CharityCAN’s 2023: Models and weights and biases, oh my!

It’s the end of 2023, which means it’s time to take a look back to see what’s happened at CharityCAN over the last 12 months.

Since we’re a tech company at heart, you can probably guess that this wrap up will talk about artificial intelligence (AI) quite a bit. You’re not wrong! As I alluded to in our 2022 roundup, we started off the year diving into deep learning in a big way. The whole development team worked on a deep learning for coders course so we could wrap our heads around some of the underpinnings of the huge advancements in AI that have appeared in the last year or so.

We took the concepts we learned there and started playing around with tools offered by OpenAI around their GPT language models to experiment and see what we could apply to CharityCAN. I’m not always one to hop on the “new shiny tech” bandwagon – there are plenty of times in the past where we’ve been promised amazing things by AI (self-driving cars, anyone?) only for the reality to fall short of expectations. This time seems different though – maybe because we’ve already been able to work with language-model powered tools ourselves to get real results.

This year, we’ve used language models like Github Copilot internally to help our developers write and understand code. I’ve used ChatGPT with DALL·E to help generate presentations or to understand concepts in deep learning. And we’ve been able to use language models in our platform to build and create new features.

The first of those features to be released to the public was our AI-generated snapshots in our Prospect Profiles. These summaries take the raw data available in CharityCAN and turn it into something easily digestible. You can export or import those summaries where you need them, saving the time of writing your own prospect briefs. I love this feature because it aligns with where I think we’re going with AI in the near-term: a future where CharityCAN users can use our platform and other AI-powered tools to save time doing menial tasks so you can have more time to do the things that are really valuable. In prospect research, that might mean that CharityCAN can suggest and prepare reports on new potential major gift prospects, and prospect researchers and managers can focus on the best way to approach and connect with those new donors.

In non-AI related features, we also added new ways to mine your organization’s connections in CharityCAN. Ways to see how you are connected to donors geographically, as well as finding connected Federal Corporations. Also ways to see donation information directly in individual connections so you can better find those valuable connections in your network.

In terms of new data, we added donor demographics to our postal code data and new granting information for registered Canadian charities – plus new ways to use that data in our donor screening.

I’m excited to see what 2024 will bring – we’ll hopefully have some exciting new things to share soon!

A programmer working at a desk

A stereotypical software developer diving into deep learning, as presented by DALL·E (not bad except I can’t grow a beard in real life)