PEAs in Pods: Co-production of community-based public engagement for data and AI research

我们的项目，豆荚中的豌豆，将使大曼彻斯特(GM)数据科学和人工智能(AI)研究社区能够与传统上被边缘化的社区进行有意义的接触，并将联合生产方法嵌入个人和机构的研究流程和治理中。我们公众参与活动的主题是围绕人工智能和数据驱动技术。让公民参与这一领域的研究和开发的必要性日益得到广泛认识，其好处包括增加公众信任和更多与社会相关的应用。如果我们想要建立信任，我们必须首先接触公民，激励他们参与进来，并证明他们的声音具有影响力。我们将培训一批来自三所转基因大学的数据科学家和人工智能研究人员，他们被称为公共参与大使(Peas)，然后指导和指导他们与来自三个传统上被边缘化和数字排斥群体的合作研究人员自信地合作。团队将共同制作一套相关的公共参与活动和活动，以回应这些社区团体的不同需求、兴趣和理解。在评估之后，他们将共同开发一套遗留资源，用于在主题为“数据伦理和人工智能在盒子中”的项目之外的持续社区参与。同时，公众参与冠军将与大学接触，以建立对长期研究人员与社区互动的认识和兴趣。她将领导联合制作机制，将与传统上被边缘化的群体的持续互动嵌入整个通用汽车的机构研究流程。因此，该项目还将使这些社区拥有发言权，并帮助影响数据科学和人工智能研究的方向及其对社会的影响。

Our project, PEAs in Pods, will empower the Greater Manchester (GM) data science and artificial intelligence (AI) research communities to engage meaningfully with traditionally marginalised communities and embed coproduction methods into individual and institutional research processes and governance. The theme of our public engagement activities is around AI and data-driven technologies. The need to engage citizens in the research and development of this field is increasingly widely recognised, with benefits including increased public trust and more socially relevant applications. If we want to build trust we must first reach out to citizens, inspire them to get involved and demonstrate that their voices have influence.We will train a cohort of data scientists and AI researchers, known as Public Engagement Ambassadors (PEAs), from three GM universities, then guide and mentor them to work confidently with co-researchers from three traditionally marginalised and digitally excluded groups. Teams will co-produce a set of relevant public engagement events and activities that respond to the distinct needs, interests, and understandings of these community groups. Following evaluation, they will then co-develop a set of legacy resources for on-going community engagement beyond the project under the theme "Data Ethics and AI in a Box". In parallel, the Public Engagement Champion will engage with the universities to build awareness of and appetite for longer-term researcher-community interaction. She will lead the co-production of mechanisms that will embed sustained interaction with traditionally marginalised groups into institutional research processes across GM. The project will therefore also empower these communities to have a voice and help influence the direction of data science and AI research and its impact on society.