Add acknowledgements

_posts/2024-10-11-tim-weeknotes.md

@@ -30,16 +30,17 @@ In short, we're seeking to build a world of participatory and multi-stakeholder
  >
  > Which to focus on, and when, is often a strategic question.  
  
- Over the coming weeks we're putting together a couple of funding proposals that focus on different aspects of the grassroots, local, national and global, and one of the things I'll be working on for these is a clear articulation of how, in our work, these levels of action are intentionally connected and feed into one another. 
+ Over the coming weeks we're putting together a couple of funding proposals that focus on different aspects of the grassroots, local, national and global, and one of the things I'll be working on for these is a clear articulation of how, in our work, these levels of action are intentionally connected and feed into one another.
+
 ### Participatory uses of AI
 
-We had a meeting of the Public Voices in AI People's Advisory Panel this week, where one of our topics of discussion was the lifecycle of an AI Application, and where and how within this publics could or should be involved. Building on discussions at previous sessions, we wanted to give panel members more of an insight into the people behind an AI system, and to think about how particular stakeholders might be influenced. 
+We had a meeting of the Public Voices in AI People's Advisory Panel this week, where one of our topics of discussion was the lifecycle of an AI Application, and where and how within this publics could or should be involved (introduced by [Reema Patel](https://www.linkedin.com/in/reema-patel-34941228/) as part of the creation of a framework for the [PVAI programme](https://digitalgood.net/dg-research/public-voices-in-ai/)). Building on discussions at previous sessions, we wanted to give panel members more of an insight into the people behind an AI system, and to think about how particular stakeholders might be influenced. 
 
 Within the constraints of our two-hour zoom meetings with the panel, we realised it would be tricky to bring along lots of AI-developers to speak, and we didn't have resource to collect interviews in advance, so we decided to experiment with 'AI generated expert testimony'. In part, this was inspired as a response to the kind of *"Algorithmic proxies for participation."* [Delgado et. al.](http://arxiv.org/abs/2310.00907) found (§3.3.3) some AI developers turning to (asking AI systems, rather than people, for feedback on system design), and in part as a reflexive activity to also explore how the group felt about simulated testimony.
 
 To create our 'imagined experts', I used ChatGPT o1-mini with prompts such as: *"You are a data engineer called Amy. You work for a LawTech firm preparing data from courts to create an AI case outcome prediction tool. You are giving a talk to explain in 60 seconds what the job of a data engineer involves covering data cleaning, features engineering and transformations."*. With light editing (to get slightly more variety in the texts), I then fed these into [Kapwing's](https://www.kapwing.com/) persona tool, which provides text-to-speech and video lip-sync functions, to [generate videos like this one](https://www.kapwing.com/w/dkM1WxDv_s) (using a low quality lip-sync algorithm for speed: we didn't have chance to test the higher quality options). We provided the panel with scripts for each persona (that explained how they had been generated) and access to the videos in advance of our sessions, and then played the videos over the zoom call (where the poor lip-sync was more forgivable!).
 
-In the panel session, the idea of an AI lifecycle was first presented using slides, and before the group heard from our video personas, we had a discussion about where in the lifecycle panelists felt public voice was important. A lot of the emphasis in the discussion at this point was on the data preparation stage. After we had shown the persona videos, the discussion shifted, with more people focussing on inputting to research. In part, this appeared to be because of how personable the simulated video presenter had come across, but also I think reflected different perspectives on the importance of the stages of the lifecycle having heard information in this different persona rather than presentation format. 
+In the panel session, the idea of an AI lifecycle was first presented by Reema using slides, and before the group heard from our video personas, we had a discussion about where in the lifecycle panelists felt public voice was important. A lot of the emphasis in the discussion at this point was on the data preparation stage. After we had shown the persona videos, the discussion shifted, with more people focussing on inputting to research. In part, this appeared to be because of how personable the simulated video presenter had come across, but also I think reflected different perspectives on the importance of the stages of the lifecycle having heard information in this different persona rather than presentation format. 
 
 We didn't run this as a full experiment, though we [lightly applied a participatory pilot model](https://arc.net/l/quote/nxygezkw) to explore AI capabilities, and reflect on them with those affected (the group felt it was an interesting way to engage with content; as facilitator I felt more conflicted about the value they brought). There is more to be done to consider whether this is an approach I'd want to use widely in future.