In our November 2023 CharityVillage Connects podcast episode, we examined how artificial intelligence is taking the world by storm – with the nonprofit sector being no exception. 

As part of our discussions, we interviewed Jason Shim, Chief Digital Officer of the Canadian Centre for Nonprofit Digital Resilience. In our interview, Jason addressed a question increasingly being asked by nonprofit professionals across Canada – will artificial intelligence take my job? We also asked Jason to give us some insight into the barriers preventing nonprofits from embracing this technology, as well as the importance of keeping a human-centred approach to the tools.  

We asked Jason to address one of the very common fears that nonprofit professionals may have about artificial intelligence – will it take my job? 

Jason Shim: And so those are very real concerns that folks have. And I think that there’s a role for organizations to play in helping to navigate that change and working with folks to make sure that AI usage within organizations is helping people do their jobs and helping to advance the mission itself.  

And when using AI in work, especially around language models, and some of you may have already experienced this as you’re experimenting and exploring some of these language models, is that sometimes when you put in a question, it can be confidently incorrect. So it can produce a response that may have a loose relationship with reality, but it’s going to say it with an authority that may not be actually true. So those are the kinds of things too that folks need to be aware of, that you really need to have those processes in place to make sure that some of the outputs are actually valid.  

For a sector that is often slow to embrace technological change, we were curious what barriers may prevent the nonprofit sector from harnessing the power of AI? 

Jason Shim: The things that maybe come to mind are the classic ones that always come to mind with regards to technology adoption, around funding, resourcing within your organization, capacity, in training. So, you know, those are some of the big, high-level considerations that present as barriers for organizations.  

And I think that it’s helpful to also get a sense of where, you know, some of the stats around that. CanadaHelps may help paint a picture of what some of the barriers may be. And so in this survey, it had 25% of organizations rating their knowledge of general office software as very good. So that’s 25%, and 54% felt that they didn’t have enough funding to make greater use of software and digital tools, and less than half, or 38%, had already integrated use of computer technology, software, digital tools, or other software-empowered processes.  

And so when we look at the current state of some organizations, there are some organizations that are well on their way, that have been on the digital road for quite a while. But in terms of the barriers that present, I mean, some of it is that within organizations, there may be limited capacity to even have the AI conversation. They may still be having conversations around, hey, how do I get a computer that is working well, that is reliable on a day-to-day basis?  

And another is, even if AI is implemented in an organization, it’s that training element that is really critical for organizations. So it’s not just about throwing technology in front of folks and expecting, oh, AI is going to take care of it all. It’s that, even in the last year or so, how AI can be used has evolved quite a bit. So how are we going to ensure that, within an organization, there’s ongoing training, support, and development? How do we build these learning communities, as well, within organizations and within our professional networks? 

For organizations and individuals who are ready to start experimenting with artificial intelligence, what should they know before they start? Should they view AI as a co-pilot? 

Jason Shim: When looking at using AI, I really like the framing that you shared around using it as a co-pilot because, ultimately, if something is generated and, let’s say there are any issues with it, there still needs to be someone who’s accountable for that output at the end of the day. Because you can’t necessarily just point at the AI and be like, oh, well, it was the AI part. So I think definitely having that understanding that, okay, just like you’re using a word processor, you can’t necessarily blame things on the word processor. It’s how you use the technology that really needs to be understood. 

I think there are a lot of things to be drawn sometimes from how fictional narratives talk about how do you handle these kinds of magical forces. In the context of, say, Star Wars, you know, there’s a kind of a light side and a dark side. And at the end of the day, using technology can be like using the Force in that you have choices that ultimately you need to make and they can be a light side, you know, for good, dark side, for bad, or some of them can be categorized with a neutral kind of in the middle. I think there are a lot of parallels that can be drawn where it’s like, the dark side is often associated with what is quick, what is easy. And it’s very tempting to do those things.  

There can be guidelines that can be written around that to guide people towards hey, if you’re using this to write an entire thing and, you know, publish it sight unseen, don’t do that. You know, that’s kind of a dark side kind of usage, whereas the light side is taking that kind of co-pilot behaviour and letting it guide the work that’s being done. But ultimately, it’s really channelling it and using that human element to connect it to the mission, to fully embrace the power that AI can bring to an organization as well.  

So I think being clear for an organization on what its internal processes are is really important because when you think about AI as a tool to automate things, if an organization doesn’t have its internal processes either documented or understood, then throwing AI at processes that are not well understood is just going to create more noise and more trouble. So when looking at some of the technology, I think taking that step back and really analyzing what is it that we’re setting out to do, what is it that we’re looking to accelerate, and then going from there. And I think it can be done in a very kind of methodical way to address those things. 

Want to hear more from Jason? Listen to his full interview in the video below. 

Listen to Jason and other technological experts discuss how artificial intelligence is set to revolutionize the sector in our new CharityVillage Connects podcast episode. Click here to listen.