Uh, they met, they produced statements, um, uh, around the definition of glaucoma, um, and, uh, ultimately we actually had a, uh, Delphi process through which we voted on these statements prior to the workshop, uh, so we would come in, uh, with a better understanding of where the agreement lay and also where the disagreement was that we needed to discuss during the workshop

workshopSo during the workshop itself, um, we actually had each of the working group, um, leads, and there were five in total, um, come up and present their consensus statements and, um, open discussion to the rest of the working group members to, um, to debate and discuss, um, their opinions.

And just to give an idea of what some of the broad categories of, uh, work, um, and discussion, we had a working group, um, targeted at identifying the barriers and knowledge gaps and identifying, you know, historical and conceptual empirical reasons why we haven't, uh, come up yet with a unified operational definition.

Um, a whole working group looking at the conceptual basis of glaucoma classification, trying to answer the question, what are we defining? You know, what are the essential diagnostic domains? Um, we had a working group, um, thinking deeply about the context and use cases of any glaucoma definition.

Could we have just one operational definition or... that satisfies the requirements of all, you know, different kinds of research, or would we need multiple, or how, how should we handle that? And then working groups focused on process and governance and implementation and dissemination, like, um, who should, uh, be involved in this process? Um, how will we update definitions of glaucoma in the future? How do we get key stakeholders involved and who those would be, and how to implement and disseminate? So, you know, each of these, um, working groups had, uh, dedicated time to, uh, during the workshop to, um, talk about their, uh, issues.

Uh, it was a very productive discussion, and then at the end, we had kind of an open, uh, discussion of, um, brainstorming and ideas of, you know, what would an operational definition of glaucoma really look like? What would be the, uh, form of it, so to speak?

But to, to be able to apply this in a reproducible fashion in a structured scientific environment is a completely different challenge.

challenge.I will say that the workshop, um, wanted to focus, uh, our work on glaucoma definitions as applying first to research, you know, kind of a research-focused approach.

Sophia, um, how concentrated is the AI landscape actually?

One research insight we've been deriving is around network connectivity, whether that's a person or an organization.

How connected are they to the rest of the ecosystem? You actually have certain policy makers like Senators Brian Schatz and Chris Murphy that are very connected within their DC policy and think tank circles.

Another important question here, which are the stakeholder groups that are systematically underrepresented in the map? And right now we see certain categories of groups like ethics, bias, and rights, as well as labor and civil society, that do not have connections to kind of the frontier labs as well as the infrastructure and compute groups, and we see a lot of opportunity to actually build bridges with these types of people involved in shaping policy.

What are you hoping that people will actually get out of your Mapping AI project?

Since we've launched Mapping AI, we've just had a lot of inbound interest from everyone from academic researchers to certain think tanks that want to use this tool to actually develop much broader coalitions, um, to advocate for certain policy changes, as well as just the general public.

So this is as much as kind of like an insight discovery tool as it is just an experiment to understand, uh, what the future of civic technology could look like and how we can build this as openly and in the public as possible.

Sophia, um, how concentrated is the AI landscape actually?

One research insight we've been deriving is around network connectivity, whether that's a person or an organization.

How connected are they to the rest of the ecosystem? You actually have certain policymakers like Senators Brian Schatz and Chris Murphy that are very connected within their DC policy and think tank circles.

Another important question here, which are the stakeholder groups that are systematically underrepresented in the map? And right now we see certain categories of groups like ethics, bias, and rights, as well as labor and civil society, that do not have connections to kind of the frontier labs as well as the infrastructure and compute groups, and we see a lot of opportunity to actually build bridges with these types of people involved in shaping policy.

What are you hoping that people will actually get out of your Mapping AI project?

Since we've launched Mapping AI, we've just had a lot of inbound interest from everyone from academic researchers to certain think tanks that want to use this tool to actually develop much broader coalitions, um, to advocate for certain policy changes, as well as just the general public.

So this is as much as kind of like an insight discovery tool as it is just an experiment to understand, uh, what the future of civic technology could look like and how we can build this as openly and in the public as possible.

Can you explain how this works, Sophia?

You can actually view around eighteen hundred different people and organizations that we believe are shaping the conversation about US AI policy today.

And so you can click around and actually be able to look at their regulatory stance, their AGI timeline, so when they expect artificial general intelligence to arrive, as well as their funding model and the types of people and organizations they're connected to.

And so we're trying to track really the structure of the entire ecosystem.

[laughs] Sophia, what about you? What led you to do this in your spare time?

AI is this kind of, like, rapidly evolving technology that's starting to collide with almost every other technological domain, and I see this very actively in the space industry where I have formal background and also just in market trends.

And our way of making an impact in this space is trying to create a transparency tool.

We see this as kind of an opportunity for the public to get involved.

Can you explain how this works, Sophia?

You can actually view around 1,800 different people and organizations that we believe are shaping the conversation about US AI policy today.

And so you can click around and actually be able to look at their regulatory stance, their AGI timeline, so when they expect artificial general intelligence to arrive, as well as their funding model and the types of people and organizations they're connected to.

And so we're trying to track really the structure of the entire ecosystem.

[laughs] Sophia, what about you? What led you to do this in your spare time?

AI is this kind of, like, rapidly evolving technology that's starting to collide with almost every other technological domain, and I see this very actively in the space industry where I have formal background and also just in market trends.

And our way of making an impact in this space is trying to create a transparency tool.

We see this as kind of an opportunity for the public to get involved, even if they are not sort of in Silicon Valley themselves, uh, developing these models.