Thanks for this. I’ve read through the whole thing though haven’t thought about the numbers in depth yet. I’m hoping to write a forum post with my retrospective on the AI in Context video at some point!
A few quick thoughts which I imagine won’t be very new to people:
Comment and comment analysis could also be a proxy for engagement and quality of engagement
Someone said that it would be hard to predict future success from AI in context based only on our one big video and I strongly agree. We’re hoping to release our next one in the next month, and I’m really excited about it but by default, we should expect a lot of regression to the mean. (Note: I wouldn’t even think of us as having two videos. The other one is just a channel trailer we threw up to have something to introduce people to the channel.)
I like this question on the value of subsequent viewer minutes, and I don’t currently have a take. I think some complicating factors are: - For one thing, it seems like a 5-minute video wouldn’t do very well on YouTube, so it’s not like it’s really an option necessarily to make a lot of 5-minute videos relative to one 45-minute video, because 45-minute videos just have a niche. You might still want to make more 20-minute videos and fewer 45-minute videos. - I’m also not convinced that effort scales with time. Certainly editing time does, but often what you’re trying to do (at least what we’re trying to do) is tell a story and there’s a certain length that allows you to tell the story. And so it’s not convertible or fungible in the way that it might naively appear. - To the point above about telling a story, I think part of the value of a video is whether people come away with like an overall sense of what the video is about in a way that’s memorable/the takeaways, and that might require telling a good story. Some stories might take 20 minutes to tell and some stories might take 45 minutes to tell. Maybe you want to focus on the stories that take less time to tell if it takes you a lot less time or money to make the video, but as I say I don’t think effort scales that way for us.
For what it’s worth we’re not currently focused really heavily on getting to the right target audience. We’re currently doing product validation to just see if we know how to make good videos, but will be excited to think about that more in the future.
Yes, there is lots to consider and I don’t want to suggest that my analysis is comprehensive or should be used as the basis for all future funding decisions for AI safety communications.
Very excited for the next AI in Context video.
I expect there to be lots of experimentation that naturally occurs with people doing what they feel is best and getting out the messages they find important. I am also slightly worried about goodharting and such, for obvious reasons. I think the analysis should be taken with a grain of salt. It’s a first pass at this.
Thanks for this. I’ve read through the whole thing though haven’t thought about the numbers in depth yet. I’m hoping to write a forum post with my retrospective on the AI in Context video at some point!
A few quick thoughts which I imagine won’t be very new to people:
Comment and comment analysis could also be a proxy for engagement and quality of engagement
Someone said that it would be hard to predict future success from AI in context based only on our one big video and I strongly agree. We’re hoping to release our next one in the next month, and I’m really excited about it but by default, we should expect a lot of regression to the mean. (Note: I wouldn’t even think of us as having two videos. The other one is just a channel trailer we threw up to have something to introduce people to the channel.)
I like this question on the value of subsequent viewer minutes, and I don’t currently have a take. I think some complicating factors are:
- For one thing, it seems like a 5-minute video wouldn’t do very well on YouTube, so it’s not like it’s really an option necessarily to make a lot of 5-minute videos relative to one 45-minute video, because 45-minute videos just have a niche. You might still want to make more 20-minute videos and fewer 45-minute videos.
- I’m also not convinced that effort scales with time. Certainly editing time does, but often what you’re trying to do (at least what we’re trying to do) is tell a story and there’s a certain length that allows you to tell the story. And so it’s not convertible or fungible in the way that it might naively appear.
- To the point above about telling a story, I think part of the value of a video is whether people come away with like an overall sense of what the video is about in a way that’s memorable/the takeaways, and that might require telling a good story. Some stories might take 20 minutes to tell and some stories might take 45 minutes to tell. Maybe you want to focus on the stories that take less time to tell if it takes you a lot less time or money to make the video, but as I say I don’t think effort scales that way for us.
For what it’s worth we’re not currently focused really heavily on getting to the right target audience. We’re currently doing product validation to just see if we know how to make good videos, but will be excited to think about that more in the future.
Thanks Chana.
Yes, there is lots to consider and I don’t want to suggest that my analysis is comprehensive or should be used as the basis for all future funding decisions for AI safety communications.
Very excited for the next AI in Context video.
I expect there to be lots of experimentation that naturally occurs with people doing what they feel is best and getting out the messages they find important. I am also slightly worried about goodharting and such, for obvious reasons. I think the analysis should be taken with a grain of salt. It’s a first pass at this.
Agree on a lot of the points on video production.