫切需要在大学引入人工智能政策并进行持续的监管策略。关于人工智能政策，我们认为每个机构都应该拥有关于人工智能在教学和学习中的政策，这至少有两个重要方面：（一）提高对多种教育工具的认识，这些工具既能积极地也能负面地影响教育；（二）减少教育中的人工智能事件风险。