Steve Newman built a word processor with the last great platform shift to the Internet. Perhaps this is the next opportunity?
My guess is that you could work/automate towards something like the scenario you describe here:
> For each of these important questions (and many more), I think the path forward involves picking the brains of a diverse group. So I’m starting a project to do exactly that. We’ll pick a topic, convene a group, drill down on as many important, confusing, and/or contentious details as we can identify, and publish the results. Then do it again, and again, and again. There’s little danger of running out of topics.
> We’re kinda getting accustomed to the idea of real-time translation (you speak in French, they hear English) although it is still mind-blowing that this will be shipping Real Soon Now with OpenAI’s GPT-4o.
> But real-time text hermeneutics, unearthing the hidden meaning of text and between texts? That’s wild.
> For instance, crossing this point with the previous one…
> What would it mean to listen to a politician speak on TV, and in real-time see a rhetorical manoeuvre that masks a persuasive bait and switch?
There was a startup called Crowdsmart who thought along similar lines worth checking out--Kim Polese and John Seely Brown were involved: https://www.crowdsmart.ai/
Using AI to scale this work does seem like a very interesting direction. The process as I'm envisioning it initially will involve a *ton* of work in facilitation and editing. That's bad, insofar as it's a lot of work; but potentially good, insofar as it could identify the opportunity to add a lot of value by automating that work.
Steve Newman built a word processor with the last great platform shift to the Internet. Perhaps this is the next opportunity?
My guess is that you could work/automate towards something like the scenario you describe here:
> For each of these important questions (and many more), I think the path forward involves picking the brains of a diverse group. So I’m starting a project to do exactly that. We’ll pick a topic, convene a group, drill down on as many important, confusing, and/or contentious details as we can identify, and publish the results. Then do it again, and again, and again. There’s little danger of running out of topics.
Informed by an embedding-centric (rather than prompt-centric) approach as speculated on by Matt Webb https://interconnected.org/home/2024/05/31/camera
> We’re kinda getting accustomed to the idea of real-time translation (you speak in French, they hear English) although it is still mind-blowing that this will be shipping Real Soon Now with OpenAI’s GPT-4o.
> But real-time text hermeneutics, unearthing the hidden meaning of text and between texts? That’s wild.
> For instance, crossing this point with the previous one…
> What would it mean to listen to a politician speak on TV, and in real-time see a rhetorical manoeuvre that masks a persuasive bait and switch?
There was a startup called Crowdsmart who thought along similar lines worth checking out--Kim Polese and John Seely Brown were involved: https://www.crowdsmart.ai/
Thanks for the pointers!
Using AI to scale this work does seem like a very interesting direction. The process as I'm envisioning it initially will involve a *ton* of work in facilitation and editing. That's bad, insofar as it's a lot of work; but potentially good, insofar as it could identify the opportunity to add a lot of value by automating that work.