Wednesday, October 25, 2023

On tech and giving

                                                        Photo by Uriel Soberanes on Unsplash

I had a chance to speak on a zoom panel today. In the before times, this would not be worthy of a comment - it's what I did. Dozens in a year. However, since getting covid that became long covid, I haven't been able to do...much. Between managing the illness, doctors and tests, and staying employed I'm at my max. 

It was fun to chat with folks. The event was hosted by Stanford Alumni Association, Stanford Alumni in Public Service, the Latino Alumni Association, and a few others - there is a recording but I don't know if it will be available beyond the hosts' networks. 

During the course of the hour, I got asked about AI and philanthropy. The Blueprint 2024 (coming on December 15, 2023) has much to say about this. But during the panel I realized something I've thought about for years, but don't think I've said before. 

Here are two true things:

1. In the past 20 years there has been a lot of innovation in digital tech and a lot of tech has been applied to giving - crowdfunding, text giving, online donations, information sources, giving platforms, etc. 

2. Participation rates in charitable giving in the U.S.A. over the last 20 years have gone down. (Total giving keeps going up, but that's from more rich people making more big dollar gifts.)

More tech. Fewer givers.* No one invested in giving innovation wants to hear that. Because, sadly, innovation in giving has become synonymous with throw some tech at it. If "innovation" is supposed to lead to "more," then it's not working. 


Another thought - one I also share in more detail in the Blueprint 2024

Lots of people are focused on AI. There are vendors and others in the social sector who are eager to sell you some AI powered gizmo to improve your fundraising (this is biggest market at moment). Here's the catch:

  1. AI gets trained on data
  2. The best data we have, on financial gifts to nonprofits, is wildly incomplete, misses out on many kinds of giving, is culturally misaligned for many givers, misses everything having to do with political giving, and ignores a great deal of the giving that other tech makes possible - for example, most crowdfunding or direct gifts to individuals 
  3. So today's AIs are being trained on yesterday's bad data
  4. This is a good thing, how?  How will it help you in the future?

More on this in the #Blueprint. But happy to talk about it before then. I don't hang out on the site formerly known as twitter anymore - it's a bit too much like late night at a KKK frat party for me. You can find me on LinkedIn, Bluesky and Mastodon - c'mon over, we'll chat.

*Yes, there are problems with the data. I know that you know that I know this. I write about it all the time. In the "truth" above I'm drawing from GivingUSA data and analyses thereof over time. So the most basic data we have on giving - financial contributions to 501 c 3 nonprofits. It's not the whole story by any means, but it's pretty comprehensive and accurate for what it is.