Transcript

Ross Dawson: Beth, it is a delight to have you on the show.

Beth Kanter: Oh, it’s a delight to be here. I’ve admired your work for a really long time, so it’s really great to be able to have a conversation.

Ross Dawson: Well, very similarly, for the very, very long time that I’ve known of your work, you’ve always focused on how technologies can augment nonprofits. I’d just like to hear—well, I mean, the reason is obvious, but I’d like to know the why, and also, what is it that’s different about the application of technologies, including AI, to nonprofits?

Beth Kanter: So I think the why is, I mean, I’ve always—I’ve been working in the nonprofit sector for decades, and I didn’t start off as a techie. I kind of got into it accidentally a few decades ago, when I started on a project for the New York Foundation for the Arts to help artists get on the internet. I learned a lot about the internet and websites and all of that, and I really enjoyed translating that in a way that made it accessible to nonprofit leaders. So that’s sort of how I’ve run my career in the last number of decades: learn from the techies, translate it, make it more accessible, so people have fun and enjoy the exploration of adopting it.

And that’s what actually keeps me going. Whenever a new technology or something new comes out, it’s the ability to learn something and then turn around and teach it to others and share that learning. In terms of the most recent wave of new technology—AI—my sense is that with nonprofits, we have some that have barreled ahead, the early adopters doing a lot of cutting-edge work, but a lot of organizations are just at that they’re either really concerned about all of the potential bad things that can happen from the technology, and I think that traps them from moving forward, or others where there’s not a cohesive strategy around it, so there’s a lot of shadow use going on.

Then we have a smaller segment that is doing the training and trying to leverage it at an enterprise level. So I see organizations at these different stages, with a majority of them at the exploring or experimenting stage.

Ross Dawson: So, you know, going back to what you were saying about being a bit of a translator, I think that’s an extraordinarily valuable role—how do you take the ideas and make them accessible and palatable to your audience? But I think there’s an inspiration piece as well in the work that you do, inspiring people that this can be useful.

Beth Kanter: Yeah, to show—to keep people past their concerns. There’s a lot of folks, and this has been a constant theme for a number of decades. The technology changes, but the people stay the same, and the concerns are similar. It’s going to take a long time to learn it, I feel overwhelmed. I think AI adds an extra layer, because people are very aware, from reading the headlines, of some of the potential societal impacts, and people also have in their heads some of the scie